More on Leadership
Sam Hickmann
3 years ago
Improving collaboration with the Six Thinking Hats
Six Thinking Hats was written by Dr. Edward de Bono. "Six Thinking Hats" and parallel thinking allow groups to plan thinking processes in a detailed and cohesive way, improving collaboration.
Fundamental ideas
In order to develop strategies for thinking about specific issues, the method assumes that the human brain thinks in a variety of ways that can be intentionally challenged. De Bono identifies six brain-challenging directions. In each direction, the brain brings certain issues into conscious thought (e.g. gut instinct, pessimistic judgement, neutral facts). Some may find wearing hats unnatural, uncomfortable, or counterproductive.
The example of "mismatch" sensitivity is compelling. In the natural world, something out of the ordinary may be dangerous. This mode causes negative judgment and critical thinking.
Colored hats represent each direction. Putting on a colored hat symbolizes changing direction, either literally or metaphorically. De Bono first used this metaphor in his 1971 book "Lateral Thinking for Management" to describe a brainstorming framework. These metaphors allow more complete and elaborate thought separation. Six thinking hats indicate ideas' problems and solutions.
Similarly, his CoRT Thinking Programme introduced "The Five Stages of Thinking" method in 1973.
| HAT | OVERVIEW | TECHNIQUE |
|---|---|---|
| BLUE | "The Big Picture" & Managing | CAF (Consider All Factors); FIP (First Important Priorities) |
| WHITE | "Facts & Information" | Information |
| RED | "Feelings & Emotions" | Emotions and Ego |
| BLACK | "Negative" | PMI (Plus, Minus, Interesting); Evaluation |
| YELLOW | "Positive" | PMI |
| GREEN | "New Ideas" | Concept Challenge; Yes, No, Po |
Strategies and programs
After identifying the six thinking modes, programs can be created. These are groups of hats that encompass and structure the thinking process. Several of these are included in the materials for franchised six hats training, but they must often be adapted. Programs are often "emergent," meaning the group plans the first few hats and the facilitator decides what to do next.
The group agrees on how to think, then thinks, then evaluates the results and decides what to do next. Individuals or groups can use sequences (and indeed hats). Each hat is typically used for 2 minutes at a time, although an extended white hat session is common at the start of a process to get everyone on the same page. The red hat is recommended to be used for a very short period to get a visceral gut reaction – about 30 seconds, and in practice often takes the form of dot-voting.
| ACTIVITY | HAT SEQUENCE |
|---|---|
| Initial Ideas | Blue, White, Green, Blue |
| Choosing between alternatives | Blue, White, (Green), Yellow, Black, Red, Blue |
| Identifying Solutions | Blue, White, Black, Green, Blue |
| Quick Feedback | Blue, Black, Green, Blue |
| Strategic Planning | Blue, Yellow, Black, White, Blue, Green, Blue |
| Process Improvement | Blue, White, White (Other People's Views), Yellow, Black, Green, Red, Blue |
| Solving Problems | Blue, White, Green, Red, Yellow, Black, Green, Blue |
| Performance Review | Blue, Red, White, Yellow, Black, Green, Blue |
Use
Speedo's swimsuit designers reportedly used the six thinking hats. "They used the "Six Thinking Hats" method to brainstorm, with a green hat for creative ideas and a black one for feasibility.
Typically, a project begins with extensive white hat research. Each hat is used for a few minutes at a time, except the red hat, which is limited to 30 seconds to ensure an instinctive gut reaction, not judgement. According to Malcolm Gladwell's "blink" theory, this pace improves thinking.
De Bono believed that the key to a successful Six Thinking Hats session was focusing the discussion on a particular approach. A meeting may be called to review and solve a problem. The Six Thinking Hats method can be used in sequence to explore the problem, develop a set of solutions, and choose a solution through critical examination.
Everyone may don the Blue hat to discuss the meeting's goals and objectives. The discussion may then shift to Red hat thinking to gather opinions and reactions. This phase may also be used to determine who will be affected by the problem and/or solutions. The discussion may then shift to the (Yellow then) Green hat to generate solutions and ideas. The discussion may move from White hat thinking to Black hat thinking to develop solution set criticisms.
Because everyone is focused on one approach at a time, the group is more collaborative than if one person is reacting emotionally (Red hat), another is trying to be objective (White hat), and another is critical of the points which emerge from the discussion (Black hat). The hats help people approach problems from different angles and highlight problem-solving flaws.
Jason Kottke
3 years ago
Lessons on Leadership from the Dancing Guy
This is arguably the best three-minute demonstration I've ever seen of anything. Derek Sivers turns a shaky video of a lone dancing guy at a music festival into a leadership lesson.
A leader must have the courage to stand alone and appear silly. But what he's doing is so straightforward that it's almost instructive. This is critical. You must be simple to follow!
Now comes the first follower, who plays an important role: he publicly demonstrates how to follow. The leader embraces him as an equal, so it's no longer about the leader — it's about them, plural. He's inviting his friends to join him. It takes courage to be the first follower! You stand out and dare to be mocked. Being a first follower is a style of leadership that is underappreciated. The first follower elevates a lone nut to the position of leader. If the first follower is the spark that starts the fire, the leader is the flint.
This link was sent to me by @ottmark, who noted its resemblance to Kurt Vonnegut's three categories of specialists required for revolution.
The rarest of these specialists, he claims, is an actual genius – a person capable generating seemingly wonderful ideas that are not widely known. "A genius working alone is generally dismissed as a crazy," he claims.
The second type of specialist is much easier to find: a highly intellectual person in good standing in his or her community who understands and admires the genius's new ideas and can attest that the genius is not insane. "A person like him working alone can only crave loudly for changes, but fail to say what their shapes should be," Slazinger argues.
Jeff Veen reduced the three personalities to "the inventor, the investor, and the evangelist" on Twitter.

Will Lockett
3 years ago
Tesla recently disclosed its greatest secret.
The VP has revealed a secret that should frighten the rest of the EV world.
Tesla led the EV revolution. Elon Musk's invention offers a viable alternative to gas-guzzlers. Tesla has lost ground in recent years. VW, BMW, Mercedes, and Ford offer EVs with similar ranges, charging speeds, performance, and cost. Tesla's next-generation 4680 battery pack, Roadster, Cybertruck, and Semi were all delayed. CATL offers superior batteries than the 4680. Martin Viecha, Tesla's Vice President, recently told Business Insider something that startled the EV world and will establish Tesla as the EV king.
Viecha mentioned that Tesla's production costs have dropped 57% since 2017. This isn't due to cheaper batteries or devices like Model 3. No, this is due to amazing factory efficiency gains.
Musk wasn't crazy to want a nearly 100% automated production line, and Tesla's strategy of sticking with one model and improving it has paid off. Others change models every several years. This implies they must spend on new R&D, set up factories, and modernize service and parts systems. All of this costs a ton of money and prevents them from refining production to cut expenses.
Meanwhile, Tesla updates its vehicles progressively. Everything from the backseats to the screen has been enhanced in a 2022 Model 3. Tesla can refine, standardize, and cheaply produce every part without changing the production line.
In 2017, Tesla's automobile production averaged $84,000. In 2022, it'll be $36,000.
Mr. Viecha also claimed that new factories in Shanghai and Berlin will be significantly cheaper to operate once fully operating.
Tesla's hand is visible. Tesla selling $36,000 cars for $60,000 This barely beats the competition. Model Y long-range costs just over $60,000. Tesla makes $24,000+ every sale, giving it a 40% profit margin, one of the best in the auto business.
VW I.D4 costs about the same but makes no profit. Tesla's rivals face similar challenges. Their EVs make little or no profit.
Tesla costs the same as other EVs, but they're in a different league.
But don't forget that the battery pack accounts for 40% of an EV's cost. Tesla may soon fully utilize its 4680 battery pack.
The 4680 battery pack has larger cells and a unique internal design. This means fewer cells are needed for a car, making it cheaper to assemble and produce (per kWh). Energy density and charge speeds increase slightly.
Tesla underestimated the difficulty of making this revolutionary new cell. Each time they try to scale up production, quality drops and rejected cells rise.
Tesla recently installed this battery pack in Model Ys and is scaling production. If they succeed, Tesla battery prices will plummet.
Tesla's Model Ys 2170 battery costs $11,000. The same size pack with 4680 cells costs $3,400 less. Once scaled, it could be $5,500 (50%) less. The 4680 battery pack could reduce Tesla production costs by 20%.
With these cost savings, Tesla could sell Model Ys for $40,000 while still making a profit. They could offer a $25,000 car.
Even with new battery technology, it seems like other manufacturers will struggle to make EVs profitable.
Teslas cost about the same as competitors, so don't be fooled. Behind the scenes, they're still years ahead, and the 4680 battery pack and new factories will only increase that lead. Musk faces a first. He could sell Teslas at current prices and make billions while other manufacturers struggle. Or, he could massively undercut everyone and crush the competition once and for all. Tesla and Elon win.
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Jared Heyman
2 years ago
The survival and demise of Y Combinator startups
I've written a lot about Y Combinator's success, but as any startup founder or investor knows, many startups fail.
Rebel Fund invests in the top 5-10% of new Y Combinator startups each year, so we focus on identifying and supporting the most promising technology startups in our ecosystem. Given the power law dynamic and asymmetric risk/return profile of venture capital, we worry more about our successes than our failures. Since the latter still counts, this essay will focus on the proportion of YC startups that fail.
Since YC's launch in 2005, the figure below shows the percentage of active, inactive, and public/acquired YC startups by batch.
As more startups finish, the blue bars (active) decrease significantly. By 12 years, 88% of startups have closed or exited. Only 7% of startups reach resolution each year.
YC startups by status after 12 years:
Half the startups have failed, over one-third have exited, and the rest are still operating.
In venture investing, it's said that failed investments show up before successful ones. This is true for YC startups, but only in their early years.
Below, we only present resolved companies from the first chart. Some companies fail soon after establishment, but after a few years, the inactive vs. public/acquired ratio stabilizes around 55:45. After a few years, a YC firm is roughly as likely to quit as fail, which is better than I imagined.
I prepared this post because Rebel investors regularly question me about YC startup failure rates and how long it takes for them to exit or shut down.
Early-stage venture investors can overlook it because 100x investments matter more than 0x investments.
YC founders can ignore it because it shouldn't matter if many of their peers succeed or fail ;)

Khyati Jain
3 years ago
By Engaging in these 5 Duplicitous Daily Activities, You Rapidly Kill Your Brain Cells
No, it’s not smartphones, overeating, or sugar.
Everyday practices affect brain health. Good brain practices increase memory and cognition.
Bad behaviors increase stress, which destroys brain cells.
Bad behaviors can reverse evolution and diminish the brain. So, avoid these practices for brain health.
1. The silent assassin
Introverts appreciated quarantine.
Before the pandemic, they needed excuses to remain home; thereafter, they had enough.
I am an introvert, and I didn’t hate quarantine. There are billions of people like me who avoid people.
Social relationships are important for brain health. Social anxiety harms your brain.
Antisocial behavior changes brains. It lowers IQ and increases drug abuse risk.
What you can do is as follows:
Make a daily commitment to engage in conversation with a stranger. Who knows, you might turn out to be your lone mate.
Get outside for at least 30 minutes each day.
Shop for food locally rather than online.
Make a call to a friend you haven't spoken to in a while.
2. Try not to rush things.
People love hustle culture. This economy requires a side gig to save money.
Long hours reduce brain health. A side gig is great until you burn out.
Work ages your wallet and intellect. Overworked brains age faster and lose cognitive function.
Working longer hours can help you make extra money, but it can harm your brain.
Side hustle but don't overwork.
What you can do is as follows:
Decide what hour you are not permitted to work after.
Three hours prior to night, turn off your laptop.
Put down your phone and work.
Assign due dates to each task.
3. Location is everything!
The environment may cause brain fog. High pollution can cause brain damage.
Air pollution raises Alzheimer's risk. Air pollution causes cognitive and behavioral abnormalities.
Polluted air can trigger early development of incurable brain illnesses, not simply lung harm.
Your city's air quality is uncontrollable. You may take steps to improve air quality.
In Delhi, schools and colleges are closed to protect pupils from polluted air. So I've adapted.
What you can do is as follows:
To keep your mind healthy and young, make an investment in a high-quality air purifier.
Enclose your windows during the day.
Use a N95 mask every day.
4. Don't skip this meal.
Fasting intermittently is trendy. Delaying breakfast to finish fasting is frequent.
Some skip breakfast and have a hefty lunch instead.
Skipping breakfast might affect memory and focus. Skipping breakfast causes low cognition, delayed responsiveness, and irritation.
Breakfast affects mood and productivity.
Intermittent fasting doesn't prevent healthy breakfasts.
What you can do is as follows:
Try to fast for 14 hours, then break it with a nutritious breakfast.
So that you can have breakfast in the morning, eat dinner early.
Make sure your breakfast is heavy in fiber and protein.
5. The quickest way to damage the health of your brain
Brain health requires water. 1% dehydration can reduce cognitive ability by 5%.
Cerebral fog and mental clarity might result from 2% brain dehydration. Dehydration shrinks brain cells.
Dehydration causes midday slumps and unproductivity. Water improves work performance.
Dehydration can harm your brain, so drink water throughout the day.
What you can do is as follows:
Always keep a water bottle at your desk.
Enjoy some tasty herbal teas.
With a big glass of water, begin your day.
Bring your own water bottle when you travel.
Conclusion
Bad habits can harm brain health. Low cognition reduces focus and productivity.
Unproductive work leads to procrastination, failure, and low self-esteem.
Avoid these harmful habits to optimize brain health and function.

Samer Buna
2 years ago
The Errors I Committed As a Novice Programmer
Learn to identify them, make habits to avoid them
First, a clarification. This article is aimed to make new programmers aware of their mistakes, train them to detect them, and remind them to prevent them.
I learned from all these blunders. I'm glad I have coding habits to avoid them. Do too.
These mistakes are not ordered.
1) Writing code haphazardly
Writing good content is hard. It takes planning and investigation. Quality programs don't differ.
Think. Research. Plan. Write. Validate. Modify. Unfortunately, no good acronym exists. Create a habit of doing the proper quantity of these activities.
As a newbie programmer, my biggest error was writing code without thinking or researching. This works for small stand-alone apps but hurts larger ones.
Like saying anything you might regret, you should think before coding something you could regret. Coding expresses your thoughts.
When angry, count to 10 before you speak. If very angry, a hundred. — Thomas Jefferson.
My quote:
When reviewing code, count to 10 before you refactor a line. If the code does not have tests, a hundred. — Samer Buna
Programming is primarily about reviewing prior code, investigating what is needed and how it fits into the current system, and developing small, testable features. Only 10% of the process involves writing code.
Programming is not writing code. Programming need nurturing.
2) Making excessive plans prior to writing code
Yes. Planning before writing code is good, but too much of it is bad. Water poisons.
Avoid perfect plans. Programming does not have that. Find a good starting plan. Your plan will change, but it helped you structure your code for clarity. Overplanning wastes time.
Only planning small features. All-feature planning should be illegal! The Waterfall Approach is a step-by-step system. That strategy requires extensive planning. This is not planning. Most software projects fail with waterfall. Implementing anything sophisticated requires agile changes to reality.
Programming requires responsiveness. You'll add waterfall plan-unthinkable features. You will eliminate functionality for reasons you never considered in a waterfall plan. Fix bugs and adjust. Be agile.
Plan your future features, though. Do it cautiously since too little or too much planning can affect code quality, which you must risk.
3) Underestimating the Value of Good Code
Readability should be your code's exclusive goal. Unintelligible code stinks. Non-recyclable.
Never undervalue code quality. Coding communicates implementations. Coders must explicitly communicate solution implementations.
Programming quote I like:
Always code as if the guy who ends up maintaining your code will be a violent psychopath who knows where you live. — John Woods
John, great advice!
Small things matter. If your indentation and capitalization are inconsistent, you should lose your coding license.
Long queues are also simple. Readability decreases after 80 characters. To highlight an if-statement block, you might put a long condition on the same line. No. Just never exceed 80 characters.
Linting and formatting tools fix many basic issues like this. ESLint and Prettier work great together in JavaScript. Use them.
Code quality errors:
Multiple lines in a function or file. Break long code into manageable bits. My rule of thumb is that any function with more than 10 lines is excessively long.
Double-negatives. Don't.
Using double negatives is just very not not wrong
Short, generic, or type-based variable names. Name variables clearly.
There are only two hard things in Computer Science: cache invalidation and naming things. — Phil Karlton
Hard-coding primitive strings and numbers without descriptions. If your logic relies on a constant primitive string or numeric value, identify it.
Avoiding simple difficulties with sloppy shortcuts and workarounds. Avoid evasion. Take stock.
Considering lengthier code better. Shorter code is usually preferable. Only write lengthier versions if they improve code readability. For instance, don't utilize clever one-liners and nested ternary statements just to make the code shorter. In any application, removing unneeded code is better.
Measuring programming progress by lines of code is like measuring aircraft building progress by weight. — Bill Gates
Excessive conditional logic. Conditional logic is unnecessary for most tasks. Choose based on readability. Measure performance before optimizing. Avoid Yoda conditions and conditional assignments.
4) Selecting the First Approach
When I started programming, I would solve an issue and move on. I would apply my initial solution without considering its intricacies and probable shortcomings.
After questioning all the solutions, the best ones usually emerge. If you can't think of several answers, you don't grasp the problem.
Programmers do not solve problems. Find the easiest solution. The solution must work well and be easy to read, comprehend, and maintain.
There are two ways of constructing a software design. One way is to make it so simple that there are obviously no deficiencies, and the other way is to make it so complicated that there are no obvious deficiencies. — C.A.R. Hoare
5) Not Giving Up
I generally stick with the original solution even though it may not be the best. The not-quitting mentality may explain this. This mindset is helpful for most things, but not programming. Program writers should fail early and often.
If you doubt a solution, toss it and rethink the situation. No matter how much you put in that solution. GIT lets you branch off and try various solutions. Use it.
Do not be attached to code because of how much effort you put into it. Bad code needs to be discarded.
6) Avoiding Google
I've wasted time solving problems when I should have researched them first.
Unless you're employing cutting-edge technology, someone else has probably solved your problem. Google It First.
Googling may discover that what you think is an issue isn't and that you should embrace it. Do not presume you know everything needed to choose a solution. Google surprises.
But Google carefully. Newbies also copy code without knowing it. Use only code you understand, even if it solves your problem.
Never assume you know how to code creatively.
The most dangerous thought that you can have as a creative person is to think that you know what you’re doing. — Bret Victor
7) Failing to Use Encapsulation
Not about object-oriented paradigm. Encapsulation is always useful. Unencapsulated systems are difficult to maintain.
An application should only handle a feature once. One object handles that. The application's other objects should only see what's essential. Reducing application dependencies is not about secrecy. Following these guidelines lets you safely update class, object, and function internals without breaking things.
Classify logic and state concepts. Class means blueprint template. Class or Function objects are possible. It could be a Module or Package.
Self-contained tasks need methods in a logic class. Methods should accomplish one thing well. Similar classes should share method names.
As a rookie programmer, I didn't always establish a new class for a conceptual unit or recognize self-contained units. Newbie code has a Util class full of unrelated code. Another symptom of novice code is when a small change cascades and requires numerous other adjustments.
Think before adding a method or new responsibilities to a method. Time's needed. Avoid skipping or refactoring. Start right.
High Cohesion and Low Coupling involves grouping relevant code in a class and reducing class dependencies.
8) Arranging for Uncertainty
Thinking beyond your solution is appealing. Every line of code will bring up what-ifs. This is excellent for edge cases but not for foreseeable needs.
Your what-ifs must fall into one of these two categories. Write only code you need today. Avoid future planning.
Writing a feature for future use is improper. No.
Write only the code you need today for your solution. Handle edge-cases, but don't introduce edge-features.
Growth for the sake of growth is the ideology of the cancer cell. — Edward Abbey
9) Making the incorrect data structure choices
Beginner programmers often overemphasize algorithms when preparing for interviews. Good algorithms should be identified and used when needed, but memorizing them won't make you a programming genius.
However, learning your language's data structures' strengths and shortcomings will make you a better developer.
The improper data structure shouts "newbie coding" here.
Let me give you a few instances of data structures without teaching you:
Managing records with arrays instead of maps (objects).
Most data structure mistakes include using lists instead of maps to manage records. Use a map to organize a list of records.
This list of records has an identifier to look up each entry. Lists for scalar values are OK and frequently superior, especially if the focus is pushing values to the list.
Arrays and objects are the most common JavaScript list and map structures, respectively (there is also a map structure in modern JavaScript).
Lists over maps for record management often fail. I recommend always using this point, even though it only applies to huge collections. This is crucial because maps are faster than lists in looking up records by identifier.
Stackless
Simple recursive functions are often tempting when writing recursive programming. In single-threaded settings, optimizing recursive code is difficult.
Recursive function returns determine code optimization. Optimizing a recursive function that returns two or more calls to itself is harder than optimizing a single call.
Beginners overlook the alternative to recursive functions. Use Stack. Push function calls to a stack and start popping them out to traverse them back.
10) Worsening the current code
Imagine this:
Add an item to that room. You might want to store that object anywhere as it's a mess. You can finish in seconds.
Not with messy code. Do not worsen! Keep the code cleaner than when you started.
Clean the room above to place the new object. If the item is clothing, clear a route to the closet. That's proper execution.
The following bad habits frequently make code worse:
code duplication You are merely duplicating code and creating more chaos if you copy/paste a code block and then alter just the line after that. This would be equivalent to adding another chair with a lower base rather than purchasing a new chair with a height-adjustable seat in the context of the aforementioned dirty room example. Always keep abstraction in mind, and use it when appropriate.
utilizing configuration files not at all. A configuration file should contain the value you need to utilize if it may differ in certain circumstances or at different times. A configuration file should contain a value if you need to use it across numerous lines of code. Every time you add a new value to the code, simply ask yourself: "Does this value belong in a configuration file?" The most likely response is "yes."
using temporary variables and pointless conditional statements. Every if-statement represents a logic branch that should at the very least be tested twice. When avoiding conditionals doesn't compromise readability, it should be done. The main issue with this is that branch logic is being used to extend an existing function rather than creating a new function. Are you altering the code at the appropriate level, or should you go think about the issue at a higher level every time you feel you need an if-statement or a new function variable?
This code illustrates superfluous if-statements:
function isOdd(number) {
if (number % 2 === 1) {
return true;
} else {
return false;
}
}Can you spot the biggest issue with the isOdd function above?
Unnecessary if-statement. Similar code:
function isOdd(number) {
return (number % 2 === 1);
};11) Making remarks on things that are obvious
I've learnt to avoid comments. Most code comments can be renamed.
instead of:
// This function sums only odd numbers in an array
const sum = (val) => {
return val.reduce((a, b) => {
if (b % 2 === 1) { // If the current number is odd
a+=b; // Add current number to accumulator
}
return a; // The accumulator
}, 0);
};Commentless code looks like this:
const sumOddValues = (array) => {
return array.reduce((accumulator, currentNumber) => {
if (isOdd(currentNumber)) {
return accumulator + currentNumber;
}
return accumulator;
}, 0);
};Better function and argument names eliminate most comments. Remember that before commenting.
Sometimes you have to use comments to clarify the code. This is when your comments should answer WHY this code rather than WHAT it does.
Do not write a WHAT remark to clarify the code. Here are some unnecessary comments that clutter code:
// create a variable and initialize it to 0
let sum = 0;
// Loop over array
array.forEach(
// For each number in the array
(number) => {
// Add the current number to the sum variable
sum += number;
}
);Avoid that programmer. Reject that code. Remove such comments if necessary. Most importantly, teach programmers how awful these remarks are. Tell programmers who publish remarks like this that they may lose their jobs. That terrible.
12) Skipping tests
I'll simplify. If you develop code without tests because you think you're an excellent programmer, you're a rookie.
If you're not writing tests in code, you're probably testing manually. Every few lines of code in a web application will be refreshed and interacted with. Also. Manual code testing is fine. To learn how to automatically test your code, manually test it. After testing your application, return to your code editor and write code to automatically perform the same interaction the next time you add code.
Human. After each code update, you will forget to test all successful validations. Automate it!
Before writing code to fulfill validations, guess or design them. TDD is real. It improves your feature design thinking.
If you can use TDD, even partially, do so.
13) Making the assumption that if something is working, it must be right.
See this sumOddValues function. Is it flawed?
const sumOddValues = (array) => {
return array.reduce((accumulator, currentNumber) => {
if (currentNumber % 2 === 1) {
return accumulator + currentNumber;
}
return accumulator;
});
};
console.assert(
sumOddValues([1, 2, 3, 4, 5]) === 9
);Verified. Good life. Correct?
Code above is incomplete. It handles some scenarios correctly, including the assumption used, but it has many other issues. I'll list some:
#1: No empty input handling. What happens when the function is called without arguments? That results in an error revealing the function's implementation:
TypeError: Cannot read property 'reduce' of undefined.Two main factors indicate faulty code.
Your function's users shouldn't come across implementation-related information.
The user cannot benefit from the error. Simply said, they were unable to use your function. They would be aware that they misused the function if the error was more obvious about the usage issue. You might decide to make the function throw a custom exception, for instance:
TypeError: Cannot execute function for empty list.Instead of returning an error, your method should disregard empty input and return a sum of 0. This case requires action.
Problem #2: No input validation. What happens if the function is invoked with a text, integer, or object instead of an array?
The function now throws:
sumOddValues(42);
TypeError: array.reduce is not a functionUnfortunately, array. cut's a function!
The function labels anything you call it with (42 in the example above) as array because we named the argument array. The error says 42.reduce is not a function.
See how that error confuses? An mistake like:
TypeError: 42 is not an array, dude.Edge-cases are #1 and #2. These edge-cases are typical, but you should also consider less obvious ones. Negative numbers—what happens?
sumOddValues([1, 2, 3, 4, 5, -13]) // => still 9-13's unusual. Is this the desired function behavior? Error? Should it sum negative numbers? Should it keep ignoring negative numbers? You may notice the function should have been titled sumPositiveOddNumbers.
This decision is simple. The more essential point is that if you don't write a test case to document your decision, future function maintainers won't know if you ignored negative values intentionally or accidentally.
It’s not a bug. It’s a feature. — Someone who forgot a test case
#3: Valid cases are not tested. Forget edge-cases, this function mishandles a straightforward case:
sumOddValues([2, 1, 3, 4, 5]) // => 11The 2 above was wrongly included in sum.
The solution is simple: reduce accepts a second input to initialize the accumulator. Reduce will use the first value in the collection as the accumulator if that argument is not provided, like in the code above. The sum included the test case's first even value.
This test case should have been included in the tests along with many others, such as all-even numbers, a list with 0 in it, and an empty list.
Newbie code also has rudimentary tests that disregard edge-cases.
14) Adhering to Current Law
Unless you're a lone supercoder, you'll encounter stupid code. Beginners don't identify it and assume it's decent code because it works and has been in the codebase for a while.
Worse, if the terrible code uses bad practices, the newbie may be enticed to use them elsewhere in the codebase since they learnt them from good code.
A unique condition may have pushed the developer to write faulty code. This is a nice spot for a thorough note that informs newbies about that condition and why the code is written that way.
Beginners should presume that undocumented code they don't understand is bad. Ask. Enquire. Blame it!
If the code's author is dead or can't remember it, research and understand it. Only after understanding the code can you judge its quality. Before that, presume nothing.
15) Being fixated on best practices
Best practices damage. It suggests no further research. Best practice ever. No doubts!
No best practices. Today's programming language may have good practices.
Programming best practices are now considered bad practices.
Time will reveal better methods. Focus on your strengths, not best practices.
Do not do anything because you read a quote, saw someone else do it, or heard it is a recommended practice. This contains all my article advice! Ask questions, challenge theories, know your options, and make informed decisions.
16) Being preoccupied with performance
Premature optimization is the root of all evil (or at least most of it) in programming — Donald Knuth (1974)
I think Donald Knuth's advice is still relevant today, even though programming has changed.
Do not optimize code if you cannot measure the suspected performance problem.
Optimizing before code execution is likely premature. You may possibly be wasting time optimizing.
There are obvious optimizations to consider when writing new code. You must not flood the event loop or block the call stack in Node.js. Remember this early optimization. Will this code block the call stack?
Avoid non-obvious code optimization without measurements. If done, your performance boost may cause new issues.
Stop optimizing unmeasured performance issues.
17) Missing the End-User Experience as a Goal
How can an app add a feature easily? Look at it from your perspective or in the existing User Interface. Right? Add it to the form if the feature captures user input. Add it to your nested menu of links if it adds a link to a page.
Avoid that developer. Be a professional who empathizes with customers. They imagine this feature's consumers' needs and behavior. They focus on making the feature easy to find and use, not just adding it to the software.
18) Choosing the incorrect tool for the task
Every programmer has their preferred tools. Most tools are good for one thing and bad for others.
The worst tool for screwing in a screw is a hammer. Do not use your favorite hammer on a screw. Don't use Amazon's most popular hammer on a screw.
A true beginner relies on tool popularity rather than problem fit.
You may not know the best tools for a project. You may know the best tool. However, it wouldn't rank high. You must learn your tools and be open to new ones.
Some coders shun new tools. They like their tools and don't want to learn new ones. I can relate, but it's wrong.
You can build a house slowly with basic tools or rapidly with superior tools. You must learn and use new tools.
19) Failing to recognize that data issues are caused by code issues
Programs commonly manage data. The software will add, delete, and change records.
Even the simplest programming errors can make data unpredictable. Especially if the same defective application validates all data.
Code-data relationships may be confusing for beginners. They may employ broken code in production since feature X is not critical. Buggy coding may cause hidden data integrity issues.
Worse, deploying code that corrected flaws without fixing minor data problems caused by these defects will only collect more data problems that take the situation into the unrecoverable-level category.
How do you avoid these issues? Simply employ numerous data integrity validation levels. Use several interfaces. Front-end, back-end, network, and database validations. If not, apply database constraints.
Use all database constraints when adding columns and tables:
If a column has a NOT NULL constraint, null values will be rejected for that column. If your application expects that field has a value, your database should designate its source as not null.
If a column has a UNIQUE constraint, the entire table cannot include duplicate values for that column. This is ideal for a username or email field on a Users table, for instance.
For the data to be accepted, a CHECK constraint, or custom expression, must evaluate to true. For instance, you can apply a check constraint to ensure that the values of a normal % column must fall within the range of 0 and 100.
With a PRIMARY KEY constraint, the values of the columns must be both distinct and not null. This one is presumably what you're utilizing. To distinguish the records in each table, the database needs have a primary key.
A FOREIGN KEY constraint requires that the values in one database column, typically a primary key, match those in another table column.
Transaction apathy is another data integrity issue for newbies. If numerous actions affect the same data source and depend on each other, they must be wrapped in a transaction that can be rolled back if one fails.
20) Reinventing the Wheel
Tricky. Some programming wheels need reinvention. Programming is undefined. New requirements and changes happen faster than any team can handle.
Instead of modifying the wheel we all adore, maybe we should rethink it if you need a wheel that spins at varied speeds depending on the time of day. If you don't require a non-standard wheel, don't reinvent it. Use the darn wheel.
Wheel brands can be hard to choose from. Research and test before buying! Most software wheels are free and transparent. Internal design quality lets you evaluate coding wheels. Try open-source wheels. Debug and fix open-source software simply. They're easily replaceable. In-house support is also easy.
If you need a wheel, don't buy a new automobile and put your maintained car on top. Do not include a library to use a few functions. Lodash in JavaScript is the finest example. Import shuffle to shuffle an array. Don't import lodash.
21) Adopting the incorrect perspective on code reviews
Beginners often see code reviews as criticism. Dislike them. Not appreciated. Even fear them.
Incorrect. If so, modify your mindset immediately. Learn from every code review. Salute them. Observe. Most crucial, thank reviewers who teach you.
Always learning code. Accept it. Most code reviews teach something new. Use these for learning.
You may need to correct the reviewer. If your code didn't make that evident, it may need to be changed. If you must teach your reviewer, remember that teaching is one of the most enjoyable things a programmer can do.
22) Not Using Source Control
Newbies often underestimate Git's capabilities.
Source control is more than sharing your modifications. It's much bigger. Clear history is source control. The history of coding will assist address complex problems. Commit messages matter. They are another way to communicate your implementations, and utilizing them with modest commits helps future maintainers understand how the code got where it is.
Commit early and often with present-tense verbs. Summarize your messages but be detailed. If you need more than a few lines, your commit is too long. Rebase!
Avoid needless commit messages. Commit summaries should not list new, changed, or deleted files. Git commands can display that list from the commit object. The summary message would be noise. I think a big commit has many summaries per file altered.
Source control involves discoverability. You can discover the commit that introduced a function and see its context if you doubt its need or design. Commits can even pinpoint which code caused a bug. Git has a binary search within commits (bisect) to find the bug-causing commit.
Source control can be used before commits to great effect. Staging changes, patching selectively, resetting, stashing, editing, applying, diffing, reversing, and others enrich your coding flow. Know, use, and enjoy them.
I consider a Git rookie someone who knows less functionalities.
23) Excessive Use of Shared State
Again, this is not about functional programming vs. other paradigms. That's another article.
Shared state is problematic and should be avoided if feasible. If not, use shared state as little as possible.
As a new programmer, I didn't know that all variables represent shared states. All variables in the same scope can change its data. Global scope reduces shared state span. Keep new states in limited scopes and avoid upward leakage.
When numerous resources modify common state in the same event loop tick, the situation becomes severe (in event-loop-based environments). Races happen.
This shared state race condition problem may encourage a rookie to utilize a timer, especially if they have a data lock issue. Red flag. No. Never accept it.
24) Adopting the Wrong Mentality Toward Errors
Errors are good. Progress. They indicate a simple way to improve.
Expert programmers enjoy errors. Newbies detest them.
If these lovely red error warnings irritate you, modify your mindset. Consider them helpers. Handle them. Use them to advance.
Some errors need exceptions. Plan for user-defined exceptions. Ignore some mistakes. Crash and exit the app.
25) Ignoring rest periods
Humans require mental breaks. Take breaks. In the zone, you'll forget breaks. Another symptom of beginners. No compromises. Make breaks mandatory in your process. Take frequent pauses. Take a little walk to plan your next move. Reread the code.
This has been a long post. You deserve a break.
