More on NFTs & Art

1eth1da
3 years ago
6 Rules to build a successful NFT Community in 2022

Too much NFT, Discord, and shitposting.
How do you choose?
How do you recruit more members to join your NFT project?
In 2021, a successful NFT project required:
Monkey/ape artwork
Twitter and Discord bot-filled
Roadmap overpromise
Goal was quick cash.
2022 and the years after will change that.
These are 6 Rules for a Strong NFT Community in 2022:
THINK LONG TERM
This relates to roadmap planning. Hype and dumb luck may drive NFT projects (ahem, goblins) but rarely will your project soar.
Instead, consider sustainability.
Plan your roadmap based on your team's abilities.
Do what you're already doing, but with NFTs, make it bigger and better.
You shouldn't copy a project's roadmap just because it was profitable.
This will lead to over-promising, team burnout, and an RUG NFT project.
OFFER VALUE
Building a great community starts with giving.
Why are musicians popular?
Because they offer entertainment for everyone, a random person becomes a fan, and more fans become a cult.
That's how you should approach your community.
TEAM UP
A great team helps.
An NFT project could have 3 or 2 people.
Credibility trumps team size.
Make sure your team can answer community questions, resolve issues, and constantly attend to them.
Don't overwork and burn out.
Your community will be able to recognize that you are trying too hard and give up on the project.
BUILD A GREAT PRODUCT
Bored Ape Yacht Club altered the NFT space.
Cryptopunks transformed NFTs.
Many others did, including Okay Bears.
What made them that way?
Because they answered a key question.
What is my NFT supposed to be?
Before planning art, this question must be answered.
NFTs can't be just jpegs.
What does it represent?
Is it a Metaverse-ready project?
What blockchain are you going to be using and why?
Set some ground rules for yourself. This helps your project's direction.
These questions will help you and your team set a direction for blockchain, NFT, and Web3 technology.
EDUCATE ON WEB3
The more the team learns about Web3 technology, the more they can offer their community.
Think tokens, metaverse, cross-chain interoperability and more.
BUILD A GREAT COMMUNITY
Several projects mistreat their communities.
They treat their community like "customers" and try to sell them NFT.
Providing Whitelists and giveaways aren't your only community-building options.
Think bigger.
Consider them family and friends, not wallets.
Consider them fans.
These are some tips to start your NFT project.

shivsak
3 years ago
A visual exploration of the REAL use cases for NFTs in the Future
In this essay, I studied REAL NFT use examples and their potential uses.
Knowledge of the Hype Cycle
Gartner's Hype Cycle.
It proposes 5 phases for disruptive technology.
1. Technology Trigger: the emergence of potentially disruptive technology.
2. Peak of Inflated Expectations: Early publicity creates hype. (Ex: 2021 Bubble)
3. Trough of Disillusionment: Early projects fail to deliver on promises and the public loses interest. I suspect NFTs are somewhere around this trough of disillusionment now.
4. Enlightenment slope: The tech shows successful use cases.
5. Plateau of Productivity: Mainstream adoption has arrived and broader market applications have proven themselves. Here’s a more detailed visual of the Gartner Hype Cycle from Wikipedia.
In the speculative NFT bubble of 2021, @beeple sold Everydays: the First 5000 Days for $69 MILLION in 2021's NFT bubble.
@nbatopshot sold millions in video collectibles.
This is when expectations peaked.
Let's examine NFTs' real-world applications.
Watch this video if you're unfamiliar with NFTs.
Online Art
Most people think NFTs are rich people buying worthless JPEGs and MP4s.
Digital artwork and collectibles are revolutionary for creators and enthusiasts.
NFT Profile Pictures
You might also have seen NFT profile pictures on Twitter.
My profile picture is an NFT I coined with @skogards factoria app, which helps me avoid bogus accounts.
Profile pictures are a good beginning point because they're unique and clearly yours.
NFTs are a way to represent proof-of-ownership. It’s easier to prove ownership of digital assets than physical assets, which is why artwork and pfps are the first use cases.
They can do much more.
NFTs can represent anything with a unique owner and digital ownership certificate. Domains and usernames.
Usernames & Domains
@unstoppableweb, @ensdomains, @rarible sell NFT domains.
NFT domains are transferable, which is a benefit.
Godaddy and other web2 providers have difficult-to-transfer domains. Domains are often leased instead of purchased.
Tickets
NFTs can also represent concert tickets and event passes.
There's a limited number, and entry requires proof.
NFTs can eliminate the problem of forgery and make it easy to verify authenticity and ownership.
NFT tickets can be traded on the secondary market, which allows for:
marketplaces that are uniform and offer the seller and buyer security (currently, tickets are traded on inefficient markets like FB & craigslist)
unbiased pricing
Payment of royalties to the creator
4. Historical ticket ownership data implies performers can airdrop future passes, discounts, etc.
5. NFT passes can be a fandom badge.
The $30B+ online tickets business is increasing fast.
NFT-based ticketing projects:
Gaming Assets
NFTs also help in-game assets.
Imagine someone spending five years collecting a rare in-game blade, then outgrowing or quitting the game. Gamers value that collectible.
The gaming industry is expected to make $200 BILLION in revenue this year, a significant portion of which comes from in-game purchases.
Royalties on secondary market trading of gaming assets encourage gaming businesses to develop NFT-based ecosystems.
Digital assets are the start. On-chain NFTs can represent real-world assets effectively.
Real estate has a unique owner and requires ownership confirmation.
Real Estate
Tokenizing property has many benefits.
1. Can be fractionalized to increase access, liquidity
2. Can be collateralized to increase capital efficiency and access to loans backed by an on-chain asset
3. Allows investors to diversify or make bets on specific neighborhoods, towns or cities +++
I've written about this thought exercise before.
I made an animated video explaining this.
We've just explored NFTs for transferable assets. But what about non-transferrable NFTs?
SBTs are Soul-Bound Tokens. Vitalik Buterin (Ethereum co-founder) blogged about this.
NFTs are basically verifiable digital certificates.
Diplomas & Degrees
That fits Degrees & Diplomas. These shouldn't be marketable, thus they can be non-transferable SBTs.
Anyone can verify the legitimacy of on-chain credentials, degrees, abilities, and achievements.
The same goes for other awards.
For example, LinkedIn could give you a verified checkmark for your degree or skills.
Authenticity Protection
NFTs can also safeguard against counterfeiting.
Counterfeiting is the largest criminal enterprise in the world, estimated to be $2 TRILLION a year and growing.
Anti-counterfeit tech is valuable.
This is one of @ORIGYNTech's projects.
Identity
Identity theft/verification is another real-world problem NFTs can handle.
In the US, 15 million+ citizens face identity theft every year, suffering damages of over $50 billion a year.
This isn't surprising considering all you need for US identity theft is a 9-digit number handed around in emails, documents, on the phone, etc.
Identity NFTs can fix this.
NFTs are one-of-a-kind and unforgeable.
NFTs offer a universal standard.
NFTs are simple to verify.
SBTs, or non-transferrable NFTs, are tied to a particular wallet.
In the event of wallet loss or theft, NFTs may be revoked.
This could be one of the biggest use cases for NFTs.
Imagine a global identity standard that is standardized across countries, cannot be forged or stolen, is digital, easy to verify, and protects your private details.
Since your identity is more than your government ID, you may have many NFTs.
@0xPolygon and @civickey are developing on-chain identity.
Memberships
NFTs can authenticate digital and physical memberships.
Voting
NFT IDs can verify votes.
If you remember 2020, you'll know why this is an issue.
Online voting's ease can boost turnout.
Informational property
NFTs can protect IP.
This can earn creators royalties.
NFTs have 2 important properties:
Verifiability IP ownership is unambiguously stated and publicly verified.
Platforms that enable authors to receive royalties on their IP can enter the market thanks to standardization.
Content Rights
Monetization without copyrighting = more opportunities for everyone.
This works well with the music.
Spotify and Apple Music pay creators very little.
Crowdfunding
Creators can crowdfund with NFTs.
NFTs can represent future royalties for investors.
This is particularly useful for fields where people who are not in the top 1% can’t make money. (Example: Professional sports players)
Mirror.xyz allows blog-based crowdfunding.
Financial NFTs
This introduces Financial NFTs (fNFTs). Unique financial contracts abound.
Examples:
a person's collection of assets (unique portfolio)
A loan contract that has been partially repaid with a lender
temporal tokens (ex: veCRV)
Legal Agreements
Not just financial contracts.
NFT can represent any legal contract or document.
Messages & Emails
What about other agreements? Verbal agreements through emails and messages are likewise unique, but they're easily lost and fabricated.
Health Records
Medical records or prescriptions are another types of documentation that has to be verified but isn't.
Medical NFT examples:
Immunization records
Covid test outcomes
Prescriptions
health issues that may affect one's identity
Observations made via health sensors
Existing systems of proof by paper / PDF have photoshop-risk.
I tried to include most use scenarios, but this is just the beginning.
NFTs have many innovative uses.
For example: @ShaanVP minted an NFT called “5 Minutes of Fame” 👇
Here are 2 Twitter threads about NFTs:
This piece of gold by @chriscantino
2. This conversation between @punk6529 and @RaoulGMI on @RealVision“The World According to @punk6529”
If you're wondering why NFTs are better than web2 databases for these use scenarios, see this Twitter thread I wrote:
If you liked this, please share it.
Dmytro Spilka
3 years ago
Why NFTs Have a Bright Future Away from Collectible Art After Punks and Apes
After a crazy second half of 2021 and significant trade volumes into 2022, the market for NFT artworks like Bored Ape Yacht Club, CryptoPunks, and Pudgy Penguins has begun a sharp collapse as market downturns hit token values.
DappRadar data shows NFT monthly sales have fallen below $1 billion since June 2021. OpenSea, the world's largest NFT exchange, has seen sales volume decline 75% since May and is trading like July 2021.
Prices of popular non-fungible tokens have also decreased. Bored Ape Yacht Club (BAYC) has witnessed volume and sales drop 63% and 15%, respectively, in the past month.
BeInCrypto analysis shows market decline. May 2022 cryptocurrency marketplace volume was $4 billion, according to a news platform. This is a sharp drop from April's $7.18 billion.
OpenSea, a big marketplace, contributed $2.6 billion, while LooksRare, Magic Eden, and Solanart also contributed.
NFT markets are digital platforms for buying and selling tokens, similar stock trading platforms. Although some of the world's largest exchanges offer NFT wallets, most users store their NFTs on their favorite marketplaces.
In January 2022, overall NFT sales volume was $16.57 billion, with LooksRare contributing $11.1 billion. May 2022's volume was $12.57 less than January, a 75% drop, and June's is expected to be considerably smaller.
A World Based on Utility
Despite declines in NFT trading volumes, not all investors are negative on NFTs. Although there are uncertainties about the sustainability of NFT-based art collections, there are fewer reservations about utility-based tokens and their significance in technology's future.
In June, business CEO Christof Straub said NFTs may help artists monetize unreleased content, resuscitate catalogs, establish deeper fan connections, and make processes more efficient through technology.
We all know NFTs can't be JPEGs. Straub noted that NFT music rights can offer more equitable rewards to musicians.
Music NFTs are here to stay if they have real value, solve real problems, are trusted and lawful, and have fair and sustainable business models.
NFTs can transform numerous industries, including music. Market opinion is shifting towards tokens with more utility than the social media artworks we're used to seeing.
While the major NFT names remain dominant in terms of volume, new utility-based initiatives are emerging as top 20 collections.
Otherdeed, Sorare, and NBA Top Shot are NFT-based games that rank above Bored Ape Yacht Club and Cryptopunks.
Users can switch video NFTs of basketball players in NBA Top Shot. Similar efforts are emerging in the non-fungible landscape.
Sorare shows how NFTs can support a new way of playing fantasy football, where participants buy and swap trading cards to create a 5-player team that wins rewards based on real-life performances.
Sorare raised 579.7 million in one of Europe's largest Series B financing deals in September 2021. Recently, the platform revealed plans to expand into Major League Baseball.
Strong growth indications suggest a promising future for NFTs. The value of art-based collections like BAYC and CryptoPunks may be questioned as markets become diluted by new limited collections, but the potential for NFTs to become intrinsically linked to tangible utility like online gaming, music and art, and even corporate reward schemes shows the industry has a bright future.
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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.

Micah Daigle
3 years ago
Facebook is going away. Here are two explanations for why it hasn't been replaced yet.
And tips for anyone trying.
We see the same story every few years.
BREAKING NEWS: [Platform X] launched a social network. With Facebook's reputation down, the new startup bets millions will switch.
Despite the excitement surrounding each new platform (Diaspora, Ello, Path, MeWe, Minds, Vero, etc.), no major exodus occurred.
Snapchat and TikTok attracted teens with fresh experiences (ephemeral messaging and rapid-fire videos). These features aren't Facebook, even if Facebook replicated them.
Facebook's core is simple: you publish items (typically text/images) and your friends (generally people you know IRL) can discuss them.
It's cool. Sometimes I don't want to, but sh*t. I like it.
Because, well, I like many folks I've met. I enjoy keeping in touch with them and their banter.
I dislike Facebook's corporation. I've been cautiously optimistic whenever a Facebook-killer surfaced.
None succeeded.
Why? Two causes, I think:
People couldn't switch quickly enough, which is reason #1
Your buddies make a social network social.
Facebook started in self-contained communities (college campuses) then grew outward. But a new platform can't.
If we're expected to leave Facebook, we want to know that most of our friends will too.
Most Facebook-killers had bottlenecks. You have to waitlist or jump through hoops (e.g. setting up a server).
Same outcome. Upload. Chirp.
After a week or two of silence, individuals returned to Facebook.
Reason #2: The fundamental experience was different.
Even when many of our friends joined in the first few weeks, it wasn't the same.
There were missing features or a different UX.
Want to reply with a meme? No photos in comments yet. (Trying!)
Want to tag a friend? Nope, sorry. 2019!
Want your friends to see your post? You must post to all your friends' servers. Good luck!
It's difficult to introduce a platform with 100% of the same features as one that's been there for 20 years, yet customers want a core experience.
If you can't, they'll depart.
The causes that led to the causes
Having worked on software teams for 14+ years, I'm not surprised by these challenges. They are a natural development of a few tech sector meta-problems:
Lean startup methodology
Silicon Valley worships lean startup. It's a way of developing software that involves testing a stripped-down version with a limited number of people before selecting what to build.
Billion people use Facebook's functions. They aren't tested. It must work right away*
*This may seem weird to software people, but it's how non-software works! You can't sell a car without wheels.
2. Creativity
Startup entrepreneurs build new things, not copies. I understand. Reinventing the wheel is boring.
We know what works. Different experiences raise adoption friction. Once millions have transferred, more features (and a friendlier UX) can be implemented.
3. Cost scaling
True. Building a product that can sustain hundreds of millions of users in weeks is expensive and complex.
Your lifeboats must have the same capacity as the ship you're evacuating. It's required.
4. Pure ideologies
People who work on Facebook-alternatives are (understandably) critical of Facebook.
They build an open-source, fully-distributed, data-portable, interface-customizable, offline-capable, censorship-proof platform.
Prioritizing these aims can prevent replicating the straightforward experience users expect. Github, not Facebook, is for techies only.
What about the business plan, though?
Facebook-killer attempts have followed three models.
Utilize VC funding to increase your user base, then monetize them later. (If you do this, you won't kill Facebook; instead, Facebook will become you.)
Users must pay to utilize it. (This causes a huge bottleneck and slows the required quick expansion, preventing it from seeming like a true social network.)
Make it a volunteer-run, open-source endeavor that is free. (This typically denotes that something is cumbersome, difficult to operate, and is only for techies.)
Wikipedia is a fourth way.
Wikipedia is one of the most popular websites and a charity. No ads. Donations support them.
A Facebook-killer managed by a good team may gather millions (from affluent contributors and the crowd) for their initial phase of development. Then it might sustain on regular donations, ethical transactions (e.g. fees on commerce, business sites, etc.), and government grants/subsidies (since it would essentially be a public utility).
When you're not aiming to make investors rich, it's remarkable how little money you need.
If you want to build a Facebook competitor, follow these tips:
Drop the lean startup philosophy. Wait until you have a finished product before launching. Build it, thoroughly test it for bugs, and then release it.
Delay innovating. Wait till millions of people have switched before introducing your great new features. Make it nearly identical for now.
Spend money climbing. Make sure that guests can arrive as soon as they are invited. Never keep them waiting. Make things easy for them.
Make it accessible to all. Even if doing so renders it less philosophically pure, it shouldn't require technical expertise to utilize.
Constitute a nonprofit. Additionally, develop community ownership structures. Profit maximization is not the only strategy for preserving valued assets.
Last thoughts
Nobody has killed Facebook, but Facebook is killing itself.
The startup is burying the newsfeed to become a TikTok clone. Meta itself seems to be ditching the platform for the metaverse.
I wish I was happy, but I'm not. I miss (understandably) removed friends' postings and remarks. It could be a ghost town in a few years. My dance moves aren't TikTok-worthy.
Who will lead? It's time to develop a social network for the people.
Greetings if you're working on it. I'm not a company founder, but I like to help hard-working folks.

Laura Sanders
3 years ago
Xenobots, tiny living machines, can duplicate themselves.
Strange and complex behavior of frog cell blobs
A xenobot “parent,” shaped like a hungry Pac-Man (shown in red false color), created an “offspring” xenobot (green sphere) by gathering loose frog cells in its opening.
Tiny “living machines” made of frog cells can make copies of themselves. This newly discovered renewal mechanism may help create self-renewing biological machines.
According to Kirstin Petersen, an electrical and computer engineer at Cornell University who studies groups of robots, “this is an extremely exciting breakthrough.” She says self-replicating robots are a big step toward human-free systems.
Researchers described the behavior of xenobots earlier this year (SN: 3/31/21). Small clumps of skin stem cells from frog embryos knitted themselves into small spheres and started moving. Cilia, or cellular extensions, powered the xenobots around their lab dishes.
The findings are published in the Proceedings of the National Academy of Sciences on Dec. 7. The xenobots can gather loose frog cells into spheres, which then form xenobots.
The researchers call this type of movement-induced reproduction kinematic self-replication. The study's coauthor, Douglas Blackiston of Tufts University in Medford, Massachusetts, and Harvard University, says this is typical. For example, sexual reproduction requires parental sperm and egg cells. Sometimes cells split or budded off from a parent.
“This is unique,” Blackiston says. These xenobots “find loose parts in the environment and cobble them together.” This second generation of xenobots can move like their parents, Blackiston says.
The researchers discovered that spheroid xenobots could only produce one more generation before dying out. The original xenobots' shape was predicted by an artificial intelligence program, allowing for four generations of replication.
A C shape, like an openmouthed Pac-Man, was predicted to be a more efficient progenitor. When improved xenobots were let loose in a dish, they began scooping up loose cells into their gaping “mouths,” forming more sphere-shaped bots (see image below). As many as 50 cells clumped together in the opening of a parent to form a mobile offspring. A xenobot is made up of 4,000–6,000 frog cells.
Petersen likes the Xenobots' small size. “The fact that they were able to do this at such a small scale just makes it even better,” she says. Miniature xenobots could sculpt tissues for implantation or deliver therapeutics inside the body.
Beyond the xenobots' potential jobs, the research advances an important science, says study coauthor and Tufts developmental biologist Michael Levin. The science of anticipating and controlling the outcomes of complex systems, he says.
“No one could have predicted this,” Levin says. “They regularly surprise us.” Researchers can use xenobots to test the unexpected. “This is about advancing the science of being less surprised,” Levin says.
