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Memoization is awesome. Let's abuse it. TL;DR: Don't apply premature optimization too early Problems Readability
Code Complexity
Premature Optimization
Obscured Logic Solutions Apply memoization in actual real business situations, and measure its impact through empirical benchmarks. Context Memoization can help you improve the performance of recursive functions involving redundant computations but compromise code readability and maintainability. It would help if you only used it with strong factual evidence on real business case scenarios. Sample Code Wrong memo = {}
def factorial_with_memo(n):
    if n in memo:
        return memo[n]
    if n == 0:
        return 1
    result = n * factorial_with_memo(n-1)
    memo[n] = result
    return result
  
  # This function optimizes the computation of factorials
  # by storing previously computed values,
  # reducing redundant calculations 
  # and improving performance for large inputs. Right def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1) Detection [x]Semi-Automatic You can search for all places where you are using this technique and validate if they are worth it. Exceptions Real performance problems with strong factual evidence Tags Premature Optimization Level [x]Intermediate AI Generation Unless you explicitly ask the IAs to use this technique, they will suggest cleaner solutions. AI Detection ChatGPT, Gemini, and Claude.ai detect some problems with this technique but do not mention readability as a concern. Conclusion It would be best if you kept a balance between performance optimization and code clarity. You can consider alternatives such as iterative approaches or algorithmic optimizations since memoization significantly compromises code readability. Relations Code Smell 06 - Too Clever Programmer Code Smell 20 - Premature Optimization More Info Wikipedia Disclaimer Code Smells are my opinion. Credits Photo by Steffen Lemmerzahl on Unsplash A cache with a bad policy is another name for a memory leak. Rico Mariani Software Engineering Great Quotes This article is part of the CodeSmell Series. How to Find the Stinky Parts of your Code Memoization is awesome. Let's abuse it. Memoization is awesome. Let's abuse it. TL;DR: Don't apply premature optimization too early TL;DR: Don't apply premature optimization too early premature optimization Problems Readability Code Complexity Premature Optimization Obscured Logic Readability Code Complexity Premature Optimization Obscured Logic Solutions Apply memoization in actual real business situations, and measure its impact through empirical benchmarks. Apply memoization in actual real business situations, and measure its impact through empirical benchmarks. memoization Context Memoization can help you improve the performance of recursive functions involving redundant computations but compromise code readability and maintainability. It would help if you only used it with strong factual evidence on real business case scenarios. strong factual evidence real Sample Code Wrong memo = {}
def factorial_with_memo(n):
    if n in memo:
        return memo[n]
    if n == 0:
        return 1
    result = n * factorial_with_memo(n-1)
    memo[n] = result
    return result
  
  # This function optimizes the computation of factorials
  # by storing previously computed values,
  # reducing redundant calculations 
  # and improving performance for large inputs. memo = {}
def factorial_with_memo(n):
    if n in memo:
        return memo[n]
    if n == 0:
        return 1
    result = n * factorial_with_memo(n-1)
    memo[n] = result
    return result
  
  # This function optimizes the computation of factorials
  # by storing previously computed values,
  # reducing redundant calculations 
  # and improving performance for large inputs. Right def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1) def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1) Detection [x]Semi-Automatic [x] Semi-Automatic [x] You can search for all places where you are using this technique and validate if they are worth it. Exceptions Real performance problems with strong factual evidence Real performance problems with strong factual evidence Tags Premature Optimization Premature Optimization Level [x]Intermediate [x] Intermediate [x] AI Generation Unless you explicitly ask the IAs to use this technique, they will suggest cleaner solutions. AI Detection ChatGPT, Gemini, and Claude.ai detect some problems with this technique but do not mention readability as a concern. Claude.ai Conclusion It would be best if you kept a balance between performance optimization and code clarity. You can consider alternatives such as iterative approaches or algorithmic optimizations since memoization significantly compromises code readability. Relations Code Smell 06 - Too Clever Programmer Code Smell 06 - Too Clever Programmer Code Smell 20 - Premature Optimization Code Smell 20 - Premature Optimization More Info Wikipedia Wikipedia Disclaimer Code Smells are my opinion . opinion Credits Photo by Steffen Lemmerzahl on Unsplash Steffen Lemmerzahl Unsplash A cache with a bad policy is another name for a memory leak. A cache with a bad policy is another name for a memory leak. Rico Mariani Rico Mariani Software Engineering Great Quotes Software Engineering Great Quotes This article is part of the CodeSmell Series. How to Find the Stinky Parts of your Code How to Find the Stinky Parts of your Code

Premature Memoization: How to Properly Apply It - Code Smell 250

I lost hundreds of thousands of dollars on hiring ineffective sales specialists for my B2B startup. With the knowledge I have now, I could have avoided that. In 5 years of scaling my company, Competera, from zero to $28.2 billion in revenues, I’ve hit all sorts of bumps trying to develop an effective sales strategy. This experience taught me a lot. Today, my company has over 120 clients worldwide, with checks ranging from $50,000 to–300,000. Here are my four rules for managing a sales department in a B2B — in early-stage and late-stage companies. startup Always start with founder-led sales. When I started my company, I would manage sales on my own. In 9 months, I closed three deals for almost $1 million ARR. A founder’s involvement in sales at a B2B startup is unavoidable (and desirable).  I don't know of any cases of growing a B2B SaaS company any other way. If you want to expand your early-stage enterprise, you need to do sales yourself until you reach $3-5 million ARR. Hiring a sales account executive early is like having someone else between you and your child. No one will be more passionate and enthusiastic about selling your product than a founder. The most valuable thing you get by doing sales yourself is early feedback from users and the opportunity to build a long-term relationship with them. B2B sales are also called human-to-human for a reason. As a startup founder, you build valuable interactions and nurture relationships with potential customers. I always tell other founders, “In your first years, make friends – not customers.” One more reason to start with founder-led sales is an extremely high conversion rate. While the standard SaaS conversion rate is 15-20%, I’ve seen firsthand that a founder-led startup’s conversion rate can be as high as 60%. That’s important for any company, let alone a new one that is trying to stay afloat, start making money, and grow. Craft sales playbook A startup founder who leads deals and gets feedback from customers has more understanding of their company’s value proposition, goals, and its clients’ needs. All of this information has to become the foundation for salespeople who’ll join the company at later stages. The knowledge generated during those first months or years by the founder should form the basis of a sales playbook. It’s a blueprint that helps future reps navigate the sales process, train new hires, and deal with difficult sales cases. Crafting such a guide will benefit your sales effectiveness (some say by up to 50%). No competent sales manager will join a company without a playbook with all the necessary sales information. So until a playbook is completed, stick to a founder-led sales strategy, and don’t waste budget on sales reps. Here’s what to include in your first sales playbook: . Write up your background, the reason you started the company, and the vision of the future you can create with your product, and add success stories that you can boast about. The story you sell Have a detailed description of a target customer, her day in life, problems, pains, values, budget range, and other indicators that are important for you. At Competera, we describe our ICP this way: “A commercial director who is responsible for increasing the company’s profit in retail stores with more than $100 million in revenue.” Target ICP (ideal customer profile). Describe how interaction with your customers looks like — from an inbound request to rollout. Ideal sales formula. . Mention parts of your pitch and product that collect aha moments. Aha moments . What doubts do your customers have, and what arguments can you use to clear these doubts up? Key objections you face Never outsource sales at B2B startups After a year of leading sales, I decided to hire sales representatives. I chose a well-proven outsourcing sales team from the U.K. During a year of our partnership, they closed… one deal. After this experience, I never outsource sales and advise you to do the same. Here are my arguments against outsourcing sales: . Startups update the product frequently (every six weeks at my firm), and external sales reps couldn’t follow the iterations. You lose alignment between teams and reduce your chances of landing a long-term deal. An outsourced team doesn’t keep up with product changes . In B2B sales, customers estimate your startup’s energy, vision, and how engaged you are. An outsourced team can’t give you this, and it’s vital in B2B. You lose your company’s vibe in communication with clients . After an external sales manager provided me with a client’s feedback that sounded unreal to me, I decided to get to the bottom of things. So, I called a potential customer to figure out the problem. It turned out that the sales manager was so annoying that he just made up an excuse to get rid of him! Due to the outsourced team not being as involved in the sales process, I was missing important comments and the opinions of potential clients. You don’t get honest, direct feedback I believe that, for a startup with up to $10 million ARR, outsourcing sales can be devastating. Sure, there were benefits to our collaboration. The outsourcing team improved the sales structure and helped finalize my company’s playbook. But we lost a lot of time that we could have spent hammering out long-term deals. Always have at least two in-house sales managers. On average, 42.5% of sales reps take ten months or longer to become productive enough to show results. You should diversify your risks and hire at least two managers to compare performance. Check intermediate results of the new hires: conversation rates from the first positive response, from response to demo, from demo to follow-up conversation, and from follow-up conversation to “money.” Outstanding professionals are never actively searching for a new job, so you will have to headhunt. Identify companies from your industry that sell your average check, find out about their sales managers (LinkedIn can help), and convince them to work for you. I discovered the right candidate from Germany on LinkedIn and spent two years talking to him online. Then I found his former boss on social media and promised a stake in Competera if he would convince this guy to join me. Now, this sales manager brings Competera $3 million annually, and his former boss is our advisor and has a share in the company. Another way to find a strong candidate is to turn to a boutique agency that specializes in hiring sales managers. They test candidates, assess their psychological profile, and so on. We hired such an agency and received 117 candidates, from which we selected 40 to take the test. Of all those who passed it, five were invited for an interview, and only one got the job — the best one. Key points Until a startup’s ARR reaches several million dollars, its founder should do the sales themselves. Founder-led sales show a 60% conversion rate, while the average sales manager’s rate is up to 20%. Don’t hire a sales team unless you have a playbook, a guide containing key info about a startup’s vision, ideal customer, sales formula, and how to handle objections/rejections. Gathering this information will improve your sales effectiveness. Sales reps in B2B startups should always be in-house. An outsourced team won’t be 100% synced with your dev team, and they won’t talk to clients as much to get their feedback. Well-performing sales managers never actively look for a job. Headhunt specialists from your rivals or hire a boutique recruitment agency.

‘Outsourcing Sales Can Kill Your B2B Startup’: Here’s How To Manage Sales Properly

The context package effectively manages and propagates timeouts and deadlines through a chain of calls in your product architecture. However, be mindful when using it. It's essential to be aware that it can also introduce performance degradation to your service in some cases with external calls. In this article, I tell you about some of them. TLDR; or have a chance to destroy the performance of your service. Be careful. Use a good cook recipe. ctx.WithTimeout ctx.WithDeadline For this article, I use as an example of an external service we use. But the cases I’m talking about are generic and can be applied to any other service or database. Redis Let’s start with a basic example of code to make a call to Redis: import "github.com/go-redis/redis/v9"

reddisClient := redis.NewClient(...)

ctx := context.Background() 
ctx, cancel := context.WithTimeout(ctx, 200*time.Millisecond) 
defer cancel()

result, err := reddisClient.Get(ctx, "redis-key").Result() This code tells us that we expect a response for the Get request to come within 200 milliseconds. And everything looks logical. But what if the Get request exceeds the timeout of 200 milliseconds? When the context deadline is exceeded, all operations associated with this context should be terminated. Let's take a look under the hood at what happens when the context deadline is exceeded.
The Redis client: Closed the current connection as a connection is not safe to re-use it Established new connection: Performed handshakes using a new connection. These three steps basically mean that we don’t use the connection pool anymore if we have a good amount of requests with exceeded deadlines. Every time for requests that exceed the deadline, we close the current connection and open a new one. It makes each operation slower and adds risks to exceeding the deadline one more time. As a result, it can be an infinite loop, It affects the performance SLA of your service and bottleneck performance for the whole product. What can we do to avoid this problem? Context is used to propagate timeouts through a chain of calls, and each call has a random timeout that depends on the timing of previous calls. To prevent it for some calls in a chain, we can use a separate timeout for every external call: ctx := context.Background()

result1, err := reddisClient.Get(ctx.WithTimeout(ctx, time.Second), "redis-key-1").Result() 

result2, err := reddisClient.Get(ctx.WithTimeout(ctx, time.Second), "redis-key-2").Result() Don’t set up timeout too small because it can cause a problem we discuss here. In a case where we need to respect incoming context timeout and build a response within that timeout, we can also use a go-routine to perform a call to an external service: ctx, cancel := context.WithCancel(ctx) 

// Process asynchronously in a goroutine. 
go func() { 
  defer cancel() 

  result, err := reddisClient.Get(context.Background(), "redis-key").Result() 
  ch <- result 
  close(ch)
}() 

select { 
case <-ctx.Done(): 
  // error happend 
case res := <-ch: 
  // success 
} In the code above, we build a response in time, but we also give redisClient to complete the Get request in the background.

Go Context Timeouts and External Calls: Cook Them Properly

Anne of Green Gables by L. M. Montgomery, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . Mrs. Rachel Lynde Is Properly Horrified CHAPTER IX. Mrs. Rachel Lynde Is Properly Horrified ANNE had been a fortnight at Green Gables before Mrs. Lynde arrived to inspect her. Mrs. Rachel, to do her justice, was not to blame for this. A severe and unseasonable attack of grippe had confined that good lady to her house ever since the occasion of her last visit to Green Gables. Mrs. Rachel was not often sick and had a well-defined contempt for people who were; but grippe, she asserted, was like no other illness on earth and could only be interpreted as one of the special visitations of Providence. As soon as her doctor allowed her to put her foot out-of-doors she hurried up to Green Gables, bursting with curiosity to see Matthew and Marilla’s orphan, concerning whom all sorts of stories and suppositions had gone abroad in Avonlea. Anne had made good use of every waking moment of that fortnight. Already she was acquainted with every tree and shrub about the place. She had discovered that a lane opened out below the apple orchard and ran up through a belt of woodland; and she had explored it to its furthest end in all its delicious vagaries of brook and bridge, fir coppice and wild cherry arch, corners thick with fern, and branching byways of maple and mountain ash. She had made friends with the spring down in the hollow—that wonderful deep, clear icy-cold spring; it was set about with smooth red sandstones and rimmed in by great palm-like clumps of water fern; and beyond it was a log bridge over the brook. That bridge led Anne’s dancing feet up over a wooded hill beyond, where perpetual twilight reigned under the straight, thick-growing firs and spruces; the only flowers there were myriads of delicate “June bells,” those shyest and sweetest of woodland blooms, and a few pale, aerial starflowers, like the spirits of last year’s blossoms. Gossamers glimmered like threads of silver among the trees and the fir boughs and tassels seemed to utter friendly speech. All these raptured voyages of exploration were made in the odd half hours which she was allowed for play, and Anne talked Matthew and Marilla half-deaf over her discoveries. Not that Matthew complained, to be sure; he listened to it all with a wordless smile of enjoyment on his face; Marilla permitted the “chatter” until she found herself becoming too interested in it, whereupon she always promptly quenched Anne by a curt command to hold her tongue. Anne was out in the orchard when Mrs. Rachel came, wandering at her own sweet will through the lush, tremulous grasses splashed with ruddy evening sunshine; so that good lady had an excellent chance to talk her illness fully over, describing every ache and pulse beat with such evident enjoyment that Marilla thought even grippe must bring its compensations. When details were exhausted Mrs. Rachel introduced the real reason of her call. “I’ve been hearing some surprising things about you and Matthew.” “I don’t suppose you are any more surprised than I am myself,” said Marilla. “I’m getting over my surprise now.” “It was too bad there was such a mistake,” said Mrs. Rachel sympathetically. “Couldn’t you have sent her back?” “I suppose we could, but we decided not to. Matthew took a fancy to her. And I must say I like her myself—although I admit she has her faults. The house seems a different place already. She’s a real bright little thing.” Marilla said more than she had intended to say when she began, for she read disapproval in Mrs. Rachel’s expression. “It’s a great responsibility you’ve taken on yourself,” said that lady gloomily, “especially when you’ve never had any experience with children. You don’t know much about her or her real disposition, I suppose, and there’s no guessing how a child like that will turn out. But I don’t want to discourage you I’m sure, Marilla.” “I’m not feeling discouraged,” was Marilla’s dry response, “when I make up my mind to do a thing it stays made up. I suppose you’d like to see Anne. I’ll call her in.” Anne came running in presently, her face sparkling with the delight of her orchard rovings; but, abashed at finding the delight herself in the unexpected presence of a stranger, she halted confusedly inside the door. She certainly was an odd-looking little creature in the short tight wincey dress she had worn from the asylum, below which her thin legs seemed ungracefully long. Her freckles were more numerous and obtrusive than ever; the wind had ruffled her hatless hair into over-brilliant disorder; it had never looked redder than at that moment. “Well, they didn’t pick you for your looks, that’s sure and certain,” was Mrs. Rachel Lynde’s emphatic comment. Mrs. Rachel was one of those delightful and popular people who pride themselves on speaking their mind without fear or favor. “She’s terrible skinny and homely, Marilla. Come here, child, and let me have a look at you. Lawful heart, did any one ever see such freckles? And hair as red as carrots! Come here, child, I say.” Anne “came there,” but not exactly as Mrs. Rachel expected. With one bound she crossed the kitchen floor and stood before Mrs. Rachel, her face scarlet with anger, her lips quivering, and her whole slender form trembling from head to foot. “I hate you,” she cried in a choked voice, stamping her foot on the floor. “I hate you—I hate you—I hate you—” a louder stamp with each assertion of hatred. “How dare you call me skinny and ugly? How dare you say I’m freckled and redheaded? You are a rude, impolite, unfeeling woman!” “Anne!” exclaimed Marilla in consternation. But Anne continued to face Mrs. Rachel undauntedly, head up, eyes blazing, hands clenched, passionate indignation exhaling from her like an atmosphere. “How dare you say such things about me?” she repeated vehemently. “How would you like to have such things said about you? How would you like to be told that you are fat and clumsy and probably hadn’t a spark of imagination in you? I don’t care if I do hurt your feelings by saying so! I hope I hurt them. You have hurt mine worse than they were ever hurt before even by Mrs. Thomas’ intoxicated husband. And I’ll never forgive you for it, never, never!” Stamp! Stamp! “Did anybody ever see such a temper!” exclaimed the horrified Mrs. Rachel. “Anne go to your room and stay there until I come up,” said Marilla, recovering her powers of speech with difficulty. Anne, bursting into tears, rushed to the hall door, slammed it until the tins on the porch wall outside rattled in sympathy, and fled through the hall and up the stairs like a whirlwind. A subdued slam above told that the door of the east gable had been shut with equal vehemence. “Well, I don’t envy you your job bringing that up, Marilla,” said Mrs. Rachel with unspeakable solemnity. Marilla opened her lips to say she knew not what of apology or deprecation. What she did say was a surprise to herself then and ever afterwards. “You shouldn’t have twitted her about her looks, Rachel.” “Marilla Cuthbert, you don’t mean to say that you are upholding her in such a terrible display of temper as we’ve just seen?” demanded Mrs. Rachel indignantly. “No,” said Marilla slowly, “I’m not trying to excuse her. She’s been very naughty and I’ll have to give her a talking to about it. But we must make allowances for her. She’s never been taught what is right. And you were too hard on her, Rachel.” Marilla could not help tacking on that last sentence, although she was again surprised at herself for doing it. Mrs. Rachel got up with an air of offended dignity. “Well, I see that I’ll have to be very careful what I say after this, Marilla, since the fine feelings of orphans, brought from goodness knows where, have to be considered before anything else. Oh, no, I’m not vexed—don’t worry yourself. I’m too sorry for you to leave any room for anger in my mind. You’ll have your own troubles with that child. But if you’ll take my advice—which I suppose you won’t do, although I’ve brought up ten children and buried two—you’ll do that ‘talking to’ you mention with a fair-sized birch switch. I should think that would be the most effective language for that kind of a child. Her temper matches her hair I guess. Well, good evening, Marilla. I hope you’ll come down to see me often as usual. But you can’t expect me to visit here again in a hurry, if I’m liable to be flown at and insulted in such a fashion. It’s something new in my experience.” Whereat Mrs. Rachel swept out and away—if a fat woman who always waddled could be said to sweep away—and Marilla with a very solemn face betook herself to the east gable. On the way upstairs she pondered uneasily as to what she ought to do. She felt no little dismay over the scene that had just been enacted. How unfortunate that Anne should have displayed such temper before Mrs. Rachel Lynde, of all people! Then Marilla suddenly became aware of an uncomfortable and rebuking consciousness that she felt more humiliation over this than sorrow over the discovery of such a serious defect in Anne’s disposition. And how was she to punish her? The amiable suggestion of the birch switch—to the efficiency of which all of Mrs. Rachel’s own children could have borne smarting testimony—did not appeal to Marilla. She did not believe she could whip a child. No, some other method of punishment must be found to bring Anne to a proper realization of the enormity of her offense. Marilla found Anne face downward on her bed, crying bitterly, quite oblivious of muddy boots on a clean counterpane. “Anne,” she said not ungently. No answer. “Anne,” with greater severity, “get off that bed this minute and listen to what I have to say to you.” Anne squirmed off the bed and sat rigidly on a chair beside it, her face swollen and tear-stained and her eyes fixed stubbornly on the floor. “This is a nice way for you to behave. Anne! Aren’t you ashamed of yourself?” “She hadn’t any right to call me ugly and redheaded,” retorted Anne, evasive and defiant. “You hadn’t any right to fly into such a fury and talk the way you did to her, Anne. I was ashamed of you—thoroughly ashamed of you. I wanted you to behave nicely to Mrs. Lynde, and instead of that you have disgraced me. I’m sure I don’t know why you should lose your temper like that just because Mrs. Lynde said you were red-haired and homely. You say it yourself often enough.” “Oh, but there’s such a difference between saying a thing yourself and hearing other people say it,” wailed Anne. “You may know a thing is so, but you can’t help hoping other people don’t quite think it is. I suppose you think I have an awful temper, but I couldn’t help it. When she said those things something just rose right up in me and choked me. I had to fly out at her.” “Well, you made a fine exhibition of yourself I must say. Mrs. Lynde will have a nice story to tell about you everywhere—and she’ll tell it, too. It was a dreadful thing for you to lose your temper like that, Anne.” “Just imagine how you would feel if somebody told you to your face that you were skinny and ugly,” pleaded Anne tearfully. An old remembrance suddenly rose up before Marilla. She had been a very small child when she had heard one aunt say of her to another, “What a pity she is such a dark, homely little thing.” Marilla was every day of fifty before the sting had gone out of that memory. “I don’t say that I think Mrs. Lynde was exactly right in saying what she did to you, Anne,” she admitted in a softer tone. “Rachel is too outspoken. But that is no excuse for such behavior on your part. She was a stranger and an elderly person and my visitor—all three very good reasons why you should have been respectful to her. You were rude and saucy and”—Marilla had a saving inspiration of punishment—“you must go to her and tell her you are very sorry for your bad temper and ask her to forgive you.” “I can never do that,” said Anne determinedly and darkly. “You can punish me in any way you like, Marilla. You can shut me up in a dark, damp dungeon inhabited by snakes and toads and feed me only on bread and water and I shall not complain. But I cannot ask Mrs. Lynde to forgive me.” “We’re not in the habit of shutting people up in dark damp dungeons,” said Marilla drily, “especially as they’re rather scarce in Avonlea. But apologize to Mrs. Lynde you must and shall and you’ll stay here in your room until you can tell me you’re willing to do it.” “I shall have to stay here forever then,” said Anne mournfully, “because I can’t tell Mrs. Lynde I’m sorry I said those things to her. How can I? I’m not sorry. I’m sorry I’ve vexed you; but I’m glad I told her just what I did. It was a great satisfaction. I can’t say I’m sorry when I’m not, can I? I can’t even imagine I’m sorry.” “Perhaps your imagination will be in better working order by the morning,” said Marilla, rising to depart. “You’ll have the night to think over your conduct in and come to a better frame of mind. You said you would try to be a very good girl if we kept you at Green Gables, but I must say it hasn’t seemed very much like it this evening.” Leaving this Parthian shaft to rankle in Anne’s stormy bosom, Marilla descended to the kitchen, grievously troubled in mind and vexed in soul. She was as angry with herself as with Anne, because, whenever she recalled Mrs. Rachel’s dumbfounded countenance her lips twitched with amusement and she felt a most reprehensible desire to laugh. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. L. M. Montgomery (2008). Anne of Green Gables. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/45/pg45-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html . The lead image was generated using HackerNoon's Stable Disffusion Al Image Generator feature, via the prompt "Anne of Green Fables".

Mrs. Rachel Lynde Is Properly Horrified

Many people are familiar with (Model-View-Controller) and its challenges, yet only a few discuss how to address them effectively. In this article, we will delve into the vital components of : the and the . MVC MVC View Controller Typically, a is employed as both a and a , resulting in increased code within the . So, let's explore the possibility of separating the into distinct and entities. UIViewController View Controller UIViewController UIViewController View Controller Let's begin by examining the lifecycle of a . UIViewController One of the methods in this lifecycle is . According to Apple's documentation: loadView “You should never call this method directly. The view controller calls this method when its viewproperty is requested but is currently nil. This method loads or creates a view and assigns it to the view property.” This insight allows us to segregate the and by utilizing the method. First, we will define a protocol that encapsulates the functionality of our future . View Controller loadView View protocol AbstractTestView: UIView {
    func bind(_ model: String)
} Now, let's proceed to implement the protocol for our . View final class TestView: UIView, AbstractTestView {
    
    private let content: UILabel = {
        $0.numberOfLines = 0
        $0.textColor = .red
        return $0
    }(UILabel())
    
    init() {
        super.init(frame: .zero)
        layout()
    }
    
    required init?(coder: NSCoder) {
        fatalError("init(coder:) has not been implemented")
    }
    
    func bind(_ model: String) {
        content.text = model
    }
    
    private func layout() {
        NSLayoutConstraint.activate([
            content.centerXAnchor.constraint(equalTo: centerXAnchor),
            content.centerYAnchor.constraint(equalTo: centerYAnchor)
        ])
    }
} Finally, we can implement our , which will communicate with the through the protocol. Controller View final class TestVC: UIViewController {
    private let mainView: AbstractTestView
    
    init(view: AbstractTestView) {
        mainView = view
        super.init(nibName: nil, bundle: nil)
    }
    
    required init?(coder: NSCoder) {
        fatalError("init(coder:) has not been implemented")
    }
    
    override func loadView() {
        view = mainView
    }
    
    override func viewDidLoad() {
        super.viewDidLoad()
        
        mainView.bind("Hello from MVC!")
    }
} For more intricate elements like tables, the business logic will remain within our . Here's an example: Controller extension TestVC: UITableViewDelegate, UITableViewDataSource {
    func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
        
    }
    
    func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
        
    }
} Now, let's connect our with the . Controller View let vc = TestVC(view: TestView()) It is crucial to maintain a clear separation between business logic and the view. Continuously ask yourself: "Does this piece of code handle the display of elements or work with data?" Initially, this may pose a challenge, but with time, it will become second nature.

Mastering MVC: Properly Cooking the Controller in iOS

I created a simple service for to test if the STUN/TURN servers are working properly. After installing and configuring a STUN/TURN server, most of the developers that are new to this stuff will ask themselves, how do I know if it's working properly? my WebRTC project So I made a snippet :) <!DOCTYPE html>
<html>

<head>
    <title>Test Stun/Turn Servers</title>

    <meta charset="utf-8" />
    <meta http-equiv="X-UA-Compatible" content="IE=edge" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
</head>

<body>
    <h1>Test Ice Servers</h1>

    <hr />

    <pre id='ice' style='overflow: auto'></pre>

    <hr />

    <p id='ip'></p>
    <p id='stun'>🔴 The STUN server is NOT reachable!</p>
    <p id='turn'>🔴 The TURN server is NOT reachable!</p>
    <p id='err'></p>

    <hr />

    <script>
        const Ice = document.getElementById('ice');
        const IP = document.getElementById('ip');
        const Stun = document.getElementById('stun');
        const Turn = document.getElementById('turn');
        const Err = document.getElementById('err');
        
        const iceServers = [
            // Test some STUN server
            {
                urls: 'stun:stun.l.google.com:19302',
            },
            // Test some TURN server
            {
                urls: 'turn:turnUrl',
                username: 'turnUsername',
                credential: 'turnPassword',
            },
        ];

        // Print iceServers config
        Ice.innerHTML = JSON.stringify(iceServers, null, 4);

        // Test the connections
        const pc = new RTCPeerConnection({
            iceServers
        });

        pc.onicecandidate = (e) => {
            if (!e.candidate) return;

            console.log(e.candidate.candidate);

            // If a srflx candidate was found, notify that the STUN server works!
            if (e.candidate.type == 'srflx' || e.candidate.candidate.includes('srflx')) {
                let ip = /\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b/;
                let address = e.candidate.address 
                    ? e.candidate.address 
                    : e.candidate.candidate.match(ip);
                IP.innerHTML = '🟢 Your Public IP Address is ' + address;
                Stun.innerHTML = '🟢 The STUN server is reachable!';
            }

            // If a relay candidate was found, notify that the TURN server works!
            if (e.candidate.type == 'relay' || e.candidate.candidate.includes('relay')) {
                Turn.innerHTML = '🟢 The TURN server is reachable!';
            }
        };

        // handle error
        pc.onicecandidateerror = (e) => {
            console.error(e);
            Err.innerHTML = '🔴 Error: ' + e.errorText;
        };

        pc.createDataChannel('test');
        pc.createOffer().then(offer => pc.setLocalDescription(offer));
    </script>
</body>

</html>

A Simple Script to Test Whether a STUN/TURN Server is Working Properly

Since the dawn of machine learning, imbalanced datasets have been plaguing the workdays of anyone working on classification problems. In truth, handling an imbalanced data set isn’t that complicated if you know what you’re doing. In case you do not, I’ll introduce you to the concept of classification problems, talk about real life examples, and share efficient ways to handle imbalanced data. What Are Classification Problems in Machine Learning? For those who are just now learning about… machine learning… I’ll include this short introduction to classification problems. It will help you understand the general concept of the article better. Classification problems are problems that classify data to multiple categories (class labels). If only two such categories exist, then it’s called . For multiple class labels, we use the term . supervised learning binary classification multinomial classification The most common example of binary classification is when determining whether an email is spam or not. A classifier will label emails based on the sample data it was given. Usually, it will deduce that emails containing certain phrases such as the are more likely to be spam than not. infamous “Nigerian Prince” A multinomial classification algorithm would do the same, but would have to be more complex and capable of labeling emails as promotional material, news, or any other category you come up with. When and Why Do Imbalanced Datasets Occur? Now that we know what classification problems are, let’s focus on imbalanced datasets. When a single class label has a significantly lower observation rate than other class labels in the same dataset, we that dataset as imbalanced. label Using our previous email example, if the classifier encountered only a couple of spam emails upon examining thousands then you have an imbalanced dataset on your hands. In practice, about . This means that the classifier was either examining a set of emails that have already been curated, or it’s simply not working properly. 50% of all emails sent are spam How to Handle Imbalanced Data? There are dozens of way to manage imbalanced datasets, but I’ll focus on explaining the most popular ones. These can be used to deal with 99.9% of data imbalance issues you may encounter. But what about the 0.01%? How do I deal with those? Most people will never encounter such specific examples of imbalanced data. If you do, then you’ll need years of experience to build a custom solution. A simple article, no matter how brilliantly written, wouldn’t help you at all. Undersampling & Oversampling Undersampling means you are reducing the size of the majority classes. It’s a fairly simple method of handling imbalanced data but works great when dealing with binary classification. The most effective way to undersample is to keep all examples from the rare class and choose examples from the abundant class. randomly Oversampling works the other way around. You keep all samples from the abundant class but add several new copies of the entire rare class to the dataset. Similar to undersampling, oversampling is most effective when dealing with binary classification problems. Both methods ensure you create a new dataset that’s balanced and easier to work with. Your classifier will be able to learn more and better predict future outcomes by going through more “bad” samples. Redistribute class_weight I am not a huge fan of this technique because I find it overly complicated for no good reason. However, many folks would want to put me in the data science jail if I didn’t introduce it here so let’s take a quick gander. A parameter called class_weight is present in almost every popular classifier model library. The default value of class_weight is 0, so the model automatically assigns weight to different classes that are inversely proportionate to abundance. By skewing class_weight parameters and applying the log loss function as the cost basis, you can “punish” your classifier much more severely when it misclassifies a rare sample compared to misclassifying an abundant one. Change Evaluation Criteria While the above two techniques have dealt with data presented to the classifier, this one modifies the classifier itself. First, you need to decide what needs to be changed and why. This is done by using evaluation metrics. Simply put, evaluation metrics are what’s used to modify the quality of a machine learning model. While many exist, the five I believe to be are: absolutely essential Accuracy, Precision, Recall F1 Score AUC/ROC Categorical Crossentropy Log Loss Let’s use another hypothetical example. Our model is trying to predict whether Oprah is ever going to become the God-Empress of our planet. Hopefully, the model says every time based on how you built it. NO is the prime evaluation criteria, so that’s the first thing we’ll use to evaluate our model. Accuracy A = (TN+TP)/(FP+TP+TN+FN) TP - True Positive TN - True Negative FP - False Positive FN - False Negative By applying the formula above, you get 99.5%. Your model is 99.5% accurate. Was this helpful? Not in the slightest. You still have an imbalanced data set on your hands and you know that it’s accurate. But it doesn’t help you predict anything. comes next. Precision P = (TP)/(FP+TP) It’s used to check how many of the predicted positives were true positives. Since we never predicted a positive, it’s useless. Essentially, it says our model is not good but doesn’t help us whatsoever. On to . recall R = (TP)/(TP+FN) We use recall to check how many of the true positives have proper class labels. Since we got no true positives, we can’t use it. Next up we have the it’s a personal favorite of mine. If you wondered why I bothered writing out the examples for precision and recall above, we’ll get to that shortly. The F1 score is always equal to a number between 0 and 1 and it represents the harmonic mean of precision and recall. F1 Score, F1 = 2(P*R/P+R) When the formula is applied to our Oprah problem, we get 0. F1 being a fairly advanced evaluation metric, we can say that our model is completely useless for this particular set of data and decide to handle our imbalanced dataset problem by building a different model. Real-life Examples of Imbalanced Datasets If you’re a professional data analyst and you encounter a real life example of imbalanced data, it’s usually going to be worth looking into. A great example is encountered in . If you work for a bank and are trying to predict credit card fraud, you’ll encounter imbalanced data sets. The competition between fraudsters and machine learning models has been going on for a long time and each side keeps finding new ways to “outsmart” the other. finance In , predictive models are being used to better diagnose various diseases and have been saving lives for the past few decades. As you can imagine, the most infrequent diseases create imbalanced datasets and classifiers learn from those to help doctors with diagnoses that would rarely come to mind. health Finally, we have so many examples of imbalanced data sets in that I sometimes believe some solutions were created solely to help marketers sell more services. Customer turnover, refund requests and even legal action taken against companies can all create imbalanced data sets and getting ahead of those is invaluable to top companies. marketing Final Thoughts By the time I finalized writing this article, I deleted my original conclusion (yes, I always write that part first) and decided to write a new one. I did so because I was sure that this will be a short and sweet piece that’s easy to both read and write. However, I found myself constantly digressing trying to explain different machine learning principles, thinking of new examples, and the like. I even learned a few new things while fact-checking myself when making edits. I consider myself a machine learning veteran, yet every time I write an article like this, I remind myself what originally got me excited about it. It’s a bottomless pit (in a good way) of theories, problems, and solutions - all created for the betterment of mankind.

Imbalanced Datasets & How to Properly Deal with Them

What is email authentication? Simply speaking, you confirm your identity as a sender when you authenticate your emails. Email authentication is a collection of techniques that provide verifiable information about the received email. It verifies the domain ownership of the message transfer agent which participated in the transfer of an email message. Without authentication, spoofers and spammers have a far easier possibility to impersonate you and cause harm to your reputation. Your reputation? Yes, email authentication also benefits your email reputation. You improve email deliverability by authenticating your emails. With that, you reassure the email servers of your identity and get your emails delivered to primary inboxes without an issue. If you wish to improve , we recommend reading that article for comprehensive guidance. email deliverability How does email authentication work? While the entire email authentication process occurs behind the scenes, the are set by the senders. Those authentication policies define the regulations by which an email can be authenticated. The sender configures the email server and technical infrastructure to conform to those policies. authentication policies Once an email server receives an email it conducts the email authentication process by investigating the details of the received email and comparing them to the defined rules of the domain owner. Afterwards, the email is either delivered to the primary inbox, sent to the spam section or sometimes even flagged or rejected. Without any authentication, the delivered email messages are highly likely to be considered and get rejected. That directly affects the email reputation, which grants us more insight into the question mentioned in the section above - how does email authentication affect email reputation? spam The set policies for email authentication are separated into standards, and there are three prominent email authentication standards. And once you have set all three email authentication protocols - you will be able to send emails freely and confidently. What are email authentication standards? In email authentication, there are three standards used prominently, also called email authentication protocols or methods. Those standards are These standards are supplementary to the basic email transfer protocol, SMTP, as it does not include any authentication mechanisms. SPF, DKIM, DMARC. SPF and DKIM are used most commonly and they serve different purposes. SPF validates if the email was sent from an authorized . DKIM verifies if the content was not changed by any interfering server during the transfer. IP address And even though SPF and DKIM are the most common, DMARC is the most sophisticated one. DMARC conducts both SPF and DKIM verification processes and performs an additional procedure. We shall speak of that procedure further down the article. We suggest reading this article for a more extensive guide on . For now, let us discuss some details on the available email authentication protocols, also called methods and standards. email authentication Sender Policy Framework (SPF) SPF is a simple TXT file included in the of the domain. When creating an SPF record, domain owners specify the IP addresses authorized to send emails on behalf of that domain. DNS records The server receiving an email runs a DNS verification of the return-path address. After locating the SPF record within the DNS it scans the list of authorized addresses. The result of this process is positive if the address is present within the SPF record in the DNS of the server. In an opposite situation the email triggers a soft fail alert. The email is then marked with an authentication failure. A server still accepts the email but has a reason to discard it. SPF is a widely adopted email verification method and is considered essential for any SPF increases the chances of valid email delivery. email sender SPF record example If you were to search the domain and locate the DNS records, an SPF record should look so: v=spf1 include:_spf.google.com include:mailtrap.io include:_spf.reply.io ~all Let us analyze this SPF record and learn how to build one ourselves: is the beginning and is referring to the version of the SPF. SPF1 is the most widely adopted version and is also referred to as the SPF Classic v=spf1 is for specifying the domains used to send emails from. include: concludes the record by specifying all other unauthorized domains. ~all Some records include IP addresses instead of server names, like so: v=spf1 ip0:000.00.00.0 ip6:000.00.00.00 include:_spf.google.com include:mailtrap.io include:_spf.reply.io ~all How to properly authenticate with SPF? If you are using a Mailtrap Email API/SMTP service, then you already have a prepared SPF server you can simply copy and paste in your DNS records. Otherwise, when building an SPF record there are many details to consider. SPF comes with qualifiers, and the details of those qualifiers define the purpose of the SPF record: is used to trigger a soft fail, accepting an email but marking it with SPF fail. ~ is used to reject emails. – is used to trigger a pass, allowing email messages. + is a neutral qualifier, indicating an absence of policy. ? The plus mark qualifier is also automatically assumed if there are no qualifiers indicated by the end of the DNS record. And all of the qualifiers above are simply suggestions and can be entirely ignored by the server if needed. Domain Keys Identified Mail (DKIM) DKIM is also considered an important email authentication method to possess. It is a digital signature attached to the transferred email and is validated by the receiving server upon arrival. Upon each DKIM validation, a public key is generated and added to the DNS records of the domain. The DKIM signature is encrypted with an individual and a private key. The signature itself contains details of the email, such as the email header and body. The entire DKIM signature is created upon the creation — do forgive the tautology — and delivery of the email itself. Upon arrival, the server compares the public key from the DNS records to the private key. If everything matches - the test is passed. But if the email message went under any modification the DKIM test fails and the email message is discarded. DKIM record example DKIM record does look more complicated than an SPF record: DKIM-Signature: v=1; a=rsa-sha256; d=example.net; s=newyork; c=relaxed/simple; q=dns/txt; t=1117574938; x=1118006938; h=from:to:subject:date:keywords:keywords; bh=MTIzNDU2Nzg5MDEyMzQ1Njc4OTAxMjM0NTY3ODkwMTI=; b=dzdVyOfAKCdLXdJOc9G2q8LoXSlEniSbav+yuU4zGeeruD00lszZ VoG4ZHRNiYzR As previously, let us dissect the entire record to understand it better to build ourselves: is a selector and labels the associated DNS. s= hashed email message body bh= the digital signature in a hashed format b= These are the most important three. It is also important to understand, that a domain itself can have multiple selectors. Multiple sectors serve different purposes, such as an email for newsletters, promotions, sales, etc. How to properly authenticate with DKIM? DKIM is highly advised to be configurated with SPF. DKIM focuses on a singular aspect of phishing prevention and provides no mechanics for indicating to a server how to treat failed attempts. Authenticating emails with both of these email authentication methods, DKIM and SPF, provides a far more secure email exchange and information on where the email message originated from, and where it has been modified. For proper email authentication with DKIM, it is important to update your private and public keys once or twice a year. verification Domain-based Message Authentication Reporting and Conformance (DMARC) DMARC is not considered an authentication method, as it builds upon other email authentication methods, such as SPF and DKIM. DMARC adds domain alignment, which is an additional layer of security. The domain alignment procedure verifies SPF and DKIM. This procedure can either be “relaxed” or “strict”. Choosing the correct variant is particularly important. If you select “strict”, you need to make sure to include all transactional and marketing domains to avoid rejecting important emails. To clarify, DMARC does not require SPF or DKIM, but having all three is considered a best practice to properly authenticate your emails. The trick would be to select a “relaxed” method, but use to control which emails you interact with and which you do not. With DMARC you are able to configure additional policies for failed verifications. That helps with the generation of email performance reports. email suppression lists DMARC record example DMARC record example is as follows: v=DMARC1; p=none; rua=mailto:postmaster@mailtrap.io; ruf=mailto:postmaster@mailtrap.io; fo=1; adkim=r; aspf=r The tags in the record are more extensive than we have seen in other two email authentication methods: is the version of DMARC. v is the policy of DMARC. p email addresses receiving reports about emails failing DMARC check. rua email addresses receiving individual and instantaneous reports about failed checks. ruf optional domain alignment for DKIM. adkim domain alignment for SPF. aspf How to properly authenticate with DMARC? Even though I mentioned configuring SPF and DKIM with DMARC is the best practice, you might find it surprising that it is not the most popular one. And that is the precise reason spoofing is often a problem. If you have already configured SPF and DKIM, you must add DMARC to have the strongest email authentication method for your domain. However, it is worth taking time when configuring DMARC to ensure proper authentication. If the configuration was flawed the DMARC tests fail. Conclusion And now you know the tips and tricks on how to properly authenticate your email. Many might consider email authentication a complicated procedure, yet proper guidance can help significantly. We understood how email authentication improves email deliverability. And with improved email deliverability you have better control over . It is important to take time in understanding email authentication and patiently configure it within your business. It improves your email reputation and asserts healthier business communication. soft and hard bounces

How to Properly Authenticate Your Emails

I’ve led many projects with deadlines over my career, but one stands out from how much I learned about planning. My team needed to redesign all five applications within three months. The problem was the sheer amount of work. We needed to re-architect some core UI components and update a ton of code. We only had three people on the team. This is a lot of work for a small team. We were going to miss the deadline. But we got it done. Ahead of schedule. How did we do it? We couldn’t change the amount of time, but there were two other options. We could add people or reduce the project scope. Both are costly. Adding people disrupts other teams and changing the scope may disappoint stakeholders. So how do figure out which lever to pull to hit the project deadline? We created a plan. In this post, I’ll explain what you need to do when planning for projects with deadlines. With a great plan, you’ll be able to advocate for expanding the team and cutting scope. So where do you start? Disclosure: This article includes affiliate links to any books I reference. I may receive compensation when you click on links to these products. Planning Projects with Deadlines The first step to managing a is to answer two questions: projects with deadlines Can we add people to the project to hit the deadline? If we add people, can we even meet the deadline? To get answers, we need to figure out the project’s effort. So grab a spreadsheet and write down the to-do list of the entire project. Don’t worry about user stories or project ceremonies. Just create a to-do list of you’re aware of. If a project area depends on someone else’s work, go find that person and have them write their to-do list. everything Spreadsheets work GREAT for scoping out a project with a deadline: They’re simple to write out a list of things. You can add metadata to each to-do item You can analyze and manipulate the data. Write out everything that you know at this point. It’s ok if you discover unknown scope later. This phase of a project with a deadline is about gathering data and advocating for more resources. Essential Data for your Project Plan Now it’s time to add metadata to each task in your project’s spreadsheet. I recommend the following: – Which systems or product areas will someone work in for this task? For example, the sign-up feature, data filters, a settings page, etc. This information is CRITICAL for later. Project Area – Make a of how many days it will take for ONE engineer to complet’e a task. – code reviews, QA work, deployment costs, etc. Stakeholders need an idea of when the project will ship. Effort Estimate rough estimate Include non-coding work – (Optional) Add special context for a task that others may need. For example, a hard dependency from your infrastructure team to provision a server. Notes With this metadata, you can create some data-driven summaries of the project’s work: Use the SUM() function to calculate the total number of days needed for the project. You can even calculate the effort of specific project areas. Color-code each row by the project area to get a quick understanding of where people will work. NOW we can start answering those expensive questions from earlier. Want to learn how to become the successful leader your team needs? to learn how. Sign up for my newsletter Will Adding People Help Hit Deadlines? Many software engineers have internalized the famous saying from : The Mythical Man-Month Adding manpower to a late software project makes it later. Brooks, Frederick P. The Mythical Man-Month . Addison-Wesley. While true for some projects, there are times when adding people will help a lot. The trick is finding how engineers can work on projects with deadlines. some concurrently “Working concurrently” means finding work where an engineer can work independently from teammates. These independent project areas are exactly . Engineers can start writing code and not worry about coordination costs. where you want to add headcount Remember when I told you to identify which project area a task contributes to earlier? Those project areas highlight where people can work concurrently. Say your team has two engineers and you identified four project areas. You can add two more engineers to the project and increase velocity. You now have one engineer independently working on each project area. In this situation, your new project estimate is the area with the most effort. What may have taken four months to complete may now be one. Your stakeholders would love to hear this news. Can We Cut Scope from Projects with Deadlines? So we’ve added headcount to the project, but let’s assume you STILL won’t hit the deadline. What do you do? Reduce the project’s scope. At this point, you need to meet with stakeholders and walk them through your plan. Your spreadsheet is critical here. It anchors the discussion and shows that you thought through every aspect of the project. Explain each requirement’s effort, your estimates, and how you outlined the work. You can expect two responses from your bosses. First, they’ll see they asked for too much and redefine the scope. You’ll learn what’s exactly needed for the deadline. There may be follow-up work after the date, but there’s less scope for the deadline. The second outcome will identify the wrong assumptions you made. Maybe you thought you needed to with five-9s of availability. Turns out, that’s not important. on your project plan highlights spots where extra effort isn’t needed. over-engineer a system Getting feedback Cutting this scope will be an immense help. The Last Option (Seriously…avoid this) Adding headcount and cutting scope will address most problems for projects with deadlines. But what if the team STILL won’t hit the deadline? . Is the deadline arbitrary or externally mandated? What happens if the team misses the date? Ask why the deadline exists Understanding HOW the deadline came to be may unveil other options. If there are no other options, then working late (or ) is your only choice. Asking a team to work overtime is the LAST thing you should consider. The team will lose a lot of trust if you don’t approach this topic carefully. crunching Sometimes, it’s a reasonable ask. The is one instance, but asking a team to work overtime needs to be a rare event. Asking once every few years is all you’ll get before people start quitting. Log4Shell incident Conclusion When your team has to work on a project with a deadline, the first step is to create a plan. Make a spreadsheet and outline the to-do list of every task needed to complete the project. Your job is to answer the following questions: Can we hit this deadline with the current team? Where can we add headcount to the project? What scope can be removed? But this exercise will do more than answer these questions. By outlining the project’s work, you can lead it. You have the map of what the team needs to work on. You can coordinate how everyone will work. With a plan in place, it’s up to you to ensure the team gets to the finish line. Good luck. Want to learn how to become the successful leader your team needs? to learn how. Sign up for my newsletter Also Published here

How to Properly Estimate Tasks So You Never Miss Another Deadline

Self-service business intelligence, or BI, has been on the to-do list of many organizations for quite a while. Marketed as a tool that allows users from non-technical backgrounds to get insights at the pace of business, self-service BI, however, is leaving many organizations disappointed when it comes to implementing it practically. Failure stories abound, with companies never getting what self-service BI has originally promised. That is freedom from IT for line-of-business users to create powerful and accurate reports to drive business growth. In this blog, you will find out what self-service BI exactly is, why organizations fail at it, and what steps your company should take to . implement a successful self-service BI solution What self-service BI is Self-service BI definition Self-service BI is often defined as a form of BI that uses simple-to-use BI tools to allow non-tech-savvy business users (sales, finance, marketing, or HR) to directly access data and explore it on their own. Self-service BI differs from traditional BI that is owned by the IT or BI department as a centralized function. In the traditional approach, it is these teams that are in charge of everything. They prepare the required data, store and secure it, build data models, create queries, and build visualizations for end-users after collecting their requirements. The idea of self-service BI is closely related to data democratization that is focused on letting everyone in an organization access and consume data. The ultimate purpose is to generate more insights at the organization level and drive better business decisions. Key benefits of self-service BI — Shifting control to end-users means skipping time-consuming stages of the traditional BI process. In self-service BI, end-users don’t have to wait for days or even weeks until their report finally goes live after getting through elicitation and approvals. They also don’t have to deal with the tedious change request management process when realizing that more visuals are necessary. This is because they can chop, tweak, and add data on the fly to uncover important trends, patterns, or anomalies. Faster time to insight — By empowering business users with thorough domain knowledge to perform their own data analysis on an ad-hoc basis, self-service BI produces better-quality insights while freeing the IT or BI teams from handling routine tasks related to data. Instead, these teams can focus on harder problems like setting up data pipelines to get cleansed and transformed data to the right destination at the right time and maintaining important data governance processes. Improved operational efficiency — Apart from optimizing IT and BI capabilities for time and cost savings, many self-service BI adopters take a step further. They arm subject matter experts with knowledge and tools for performing . In other words, they raise citizen data scientists who know how to generate ML-driven predictions critical to business. With data science talent coming at a hefty price tag, this kind of investment is probably one of the best a data-driven company can make. Cost reduction advanced data analytics Core features of self-service BI tools To enable the powerful benefits of self-service BI mentioned above, self-service BI tools should have the following essential features: that enable self-service BI tool integration with databases, CRM, ERP, marketing analytics, finance software, and other on-prem and cloud systems to serve analytics needs in the most efficient way. Data connectors that range from book-quality canned reports with customizable settings to ad-hoc drill-downs while allowing users to schedule distribution or divide the results into subsets for different audiences. Vast reporting capabilities that allows users to select data fields and visuals and drag and drop them into report canvas for exploration and storytelling. Intuitive drag-and-drop or click-based interface that simplify the process of creating dashboards based on user preferences and needs. Data visualization templates Many organizations take their self-service BI to the next level by enriching it with capabilities in and . Augmented analytics platforms enable users to discover more data, evaluate uncharacterized datasets, and create what-if scenarios. This way, business can react to its evolving needs as quickly as possible, achieving the utmost nimbleness. data science machine learning Why organizations fail at self-service BI 1. Unrealistic expectations An organization that just starts throwing data at novice users is facing a serious risk of poor-quality reports. It will be very lucky if these users with different qualifications wind up with non-misinterpreted data without first learning the basics of reporting. For instance, a happy user creating their first report on total sales in a historic period might end up with average numbers instead of a SUM, knowing nothing about default aggregations for various measures. Or on the contrary, they can submit inflated numbers. There is also risk of data inconsistency that might affect weighted averages when they need to be displayed with different levels of granularity. Further on, a non-power user might rest satisfied with just a casual analysis that has supported their initial beliefs. The confirmation or cherry-picking bias trap is not something an untrained user is necessarily aware of, especially when under pressure to explain a certain pattern. 2. Reporting chaos Self-service BI doesn’t mean zero IT involvement. Letting users toy around with data with no governance from IT usually leads to reporting anarchy. With no governance, there could be redundant reports from different users working in silos and delivering the same analysis or reports from different users analyzing the same metrics but using different filters and hence delivering conflicting results. Reports from different departments can rely on different naming conventions for quantity, value, or time or use the same terms but not necessarily the same definition. Multiple versions of the same database, errors in databases that are never fixed, the creation of objects used only once … The list is endless. Governance is not something that a data-driven organization can boycott in the world of self-service. No matter how badly a company wants to free users for conducting their own analysis, IT still needs to be involved to maintain high data quality and consistency. 3. Lack of adoption Truth is, not everyone likes to work hard. Most business users just want a simple dashboard that will give them the numbers. Valuable insights, however, often lie levels deeper that go beyond plain business performance analysis. Another psychological factor that may hold back an efficient self-service BI is resistance to change. It is not uncommon for many organizations in the early stages of their self-service BI journey to see frustrated business users coming back to BI or IT to request a report as they did in the good old times. Older approaches are safer. Unfriendly self-service BI environment setups also might be a problem. What may seem for IT or BI teams to be an easy-to-use tool for collecting and refining results can have an overwhelming and demotivating amount of features for a casual user without technical skills. Pivotal tables and spreadsheets might be dull, but users when getting stuck. are quick to revert to them 10 tips from ITRex on how to implement self-service BI successfully Below is a list of essential takeaways from ITRex experience in building efficient self-service BI tools for both smaller business and large companies, including for the world’s leading retailer with 3 million business users (read more about‌ this project ): here . You first need to define what you want to achieve with self-service BI, be it as simple as reducing delayed reports or providing data access organization-wide. Self-service can mean anything to different people, so you should be clear about your project. It’s also important to understand early the scale of implementation, the types of users, their technical proficiency, and your expectations of deliverables. Set your self-service BI strategy . You should wrap your head around what your stakeholders look for in data and what their data-related success metrics are. Interview them to collect their functionality, usability, user experience, and other inputs. Then continuously ask them for feedback as you iterate. Apart from making sure you build a relevant self-service BI tool, you will also give your stakeholders a sense of ownership and improve their engagement. Keep all stakeholders on board throughout the project . This is also essential. Your IT has all the information on your data environment, existing data sources, data governance controls in place, and data access management. They will help you choose or build a self-service BI solution that is easy to maintain, monitor, and manage in terms of user access and integration of new data sources. Involve the IT department . Self-service BI governance encompasses the following: Set up robust governance Data governance policies and procedures to ensure your data is consistent, complete, integral, accurate, and up-to-date. Here you will need to and adopt leading practices in master and metadata management as part of it develop a broader data management strategy Governance of business metrics to define them uniformly across your self-service BI environment and rule out any deviations Governance of reports to set a procedure for their quality validation Data security to define who gets access to what data in your self-service BI and establish data lineage . There’s no one-size-fits-all strategy. Your users have different needs and skills your tool should precisely cater for. You will probably need to balance between flexibility and sophistication to allow your users to ask new questions while staying self-reliant. A custom self-service BI solution will make it easier to achieve. Select the right tool . A single source of truth is implemented as part of solution architecture to enable decision-making based on the same data. For this, companies build a or another kind of central repository that provides a 360-degree view of all their data from multiple sources and makes data access, analysis, enrichment, and protection much simpler and more efficient. It’s worth the investment. Establish a single source of truth data warehouse . Three types of training programs for end-users are a must: 1. data analysis and visualization, 2) the basics of joining data and building data models, and 3) continuous peer-to-peer training. Educate users . It will help a lot if you either establish a center of excellence or have an expert community on Slack or Teams so that your end-users know where to go to fill in gaps in knowledge. Build a community . They will help drive engagement by increasing access to data for users with no analytical background and providing oversight as needed for better-quality reporting. Consider embedding BI specialists in business units . Choose a limited environment for starting your self-service BI project and build from there using an agile approach. This way, you will fix problems early before scaling up. Start small Watch this two-minute video of a project from the ITRex portfolio to learn how self-service BI augmented with AI can drive efficiency gains for a large enterprise if done right. https://youtu.be/KVARUwIRFZE if you consider embarking on a self-service BI journey. With their battle-tested approach, we will help you avoid common pitfalls while bringing your project to success. Drop ITRex team a line

Self-Service Business Intelligence and How to Do It Properly

The (GDPR) was big news for companies when it came into effect in 2018. It aimed to put more controls on how organizations manage the personal data of their EU-based users. Since the law’s enactment in 2018, some US states, such as California and Virginia, followed suit and passed their own data privacy laws for their respective residents. Companies that do business in those regions now have to ensure they comply with these legal requirements. General Data Protection Regulation This post is the third in a series about what developers need to keep in mind when sorting out security and compliance for their application. The first article in this series covered how to build , the second was about for SaaS apps, and this one is all about GDPR and customer communications. GDPR and similar regulations cover all communications from a company to its customers and prospects, including marketing and transactional notifications. If you are considering sending notifications to the users of your SaaS application, whether via email, push, or a Slack bot, you need to keep GDPR in mind when building your service. security for user communications compliance certifications and regulations In this article, we cover the implications of GDPR for your customer communications in more detail. GDPR covers broad swaths of user data The GDPR serves to protect the personal data and privacy of individuals. While it applies to the European Union, global companies still have to comply with the regulations if any of their customers are EU citizens or residents. The law applies to the handling of data, including its storage, transmission, and analysis. So, if your SaaS company collects any user information, for example, email addresses or phone numbers, and some or all of your users are based in the EU, you must comply with the GDPR or face significant fines. The GDPR applies to “identifiable information,” which is defined as a person’s name, identification number, location data, online identifier, or information regarding their physical, physiological, genetic, mental, economic, cultural, or social identity. As you can see, many types of data can fall under the regulation’s scope. For example, even if your organization is just tracking the IP addresses of visitors to your website, you have to comply with GDPR standards. The cost of noncompliance with GDPR The GDPR obliges organizations around the world to seriously question what forms of data collection are absolutely necessary. Companies need to ask themselves which data to collect, how to process it, and how exactly they will use it. The penalties for noncompliance are steep, as Facebook and Google have . The fines can reach 4% of a company’s . These fines are as high as they are so that organizations don’t just accept them as the cost of doing business in the EU. The goal is to change how companies manage data and bring the power of data privacy to the general public. already found out global revenue While the tech giants have been the primary target of the EU compliance bodies so far, all SaaS companies could be checked for compliance with GDPR in the future. Because most SaaS products send customer communications that include personal and identifiable information, it’s critical to be in compliance to avoid potentially massive fines. What’s the best way to avoid GDPR noncompliance when sending user notifications? Know what compliance with GDPR involves, and get ahead of any issues. We offer specific suggestions below. What does GDPR compliance look like for customer communications? Your approach to customer communications should be based on of the GDPR, which outlines the rights of “data subjects” (the individuals whose data you’re collecting). According to that chapter, your strategy should include a clear privacy policy, granularity of consent, data storage compliance, and audit logs. chapter 3 (Art. 15–23) Covering customer communications in your privacy policy An easy-to-understand privacy policy is one of the tenets of the GDPR. The policy should be written in clear language, freely accessible to the public, and absolutely transparent regarding all handling of data. The GDPR even stipulates that this privacy policy should be readable by children. The privacy policy also needs to cover your customer communications, including marketing and transactional emails, push notifications, and other types of notifications, as they form an integral part of your SaaS application. Make sure you are transparent about customer notifications in the policy. This includes listing third-party services you might be using for notifications, retention periods for notification data, and ways to access the notification preferences. While not directly related to the privacy policy itself, it is a good practice to spell out how exactly your customers will get notified of changes to your privacy policy. (This is getting quite meta — we know!) Check out for an example of a privacy policy for a SaaS service. Courier’s privacy policy Granular consent To comply with the GDPR, companies need to ask their users for granular consent. For example, websites have to notify users that their data will be collected and provide a link to the privacy policy. Customers must be able to reject data collection strategies like cookies on a case-by-case basis. The granular consent requirement also applies to customer communications, specifically the channels of notification. In our series on , we wrote about why you should let users choose which notification channels they want to use and when in order to avoid mass opt-outs from all notifications. notification preferences To keep more users subscribed (and meet your GDPR obligations), let them choose which channels or, even better, which specific notification types to opt-out of. Data storage and retention When it comes to data storage, the GDPR stresses the importance of cybersecurity best practices. If your SaaS company stores data on physical servers, then you need to control physical access. And if you take the more modern approach of storing data in the cloud, the storage services themselves need to be compliant with EU-based policies. Additionally, you need to include password control, firewalls, and data encryption in your organization’s risk management process. Therefore, you should store the data you use for customer communications, including names, email addresses, and phone numbers, following the best practices while also allowing customers unobstructed access to their data if they request it. Access to the data does not have to be automated through an API endpoint or a menu in the user interface — it can also be a script that your support team runs manually, for example, or a Slack bot command. However, if the volume of customer requests for data increases over time, you should consider automating the handling of data access requests. Customers can also request that their data be deleted (also known as “the right to be forgotten”). If you receive such a request, remember to clean up the customer’s data from all downstream providers and services that you might be using for customer communications, from email providers to push notification endpoints. Audit logs The GDPR requires that companies keep an audit trail of everything that happens to their customers’ data — that is, records of when and by whom the data was accessed and for what reason. The logs will prove invaluable if you’re trying to show compliance or improve your chances of clearing an investigation if an incident occurs. Consider including actions around customer communications in your audit logs. For example, the sending of a notification to a particular channel should be logged as an auditable event, ideally along with the reason why the notification was triggered. We also recommend logging any changes to customer preferences, whether your application changed or the user made the change themselves. Conclusion The whole point of the GDPR was to force organizations to think about how they manage user data. Gone are the days when companies could do whatever they wanted with the data they collected. With US states following in the GDPR’s footprints and voluntary compliance standards such as ISO 27001 becoming more prevalent for competitive SaaS companies, handling customer data with care is no longer a choice. At Courier, we believe that we need to maintain the utmost compliance standards and transparency for customer communications, not just for the sake of our product but also for all of our users. Not only do we comply with legal standards like the GDPR and the (CCPA), but we also push further, like when we recently became . To stay in compliance and deliver a great notification experience to your customers, about how we approach it. California Consumer Privacy Act SOC2 Type 2 compliant learn more

How to Properly Implement GDPR for Customer Communications

Photo Credit: Ellen Stevens/Hacker Noon. Double exposure of an apple and a calculus book. I.   Love.  Work. I love working during the day and I love working late into the night. If I could train my body to function properly without sleep, I would work 24/7. During university, I was employed at multiple jobs in order to sustain my life. The loan that I had taken out for school simply didn’t cover all of my daily needs. I had moved—by myself— to a new city, where I didn’t know anyone, and tried to embrace the adventures of both academia and independence as much as I possibly could. I got really good at a lot of things in those days, but the one thing that I was particularly skilled at was avoiding cooking. It got to the point where one of my staff members would bring  home-cooked meals for me to the office because he “thought I might die.” At the time I thought this was pretty amusing and I was obviously flattered that literally anyone cared or noticed. My schedule was frequently so crazy and hectic that I didn’t give my body much thought. I should probably also note that I’ve always hated cooking, HATED it.  Which is why my newly developed  ' is slightly comical and terribly ironic. expertise in nutrition' I wasn’t raised with cooking being a big part of my life, nor was I raised to be a foodie. I was raised with a general appreciation for healthy food choice practices, and an understanding that fruits, veggies, and various grains and meats were better than fast food. That much I knew. But the intricacies and scientific whys of the matter were never covered in any thorough detail. Nor was I ever given a thorough education in nutrition from anywhere else. I figured: 'E h I’ll wing it for now.' Photo Credit: Ellen Stevens/Hacker Noon After years of a steady diet on the same basic few foods —to note, they actually were horrendous choices—energy drinks and stress, my body’s sluggish performance was starting to get in the way of the intensity of my goals. not This was unacceptable. How was I supposed to continue to pursue my passions with the drive that I encompass, if I felt consistently subpar? This is when I began my research into nutrition science. The below assortment of links and suggestions is an outline and summary for potential topics — in what may unfold to become a series here on . With that being said (or written), Hacker Noon a summary such as this something I would have died to come across when I was first starting out. There is so much questionable nutrition content out there— too much of it is scattered, with very little depth, promoting a specific diet agenda, and a lack of a full picture presented —that I wanted to create something that would give readers the fullest picture of nutrition— at least that I could summon. Furthermore, part of the Thus, presenting a pretty thorough map of the points from which to start. value of this article is it addresses the importance of treating the potential underlying deficiencies your body may have. There is an overwhelming amount of natural or pharmaceutical solutions to treat all sorts of Some of them work great! However, when it comes to deficiencies, treating the deficiency is likely more efficient than the symptoms you get from it. symptoms. If you treat the root of the problem, things like sleep, digestion, energy, are likely to fall into place. Being deficient in any one mineral or other nutrient can cause a plethora of physical and mental ailments. Please also read ALL of the disclaimers found at the bottom of this article. It is very important for you to be aware of how to approach any ‘medical advice’ you find on the internet. Notably, it's also important to understand that contrary to many popular beliefs, it is frequently ‘ to experience one or more of the following symptoms: It's entirely possible it has to do with a deficiency or food choices. NOT a normal part of adulthood’ Being constantly tired (especially after meals), not being able to sleep properly, being bloated, and experiencing constant brain fog . in this series will show a framework and summary of what you might consider when reprogramming your approach to nutrition and supplements. will take you through some of the brilliant nutrition science research currently available. The first piece The future content It's probably most important to note that all of this research wasn't a waste of time, I feel incredible. Being on a Diet Does not Automatically Equate to Being Healthy Just because are an ‘ideal weight’ or not an ‘ideal weight,’ super fit, or not super fit, or live in the West, absolutely does NOT mean that you are automatically meeting your body’s requirement for nutrients. How you feel overall is a pretty important indicator on whether or not to go in for testing (although it is my personal opinion that everyone should go in for testing just in case). Simply eating fortified foods, or even a ‘balanced diet’ doesn’t guarantee a 100% ‘nutrition success rate.’ It also doesn’t mean that you are not meeting them. Please Consider Some of the Following Resources and Suggestions: (The below organizations and people are in no way affiliated with me at the time of publishing this article. They are simply sources I found throughout my own research that I have personally found to be excellent.) 1. Harvard Medical School @HarvardHealth This incredible chart compiles an outline of the daily nutrients that your body needs. They list the required amounts per vitamin, the upper limit, the foods that you can find it from, as well as what happens when you have deficiencies. Harvard Health Publishing in partnership with the Harvard Medical School provides a thorough Listing of Vitamins in a chart. The below image is just a small portion of it, the chart is much larger. 2. Eat This Much @EatThisMuch is a small company “focused on providing tools and support for people who want to take control over their nutrition.” They have a that allows users to type in pretty much any food, and have a relatively accurate measurement of the amount of nutrients in it. Eat This Much tool on their website You can map your diet into the above chart and see what you are likely not getting. If you find that you are ‘scoring’ lower in a particular nutrient, do a separate search for the particular food and nutrient information to double-check.  While the above site does a pretty remarkable job, it sometimes doesn’t capture every single nutrient. 3.  Joanna Soh @Joanna_Soh is fantastic in aggregate, but her video called “ ” is one of the best videos about digestion I have ever seen. You may have to skip the first few minutes of the video while she discusses a related function, however, the rest of this video is .  According to the video the categories of food to eat are: Joanna Soh Official’s YouTube Channel 5 Must Eat FOOD for a Flat Tummy (Healthy Digestion) information gold 1) Food containing high PROBIOTICS 2) Food high in FIBRE 3) Food high in WATER 4) Food containing high PREBIOTICS 5) Certain HERBS & SPICES. 4. Thomas DeLauer @ThomasDeLauer has fantastic nutrition-oriented content. He will actually go to different stores and break down an available product’s ingredients, how they impact your system, and how they are produced. He’s a bit keto-obsessed but has very good links to legitimate research. He has videos on fasting, various supplements and ingredients, various #biohacking tips, and more!  He’s an unbelievable source of excellent nutrition information. Go Thomas! Thomas DeLauer’s Youtube Channel Burnout Video Protein Bar Ingredients Supplements Worth Considering (For when there are nutritional gaps not being met by food.) Multivitamin Good for overall functioning and energy. Take one in the morning or during lunch with food. Find a quality one, better if it’s a capsule. Brand suggestion: (Pay close attention to the ingredients in their various supplements, try and match the one you buy to that or order from them.) https://platinumnaturals.com/ Omega 3 Fish Oil Good for cognitive function, cardiovascular system, etc. Take with dinner and lunch, or as described on your particular bottle. Make sure it is a quality pill with EPA/AEP 660 mg and DHA/ADH 330 mg. Brand suggestion: https://newrootsherbal.com/product/id/1253 Vitamin D Good for brain health, skin, immune support, mood, etc. Take with dinner. This is especially beneficial in the winter when many people are not exposed to direct sunlight. A capsule is generally better than a hard pill. Calcium Good for bones. Many people get enough calcium through their diet. However, if you don’t eat dairy this may be something to look into. More is needed as you age. Take with dinner. If you take calcium, you should also take Vitamin D and Vitamin K t o help it absorb. ZMX (Zinc, Magnesium, and B6) Good for people who exercise, sleep, etc. Take at night time. Good Probiotic Good for digestion. Ask for advice from whatever health store you go to on this one. Collagen and Biotin Good for your skin, especially as you get older. Other Tidbits to Consider 1. Stop equating healthy eating with bad-tasting food. You can make delicious meals and snacks from ingredients that won’t inflame your system and give you a plethora of disorders. 2. Processed sugar has little to no nutritional value. Try and limit its consumption. There are plenty of natural sources of sugar that are delicious and have nutritional value.  [ ] Source 3. Exercise is important, but you have to make sure you’re doing it in the right way. This means eating the right diet and taking the appropriate breaks to make sure you are not doing more harm than good to your body. This usually means consuming more protein and supplementing your electrolytes. 4. Don’t buy into fad diets. Consider a holistic approach. My personal preference is to follow both a Mediterranean and paleo-style diet. Please note that there is a whole plethora of factors to consider when you make a decision for what you include in your diet or you don’t. 5. Keep in mind that if you cut out certain types of foods, you may need to supplement with a particular nutrient. For example: Not eating dairy means that you may have to consider a calcium supplement. 6. If your body tends to react badly to a particular food, it may be time to reconsider how much you are eating of it. Sometimes you may not even know that your food consumption preference is what is making you feel bad, so be aware that this is a possibility. 7. Consider soups, various meats, seaweed, as substitutes for sugary snacks. 8. Consider tea as a substitute for coffee. Many teas have caffeine and more nutritional value. 9. Consider starting the day with protein and switching to tea. The ‘crashes’ you may be feeling during the day may be due to carb intake and coffee. 10. Get enough sleep. Granted, it’s easier said than done, but actively making an effort to maintain proper sleep hygiene is essential. 11. Green tea, apple cider vinegar, and various spices like cinnamon, cayenne pepper, and turmeric are staples which should be found in every kitchen. 12. It’s ok to “cheat” just make sure you’re making better choices more often than not. 13. If you look at this content and think you have to make a dramatic change, . Instead of buying multiple sugary snacks, consider getting frozen or unfrozen berries instead. Make the changes sustainable. Otherwise, you are more likely to go to bad habits. start slowly 14. The healthy lifestyle has to be sustainable for you. Find a way to make that happen. 15. You don’t have to run after every new health fad, wait until there is more research available. 16. Look and research the ingredients in your food. It’s time-consuming and frustrating, but eventually, you will learn to recognize what to avoid. You will probably be shocked at not only what is in some popular foods but also how much better you feel when you are more selective of what goes into your system. 17. Fasting has been a practice in many cultural and religious circles. There is an abundance of research available now for its benefits. Learn how to do it properly. 18. Consider taking one of the . following nutrition courses 19.Many people are opting out of eating wheat, dairy, and processed foods. In future articles, I will cover the reasons for why that is. We are bombarded with a plethora of disastrous information that placates terrible health choices and decisions. All the while having to grow up with a serious lack of and nutrition science information from formal education. This is genuinely backwards from how modern societies should be. unbiased quality What you put into your system can dramatically alter the outcome of your life.  Food and body interactions are complicated. Nutrition science is complicated. The way different substances interact with your particular body is very sophisticated. Food and body interactions are literally biochemistry. It’s so crucial and fundamental that we somehow manage to take food choice practices completely for granted, and then wonder why we need a cocktail of pharmaceuticals and energy drinks to keep us going past thirty. Important Disclaimers This article is written largely for those who have normal, standard screening test results but continue to feel sluggish etc. for some unknown reason. That being said, considering we're all human (as far as I know), no matter what the case, treating deficiencies will probably be better than not, in most cases.  Though again, I'm sure not in every case given that bodies and conditions are complex. Both supplements and various types of food can interact with your body in very specific and fundamental ways and thus have an impact on the current medications you may be taking. Consuming too much of a particular vitamin can be toxic and sometimes lethal. Always speak with your doctor before trying anything you see in this article or the ones to come after it. Especially if you are taking a plethora of medicine or supplements already. While I can acknowledge that a lack of regulation for things like vitamins can lead to inconsistent quality, I can also appreciate that there are companies out there that actually care about producing quality supplements because they are run by people whose lives have been saved— or dramatically improved— by these things. It’s up to you to make sure you are taking supplements from a trusted brand in your country. While I have a degree in Psychology, I am neither a doctor nor a nutrition scientist. I’m just a person who needed to take a ‘deep dive’ into this subject for my own wellbeing. It has worked and so I have been encouraged to share my findings on numerous occasions. Consider seeing a nutrition specialist or homeopathic doctor for a blood test to test for all of the possible deficiencies you may have. Also, consider getting testing for various food sensitivity you may have. Standard medical tests frequently do not capture everything there is to look for. This is not an article arguing in support of ALL homeopathic medicine. Nor is it an article arguing against modern medicine. It’s simply acknowledging that there is frequently a lack of education for medical health professionals in preventative measures. Seeing a nutrition specialist might be easier than following some of the above suggestions, and trying to ‘wing it’. That being said, if you’re as much of a nerd as I am, you might as well read through the above suggestions. This article isn’t about body shaming, or telling you things you don’t want to hear. It’s about your health and how you feel overall. While it should probably be a cultural responsibility to promote better food choice practices—and admittedly certain situations obviously make proper eating habits difficult— your wellbeing is your responsibility. The pieces I plan to write are about sharing some knowledge I personally have found remarkably helpful, not dictating to you how you should live your life. Follow Ellen on Twitter @ escvdotca

How to Biohack Properly

Testing your business idea is a basic skin a bones method to gaining an insight into the potential success of your venture. Recognising the challenges your business may throw at you and not being blinded by your emotions is an important step that some small business owners have a tendency to miss out on. Self Motivation When you decide to and become a self-employed entrepreneur, you will have autonomy over your working life. This includes your schedules, your work-life balance, creating your own working culture, but the goal is to turn around a profit. If you are someone who has the tendency to start something and be really enthusiastic about it and then reach a plateau and give up, you may need to do some evaluation on your business idea because longevity and consistency is the name of the game. start your own business The challenges that come paired with running your own business are synonymous with you having the self-motivation to get stuff done. You will have no boss or ultimatums, the work you put in will directly affect the results and you only have yourself to answer to. Any unpaid invoices, it’s on you to chase them, want to reach a new target audience, it’s up to you to action a strategy. There’s no shame in not wanting to take on that responsibility, but you have to be transparent with yourself about if your is something you will truly be committed to. business idea Unique Selling Point There are a range of gaps in a range of different markets and the accessibility of the world means that many business ideas are already being executed. However this does not mean that there isn’t room for your business idea on the market, but you do need to establish what makes your business desirable and . For example, if you are a video editor and want to become self-employed, what types of video editing do you specialise in, is there software that is a niche to your industry that you are an expert in? Really take the opportunity before you launch to pick at your business and really hone in on what you have to offer and do plenty of research on your industry and competition. stand out from your competition Communication is King Do you know your business idea enough to communicate it in the most basic terms to someone who has no idea what it is you are actioning? If the answer is no, then you need to go back to the drawing board. Communicating your business idea is key when it comes to outlining your business to potential customers or clients. This could also mean getting your . If you are going to be taking your business idea to a panel of potential investors, will your vision be clear to them? You have to be acutely aware that not everyone will know what is going on inside your head, you have to be reliant on the way you are able to communicate your business idea and make sure that it is clear. You can practise outlining your business brief to someone outside of your sector, try it with people who would have a neutral opinion or someone who you know will be honest with you and give you . pitch ironed out constructive feedback If you feel that when it comes to describing your business you get a bit hazy or that your explanation is long-winded, then try to write down the main attributes of your business and what the goal of the business is. Start with the basics, is it a product or service? Who will it help and what is your expertise? Once you have the basic bones of your business pitch you can then flesh it out for your personal business. Your Target Audience and Market Do you know who your ? Can you outline the demographic and interests of the people you want interested in your business? If the answer is no, then this is vital to the success of your business idea. If you want to launch a mobile app, for example, can you outline what your users will turn to the app for and does it meet your target audience’s needs? Asking yourself the hard-hitting questions when it comes to your target audience is vital as it will dictate how you present and market your idea. target audience is Putting your business idea through a thorough stress test will only ensure that you identify any potential issues you may face, but will give you the opportunity to outline any elements of your business that you may not have thought of previously. Consider a business stress test as a preliminary step for your launch, and it’s important to action it.

How To Properly Stress-Test Your Business Idea Prior To Launching

There’s an underestimated tool on your website that holds the key to business growth. If you use it well. What am I talking about? I'm referring to the simple form tool that we use to create contact forms and other means of getting inputs from users. Forms are the basis of many interactions online. We carry out searches by entering in a form field and then hitting ‘Search’, we send messages via forms, we enter shipping and billing details with forms, and do so much more. keywords It makes sense that improving how you build forms will also (UX). And as a result, you’ll build leads, get more customers, and engage with people better. improve user experience Now let’s take a look at practical ways you can leverage forms and improve UX on your website. Here we go. Create conversational forms Are you experiencing form abandonment? A large number of people who start filling your forms actually leave without hitting submit. This happens when your form is confusing, unintuitive, or too long. When you do need to collect a lot of data for things like surveys, it’s necessary to create multiple fields. In such cases, you need to find a way to make it engaging and interesting even though there are several fields that need to be filled. This is where conversational forms come in. A conversational form is where questions appear as if they’re being typed in real-time. And only one question is asked at a time. So when people respond to the form question, it’s like sending a chat message. Conversational forms remove the feeling that a user is filling a static form and is having a dynamic and more interesting experience instead. If you’re seeing low form conversions or just want to optimize your surveys to get the most feedback, make use of conversational forms. Add multi-page forms and breadcrumbs Another way to get people to fill long forms is by creating your form in a multi-page layout. Here, your form is spread across different pages that people get to once they’ve finished the current form page. By breaking down your form into bite-sized pieces, it removes mental fatigue as users enter data. You’ve probably already used multi-paged forms while making payments or applying for jobs. Breaking up your form in this way also removes the need for people to scroll down too far and ensures that the input they’ve already given is saved. Here’s another feature you can add that makes your multi-page form user-friendly: breadcrumbs. Breadcrumbs are visual cues that tell people where they are on your form or website. It lets them know how far along they are on your form and how much more is left to complete. This creates mental ease and gives the sense of making progress as a user completes the form. Use conditional logic Conditional logic is a form feature where you display certain questions based on the choices a user makes. For example, if you’re using forms to get job applications, then depending on the role a person selects, they’ll get questions related to that role. A person who is would then be shown a dropdown list consisting of qualifications or skills that they can pick. applying for the role of a developer Using conditional logic means that you only ask the right questions and get relevant answers. And your users won’t have to answer generic questions that waste their time. Another way that you can use conditional logic is by creating custom messages for different form responses. If a customer makes an inquiry, your success message can thank them and ask them to wait for 24 hours for a response. Or, if a customer wants to get information for an event, you can automatically assign such queries to people or departments in your business that deal with events. It’s also possible to redirect customers to different pages once they complete and submit their form. If they’ve signed up for an event, you can take them to a page with a countdown timer that’s ticking down until the event takes place. Or if they subscribed to your newsletter, you can send them to your blog page to start reading. There are many ways to leverage conditional logic. Look for ways to personalize interactions on your website using forms and you’re certain to see higher conversion rates soon. Auto-fill content The less work your audience has to perform on your website, the happier they’ll be. Auto-filling some form fields based on your page links or user behavior will make less work for your audience. For example, if your user is on your product pricing page and wants to send a message asking for more information, a form that popups from that page could automatically fill the subject field with appropriate text like ‘I’d like to know more about this product’. Users could add to it, send it as is, or replace the text. You can also enable a dynamic field population, where users who’ve entered information about themselves once before will find future forms automatically filled. Make custom form landing pages One of the issues faced with using forms on WordPress is that the theme controls what a form looks like. And because of this issue, you’re very limited when it comes to designing your form. One way to overcome this is by creating a dedicated form landing page. You build a single landing page with almost no other content except your form. You’ll have control over how it appears by managing spacing, sizes, colors, and more. Building a landing page for your forms gives you more control over your form's appearance. This helps your audience to focus on the form and prevents users from feeling overwhelmed or distracted by other content. Over to you Forms are simple but powerful tools and often underestimated by businesses. It is critical that you use a to create the best chance of making a positive user experience for users. good form plugin Along with sending messages, forms are important tools that help you gather leads, get payments, and even . get blog post submissions Invest in the right tool and make sure that you create ease for customers who want to interact with your business. In this way, you’ll grow your business fast.

Improving User Experience And Growing Leads By Building Forms Properly

Your content collections store your site's content. The collections organize your content with items (rows) and fields (columns). The fields usually describe the items. For example, if one item is a car, a field may list its color. The image below shows a collection of 4 fields and 5 items. Regular Fields Each field in a collection has a , (Velo by Wix only), and . Field Name Field Key Field Type Field Name The is the label you see at the top of the column in the Content Manager. The is also used in the connect panel for elements you can connect to a dataset connector in the Editor. Field Name Field Name For example, when connecting a text element to a field from your collection, you use the in the Connect Text panel. Field Name When you add a new field in the Content Manager, you specify the . You can change the after the field has been created, and all connections to that field will be updated. Field Name Field Name (Velo by Wix users only) Field Key The is used when referring to the field in code using the or . Field Key Data API Dataset API For example, if you want to insert an item using the Data API, you use the . Field Key wixData.insert( , { : }); "CollectionName" "fieldKey" "value" When you add a new field in the Content Manager, the is created automatically based on the . You can specify your own field key, if you wish. Field Key Field Name Note: You cannot change the once the field has been created. Field Key Field Type The defines what kind of content the field contains. When you add a new  field in the Content Manager, you choose one of the following . You can read about field type support and limitations . Field Type Field Types here Reference Text Image Boolean Number Date and Time Address Rich Text URL File Video Media Gallery Time Tags The field type is used when connecting page elements to fields in your collections. You can only connect certain to fields of relevant . For example, you can connect a text element to a Text or URL field but not to an Image field. input elements Field Types While the Content Manager doesn't allow you to add new values of the wrong field type, content imported from a CSV file or added via code is not validated. For example, you could import a text value to a number field. In this case, the Content Manager will show an error. You use the Reference field type to select items from the Main field of the referenced collection. For more information, see . Adding a Reference Field to a Database Collection Note: You can . Make sure to consider the effect this can have on your site before you do so. change a field's type Main Fields Every content collection has a Main field which are used by reference fields to create connections between collections. A collection's Main field is indicated by a lock icon next to its field name. By default, the field is the Main field. You can define any text field in your collection to be the Main field except for the ID system field. Title When you fill in information in a Reference field, you select from the values in the Main field of the referenced collection. If you change the Main field in the referenced collection, the values displayed in the reference field change to match the ones in the new Main field. It is good practice to ensure that each item has a unique value in the Main field. For more information, see . About Reference Fields System Fields Every content collection contains the default fields shown here. They cannot be edited and are hidden by default. https://support.wix.com/en/article/about-collection-permissions Calculated Fields When you create a , a new field is added to the collection that the dynamic page pulls content from. This field contains a calculated URL with the dynamic page's prefix and the values of the fields that determine which content will be bound to the page. dynamic page For example, you might have a dynamic item page to show items from a collection based on their field. In your collection there will be a field called with URLs such as and . Dishes Title Dishes (Title) /Dishes/pizza /Dishes/chicken When a visitor goes to a dynamic page, all the items in the collection with a URL that matches the URL of the page will be bound to the page's dataset. For dynamic item pages, each item will have a unique URL. For dynamic category pages, multiple items will share a URL. You cannot edit the contents of calculated fields. However, if you change the URL of your dynamic page, the URL in your collection will change accordingly. If you create multiple dynamic pages based on a collection, the collection will have one calculated field for each dynamic page. For more information, see . About Calculated Fields Before you create a collection you may want to read about . Planning Your Database Model You can also learn more . Accessing Your Sandbox and Live Content Collections Previously published at https://support.wix.com/en/article/about-your-content-collection-fields

Wix Content Collection Fields: Helpful Tips on How to Use Them Properly

We're used to thinking that you cannot deliver fast and maintain a healthy codebase. But does it really has to be a trade-off? One of my greatest privileges building Stepsize has been hearing from hundreds of the best engineering teams in the world about how they ship software at pace while maintaining a healthy codebase. That's right, these teams go We're so used to the quality vs. cost trade-off that this statement sounds like a lie—you can't both be fast and maintain a healthy codebase. faster because they manage technical debt properly. Martin Fowler does a great job at debunking this idea in his piece ' '. Spoiler: Is high quality software worth the cost? High quality software is actually cheaper to produce. The lessons I'll relay in this article are drawn from the combined centuries of experience of the these 300+ software engineers I've interviewed. Why bother? As Adam Tornhill and I recently discussed in our webinar, software has well and truly eaten the world. And look, if you're here, this will probably sound like a cliché to you. In this case, it's because it's true. Look around you, can you name one object that didn't need some form of software intervention to be manufactured, purchased, or delivered to you? Software companies live and die by the quality of their software, and the speed at which they deliver it. Stripe found that 'engineers spend 33% of their time dealing with technical debt'. Gartner found that companies who manage technical debt ship 50% than those who don't. These data points may seem a little dry, but we intuitively know they're true. How many times have we estimated a feature will be delivered in a sprint, only for it to take two? Now take a moment to extrapolate and think about the impact this will have on your company over a year, two, or its entire lifespan. Is it not clear that companies who manage technical debt properly simply win? A simple framework to achieve these results Google around for 'types of technical debt', and you'll find hordes of articles by authors geeking out about code debt, design debt, architecture debt, process debt, infrastructure debt—this debt that debt. These articles are helpful in that they can train you to recognise technical debt when you come across it, but they won't help you decide how to deal with each piece of debt, let alone how to manage tech debt as a company. The only thing that matters is whether you're dealing with a small, medium, or large piece of debt. The process for small pieces of debt This is the type of tech debt that can be handled as soon as the engineer spots it in the code—a quick refactoring or variable rename. Engineers don't need anyone's approval to do this, or to create a ticket for it to be prioritised. It is simply part of their jobs to apply coined by Uncle Bob: the boyscout rule Always leave the code better than you found it. This is table stakes at every software company who have their tech debt under control that I've interviewed. It's mostly driven by Engineering culture, gets enforced in PRs or with linters, and it is understood that it is every individual contributor's responsibility to handle small pieces of debt when they come across them. The process for medium-sized debt The top performers I've interviewed stress the importance of addressing technical debt continuously as opposed to tackling it in big projects. Paying off technical debt is a process, not a project. You do not want to end up in a situation where you need to stop all feature development to rewrite your entire application every three to five years. This is why these teams dedicate 10-30% of to maintenance work that tackles technical debt. I call the tech debt that is surfaced and addressed as part of this process medium-sized debt. every sprint To determine what proportion of your sprint to allocate to tech debt, simply find the overlap between the parts of your codebase you'll modify with your feature work, and the parts of your codebase where your worse tech debt lives. You can then scope out the tech debt work and allocate resources accordingly. Some teams even increase the scope of their feature work to include the relevant tech debt clean up. More in this article ' '. How to stop wasting time on tech debt For this to work, individual contributors need to track medium-sized debt whenever they come across it. It is then the Team Lead's responsibility to prioritise this list of tech debt, and to discuss it with the Product Manager prior to sprint planning so that engineering resources can be allocate effectively. The process for large pieces of debt Every once in a while, your team will realise that some of the medium-sized debt they came across is actually due to a much larger piece of debt. For example, they may realise that the reason the frontend code is under-performing is because they should be using a different framework for the job. Left unattended, these large pieces of debt can cause huge problems, and—like all tech debt—get much worse as time goes by. The best companies I've interviewed have monthly or quarterly technical planning sessions in which all engineering and product leaders participate. Depending on the size of the company, Staff Engineer, Principal Engineers, and/or Engineering Managers are responsible for putting together technical proposals outlining the problem, solution, and business case for each of these large pieces of debt. These then get reviewed by engineering and product leadership and the ones that get prioritised are added to the roadmap. How to achieve this easier In order to be able to run this process, you need to have visibility into your tech debt. A lot of companies I've spoken to try to achieve this by creating a tech debt backlog in their project management tool or in a spreadsheet. It's a great way to start, but here's the problem: these issues will not contain the context necessary for you to prioritise them effectively. Not only do you need to rank each tech debt issue against all others, you also need to convincingly argue that fixing this tech debt is more important than using these same engineering resources towards shipping a new feature instead. Here's the vicious cycle that ensues: the team tracks debt, you can't prioritise it, so you can't fix it, the backlog grows, it's even harder to prioritise and make sense of it, you're still not effectively tackling your debt, so the team stops tracking it. You no longer have visibility into your debt, still can't prioritise it, and it was all for nothing. We built Stepsize to solve this exact problem. With our product, engineers can track debt directly from their workflow (code editor, pull request, Slack, and more) so that you can have visibility into your debt. Stepsize automatically picks up important context like the code the debt relates to, and engineers get to quantify the impact the debt is having on the business and the risks it presents (e.g. time lost, customer risk, and more) so that you can prioritise it easily. You can join the best software companies by adopting this process, start here. Previously published at https://www.stepsize.com/blog/how-to-maintain-a-healthy-codebase-while-shipping-fast

How To Manage Technical Debt Properly

We've been working recently on adding rules to help write better regular expressions in Java. I've talked already about rules to and with . Those rules help you make sure your regular expressions are accurate and maintainable. Today I will show you how to make sure that the regular expression won’t crash your program. find errors in character classes the use of boundary markers and overly complex regular expressions As a brief reminder: regular expressions are a terse and powerful mechanism for matching patterns in strings. Part of the power of regular expressions is that a pattern can concisely describe a string that might be much larger than the original pattern. Sometimes much, much larger. Sometimes enough to overflow the stack and crash your application. Due to the way regular expression matching is implemented in Java (and many other languages/libraries), matching a pattern may - depending on the regex - require stack space proportional to the length of the input. This means large inputs could cause the program to crash with a when you try to use the regex. StackOverflowException We ran into this problem in our own code when analysis tried  to find comments containing at least one word with more than a given number of characters. For this we used a regex similar to , which would cause the analysis to crash on source files containing sufficiently long comments. To prevent problems like this for our future selves as well as for you, dear users, we implemented a rule which can detect problems like this: #(.|\n)*\w{3,} java:S5998 - Regular expressions should not overflow the stack In theory any regex is susceptible to stack overflow if it contains a repetition that contains some sort of branching, such as another repetition or an alternative. However, for some regular expressions the length of input required to make them crash is much larger than for others. To account for this, our rule tries to estimate how much stack space a regular expression will consume relative to the input size and only raises issues on regular expressions whose stack consumption exceeds a configurable threshold. One way to avoid stack consumption in regular expressions is to use . Possessive quantifiers are created by adding a to a quantifier (e.g. instead of ). Doing so disables . In addition to avoiding issues with catastrophic backtracking, making a quantifier possessive allows a pattern to be matched without consuming stack space. The problem is that sometimes backtracking is necessary and using possessive quantifiers to disable it may leave you with a regex that can never match any input. possessive quantifiers + x*+ x* backtracking Consider for example the regex I cited above: : If we try to fix the stack overflow by making the quantifier possessive, we end up with . This regex can never match anything because any input that could be matched by will already have been matched by and, being possessive, it won’t give it back. Luckily we have a rule that warns you about issues like this: #(.|\n)*\w{3,} #(.|\n)*+\w{3,} \w (.|\n)*+ java:S5994 - Regex patterns following a possessive quantifier should not always fail So how would one properly fix this issue? In our case, we decided to get rid of the regex altogether since there wasn’t really a good reason to use a regex here. But the regex could also be salvaged easily enough by getting rid of the alternation. The intent of was to match any character, including line breaks, because . does not match line breaks by default. The proper way to match any character would be to enable the flag, which can also be enabled from within the regex using . So either or would work (the latter of which also works when using methods that don’t involve ). .|\n DOTALL (?s) Pattern.compile(“#.*\\w{3,}”, Pattern.DOTALL) ”(?s)#.*\\{3,}” Pattern.compile Another regex susceptible to stack overflows would be something as simple as . Here the alternation can be removed by using a character class instead, which doesn’t require stack space to match: . Luckily we have a rule that finds alternations that can be replaced by character classes and suggests just that replacement like in the following code: (a|b)* [ab]* Spring Boot java:S6035 - Single-character alternations in regular expressions should be replaced with character classes Regular expressions are a truly powerful feature. Because great power comes with great responsibility (and great opportunities for screwing things up, or confusing your colleagues and future-you), we now offer a total of 24 rules targeting regular expressions. They are all available today in SonarCloud. These three rules around avoiding stack overflows are available starting from SonarQube 8.7, but the rest are already released. You can see them all at . rules.sonarsource.com Finally, note that some of the rules perform in-depth automata-based analyses on your regular expressions to identify issues as accurately as possible. This is an extremely promising approach and we will probably discuss this feature in a future blog post because we truly believe it’s amazing. This will for sure bring A LOT to regex code quality in general, so stay tuned!

Avoid Stack Overflows By Writing Regexes Properly

Perhaps it is not news to everyone that there are two hard things in Computer Science . I previously explained why I felt because there is some art in doing it . I will not spend any time here arguing whether naming things is an art or not. programming is not boring Instead, I will just go straight into how to name things properly. All the examples below uses the even though the same principles can be applied to other languages. Julia language Why? To me, it is extremely important to write code that is readable and easy to understand. If I write it properly, my colleagues will be able to read it, support it, and enhance it going forward. If I write it badly, I may even curse at myself in the future. I will not cover naming conventions such as or , as they are fairly well documented and understood. Rather, I will focus more about the semantics. CamelCase snake_case As our journey begins... What are the things that we need to give names to? In Julia, the main things are modules, data types, functions, constants and variables. The very first decision is to choose between using a , a , or an . verb noun adjective This is actually not too difficult. One reasonable approach is to adopt the following convention: Naming modules A good module name typically encompasses a group of concepts and functionalities provided by the module. It needs to be broad enough to cover all functionalities but specific enough to distinguish itself from other modules. For example, I have a module that provides an implementation of a circular linked list. I do not name it as , nor would I name it as , for those are too broad of a concept. CircularList LinkedList List Sometimes you want to think bigger and name the module a little broader than what is currently implemented. I think it is appropriate as long as there is a plan to develop the package further, and it does not cause any confusion for any user of the package. But, it should not miss the mark. Additional guidance can be found at the documentation. Julia package naming guidelines Naming data types Data types are used to represent either abstract concepts (abstract types) or concrete data structures (concrete types). That's why using nouns would be appropriate. In the case that data types represent behavior or traits, it is appropriate to use adjective such as and . Iterable Pretty A general rule of thumb is to come up with names that are not too long. I would say any name that is composed of more than three words is . code smell So, is perfectly fine and even is acceptable but would be too long. ProductCatalog ElectronicProductCatalog ElectronicDepartmentProductCatalog Why is it bad? It is because long names are harder to read and spelling mistake are hard to find, causing headaches during debugging. Naming functions For functions, when should I use verbs? And when should I use nouns? There is no hard-and-fast rule. Based upon my experience, I have developed an intuition to make these kinds of judgment. Let me illustrate my thought process with an example. How a noun looks better than a verb... Let's say I am working on an e-commerce site and I have a data type. I want to define a function that determines the price of the product based upon the current market condition. I can think of two names - and . Product current_price calculate_price Now, consider the code below: product products current_price(product) price_range
        add(search_result, product) for in if in end end Does it look better or worse if I choose instead? I bet it would look worse! calculate_price The reason why looks better is that it's easier to read. I can read the code as But, I cannot read the code as " current_price "if current price of the product is in the price range..." if calculate price of the product is in the price range...". Get it? When I use , I'm emphasizing the thing that is being returned from the function rather than how it does its job. current_price At this point, one may argue that the readability issue can be resolved with a temporary variable.  Let's assign the result of the function call to a variable: price product products
    price = calculate_price(product) price price_range
        add(search_result, product) for in if in end end Sure, that could work but obviously it limits the way you write code, so I can't say it's optimal. How a verb looks better than a noun... Next, let's consider the case that I need a new function that find the best price of the product using several different pricing algorithms. So, the pricing function needs to take an algorithm argument. Let's write the function and its corresponding doc string above: current_price(product::Product, algorithm::Algorithm) "Return the current price of the product calculated using the specified algorithm." At this point, it starts to feel just a little more awkward to read. Let's try to use a verb: calculate_price(product::Product, algorithm::Algorithm) "Calculate the price of the product using the specified algorithm." Using a verb makes it more natural when you need to emphasize the action being taken to get the job done. In this example, the use of calculate goes together with the argument algorithm quite well. So, my point is, what do you want to emphasize when calling the function. Is it the thing that it returns, or the process that it goes through? You should be able to make a better decision when you can answer the above question. Naming Constants/Variables I believe the best code should be readable. More often than not, I have heard from other programming experts about using meaningful words for all variables in the code. I can agree to that most of the time, until the verbosity kicks in and kills readability. Religiously. I can think of two examples where it makes sense to use terse names. Doing Math The first case is code that performs heavy-lifting mathematical calculations. It is usually more natural to use math symbols than English words. Julia has and this is an area where it shines. Here's an example from my package: full support of Unicode BoxCoxTrans.jl transform(𝐱, λ; α = , scaled = , kwargs...) α != 𝐱 .+= α any(𝐱 .<= ) && throw( ( )) scaled
        gm = geomean(𝐱)
        @. λ ≈ ? gm * log(𝐱) : (𝐱 ^ λ - ) / (λ * gm ^ (λ - )) @. λ ≈ ? log(𝐱) : (𝐱 ^ λ - ) / λ function 0 false if 0 end 0 DomainError "Data must be positive and ideally greater than 1.  You may specify α argument(shift). " if 0 1 1 else 0 1 end end At current state, the code looks fairly clean and maybe even resembles the formula found in a math research paper. By contrast, it would look very ugly if I have to replace all symbols with names like , , and . alpha lambda time_series Indexing arrays The second case relates to the argument about naming indexing variables such as . I generally oppose this idea. For simple code, it does not matter. For something more complex, it goes against you and hurts readability. index Consider this code that I found from the package: LinearAlgebra rcswap!(i:: , j:: , X:: {<: }) k = :size(X, )
        X[k,i], X[k,j] = X[k,j], X[k,i] k = :size(X, )
        X[i,k], X[j,k] = X[j,k], X[i,k] ## Swap rows i and j and columns i and j in X function Integer Integer StridedMatrix Number for 1 1 end for 1 2 end end Let's just do an exercise and see how it looks if we replace those short variable names with the more meaningful and longer version: rcswap!(index1:: , index2:: , matrix:: {<: }) position = :size(matrix, )
        matrix[position,index1], matrix[position,index2] = 
            matrix[position,index2], matrix[position,index1] position = :size(matrix, )
        matrix[index1,position], matrix[index2,position] = 
            matrix[index2,position], matrix[index1,position] function Integer Integer StridedMatrix Number for 1 1 end for 1 2 end end If the purpose of using longer variable names is to improve readability, then this is doing more harm than good. By contrast, using single-letter variable names is not too bad. In fact, it is quite common that single-letter variable names are used for indexing arrays in any programming language tutorials (e.g. , , , and ). python java javascript rust In addition, whenever I read code, my brain already translates them to read like index. Really, there is no difference between , , or . i j k index They all look the same to me. Wrapping up... Is naming things actually difficult? Definitely, maybe. You may think that I always name things properly? Wrong! I am definitely not perfect. Having written a book and a couple of blog posts, I have come to realize that writing code is no difference from other types of writing in general. You must keep revising (refactoring) to make it right. I do believe that practice makes perfect. I would encourage you to ask someone else to read your code and give you feedback. P.S. For more tips in writing good code in Julia, consider picking up my book Hands-on Design Patterns and Best Practices with Julia .

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