Lovelace Worldis in the Non Fungible Tokens Industry

Lovelace World

Hey there, fellow truth-seekers! Are you tired of crossing your fingers, avoiding black cats, and sacrificing your lunch to appease ancient superstitions? Well, fret no more! It's time to dive into the enchanting world of technicality and wave goodbye to those old wives' tales. Buckle up, because we're about to embark on a hilarious journey to discover why being technical is the potion that'll bring joy, success, and a sprinkle of unicorn dust into your life. Understanding Technicality: Picture this: superstition is like believing in a horde of invisible leprechauns plotting against you, while technicality is like putting on a superhero cape, armed with a laser-guided truth-seeking missile. It's about being rational and logical, my friends! While others are chasing rainbows and knocking on wood, you'll be making informed decisions like a boss. Breaking Free from Superstition: Let's be real here: superstition has a few screws loose. Avoiding sidewalk cracks because you don't want to break your mother's back? It's time to break free from these chains of absurdity and embrace the freedom of critical thinking. Say goodbye to walking like a contortionist just to avoid a few cracks in the pavement! If you are interested in reading more of my articles and staying in touch with me then consider subscribing to my Hackernoon newsletter. You can subscribe by hitting that subscribe button below. The Benefits of a Technical Mindset: Objective Decision-Making: When you're technical, you'll have the power of reason on your side. You won't need a rabbit's foot to make decisions. Instead, you'll rely on evidence, facts, and good ol' common sense. No more flipping coins to choose your next career move—it's time to flip the switch to logic! Problem-Solving Prowess: Being technical is like having a supercharged brain. You'll possess the ability to analyze problems, break them down into bite-sized pieces, and zap them away with your intellect. It's like being MacGyver, but with fewer paperclips and more brain power. Who needs a lucky charm when you've got your very own genius mind? Resilience and Adaptability: Life is like a magical unicorn roller coaster—full of unexpected twists and turns. With a technical mindset, you'll be equipped with the skills to adapt and thrive in a world of constant change. You won't be afraid of black cats crossing your path because you'll know that their fur color has zero impact on your success. Avoiding Pitfalls: Superstition is a sneaky devil that lures you into its traps. But fear not! A technical mindset will shield you from falling into those pits of deception. You'll be equipped with the armor of skepticism, able to spot frauds and scams from a mile away. No more falling prey to enchanted love potions or mystical get-rich-quick schemes! Thriving in a Technological Era: Ah, technology—the wizardry of our time! Being technical isn't just about embracing rationality; it's about riding the technological wave to success. Think of it as Gandalf summoning his digital army. In this digital age, technical skills are like the golden ticket to the chocolate factory of career opportunities. Embrace technology, and you'll be one step closer to becoming a tech-savvy wizard. Cultivating a Technical Mindset: So, how does one transform into a technical wizard, you ask? It's not as complicated as deciphering ancient scrolls, I promise! First, embrace your inner curiosity. Let it flow through your veins like an unstoppable force. Second, practice critical thinking like it's an Olympic sport. Solve puzzles, ask questions, and challenge the status quo. Lastly, seek knowledge like Indiana Jones hunting for ancient artifacts. Read, learn, and expand your mental horizons. Real-Life Examples: Remember that time when Nikola Tesla casually invented alternating current while sipping tea? That's the power of a technical mindset! Or how about Ada Lovelace, who wrote the world's first computer program? These remarkable individuals didn't rely on rabbit's feet or four-leaf clovers. They trusted in their technical prowess and went on to change the world. You can do it too! If you are interested in reading more of my content, then I recommend subscribing to my Hackernoon newsletter to stay in touch with me. Just click the . subscribe button

Unlock the Magic of a Technical Mindset: Your Key to Success in Life and Jobs!

And all the Women in Tech That Got Us There. When we think of great advances in tech, names like Elon Musk (space Tesla, anyone?) or Bill Gates spring to mind. Today though, we’re going to switch gears and take a look at tech from a more feminine perspective. From the 19th century all the way to day, woman have always been a huge part of the tech world, though their voices have not always been heard. Considered by many to be the world’s first computer programmer, Ada Lovelace theorized the looping process used by computer programs today. Born in 1851, Lovelace’s education was exclusive tutoring in mathematics, giving her a unique perspective to theoretical computing. A woman ahead of her time, she envisioned a computer being able to produce words, pictures, music, and of course, numbers- much like what we know today. Today, tech is taking on a distinctly new landscape: cryptocurrency and blockchain. A new frontier for computing, woman like Iliana Oris Valiente, founder of ColliderX, and Meltem Demirors, VP at Digital Currency Group, are working hard to not only advance tech developments but also to cultivate a positive environment for the future of women in tech. This Women’s History Month, let’s remember the women that shaped technology as we know it today. From theoretical computing, to computer algorithms, to blockchain, these women helped build the technology empire we know today, and they show no signs of slowing down. Take a look at this infographic for more about the , and why you should know them by name. iconic women of computing and crypto

A Look at the Women of Crypto

The world’s first computer programmer could also be described as a pioneer in B2B technology marketing. Her wisdom and discerning insights into the potential of technology not only advanced science but also serve as a guiding light today for those of us tasked with articulating to others tech’s potential. Lovelace was an aristocrat, fortunate to study mathematics in the early 19th Century. Her mother, also a mathematician, believed what we might call a STEM education could prevent Ada from following in the footsteps of her father, the sensual Romantic poet Lord Byron. Lovelace began studying Charles Babbage’s prototype digital computers in the 1830s. And don’t get thrown off to that reference to digital. Today “digital” suggests electrons moving around. But here digital means reducing the world to ones and zeroes to better compute what’s going on in it, rather than figuring things out via analogs. Read Walter Isaacson’s The Innovators, for an excellent history of the people who advanced computing for the details. Here’s where the marketing comes in What cemented Lovelace’s place in history in 1843 was her translation and ridiculously extensive annotation of an Italian mathematician’s article on Babbage’s Analytical Engine. Despite her mother’s efforts, Lovelace inherited her father’s gifts with the pen. Her science was like verse. “The Analytical Engine weaves algebraic patterns just as the Jacquard loom weaves flowers and leaves,” she wrote in one of her notes in the article. The substance of her thoughts was even more powerful. Her annotations envisioned applications of the Analytical Engine that went beyond basic calculations, creating the first known computer program with an algorithm that produced Bernoulli numbers. Her contributions remind us of the importance of an often-overlooked tool in tech: human perspective. Rather than focusing solely on the nuts and bolts of a remarkable innovation, she considered its applications. She perceived new worlds where the benefits of technology could be brought to fruition. These insights are extremely important for the future of enterprise AI. Advancements in AI, machine learning, and other technologies have promised ambitious but too-often-unrealized advancements for organizations in many industries. Many of those advancements have yet to be achieved not because AI is incapable of performing them. Rather, too few companies have created AI-enabled applications that busy professionals can integrate into their workflows without significant training, teams of data scientists or other accommodations. Until the hype cycle around generative AI achieved liftoff, selling AI in a general sense wasn’t really moving the industry forward. In other words. business solutions that AI makes possible was the name of the game. Generative AI has changed that game, but its utility will still be expressed most tangibly through business solutions. And it will be what business solutions can and can’t do that will ground the conversation. You might accuse me of sidestepping consumer applications, and you would be right. But let me save that for a future piece. First tech white paper? Lovelace foresaw the distinction. When she wrote her groundbreaking notes, Babbage and his colleagues were hoping that the British government or others would finance the completion of his complicated machines. Unfortunately, they never received it, though researchers have been seeking to replicate and finalize his inventions in the 150 years since Babbage died thanks in part to Lovelace’s notes. And today marketers might call those notes a white paper, or a document that aims to both inform readers – usually prospective customers or partners – about a complicated technical subject and persuade them of its utility in solving problems. It’s a translation and explanation of a solution, one might say. While Babbage and his team were concentrated on the nuts and bolts of their engines, she was busy showcasing their work to the rest of the world and describing its material benefits to potential users. She was on the frontlines. That’s where B2B marketers in enterprise AI need to devote their attention today. When the sugar high of generative AI fades, it will still be delivering understated but significant value in business operations in a wide variety of industries today, from clinical trials for pharmaceutical development, to consumer lending, to manufacturing. Much of that value will originate in incremental advances with AI that don’t garner headlines because it may be more on the user interface side. The momentum is clear, however. AI is at the center of the digital transformations changing the global economy today. B2B marketers should take a page from Lovelace and clarify just how big it can be, and what stands in the way.

Ada Lovelace Was a Marketing Genius, Too

Especially when over 85% of businesses will not survive up to 10 years "Failure is the mother of success." (Ancient Chinese proverb) The Chinese proverb, 失败是成功之母 ( ), defined failure as an . shī bài shì chéng gōng zhī mǔ; in Chinese translation essential process to success This is why in addressing high business shutdown rate, is building an affordable business intelligence to help early stage startup founders , , , and to build businesses with strong competitive edge. Flipidea reduce costly mistakes make prudent strategies compete innovatively fundraise strategically : According to Flipidea’s recent study on 8,377 inactive companies from around the world, . Show me the numbers 89.2% of companies did not survive up to 10 years Within 3 years duration, 37.1% of companies shuttered In 3 to 5 years duration, 26.5% of companies shuttered In 5 to 7 years duration, 14.4% of companies shuttered In 7 to 10 years duration, 11.2% of companies shuttered The top 5 reasons for shutdown: Strong competition Poor business model Lack of funds No product-market fit Failed fundraising Postmortem analysis was conducted on 1,026 shuttered companies with reasons for shutdown and a total of 127 unique reasons for shutdown were identified. : Through its research, the company observed that most new companies failed to identify their problem-market fit before they validated their business to achieve the desired product-market fit, and as a result, they ended up in a highly saturated and competitive market. Why it matters Its postmortem analysis showed that strong competition is the number one reason for shutdown, highlighting the importance of market validation - - in building competitive differentiation. by learning what not to do and focus on doing what is right “Companies often fail because founders and investors ,” says Flipidea Co-founder and CEO Paul Lee. “Not every great idea is business worthy because business is simply what your target market is willing to buy what you’re selling them.” neglect to look before they leap “We all know that ideas are cheap and execution is expensive. But what’s more expensive? The execution of untested ideas.” (Paul from www.flipidea.co) : When founders want to build a business with strong competitive edge but do not have the right knowledge and affordable tools, Flipidea aims to help founders analyze and validate the market at minimal cost, so founders can make data-informed decisions to improve and innovate their business. What can be done Flipidea’s postmortem data also showed that most inexperienced founders lack the know-how and affordable tools to effectively validate the market and conduct competitors’ analysis. “At its core, business is more science than art because its many structural components and processes are methodical, measurable, experimental, and repeatable,” says Lee. “Founders, even investors, should identify avoidable patterns from past experiences to avoid hindsight bias. Similar to how experiments are tested for desired outcomes.” Got an intuitive business idea? We help reduce risk of business failure. , especially in the quest for innovation, in the fields of entrepreneurship, engineering, and science. Failure is the process of advancement In science, . failure is part of the process Many renown scientists such as Thomas Edison, Albert Einstein, Robert Goddard, Marie Curie, Ada Lovelace, Alice Augusta Ball, to name a few, are testimonies to this scientific truth who went through repeated and painful failures before they made their scientific breakthroughs. “Embracing failure as information or data for innovative problem-solving helps us to cope with the fear of failure because it is the very essence of empirical learning,” says Lee. “We can unpack failure like an experiment and learn from it through the scientific method - .” formulating a hypothesis, testing it, measuring it, learning from it, and reiterating it This explains why Flipidea’s solutions such as postmortem analysis, competitive analysis, portfolio analysis, co-investors analysis, and idea validation are powered by its extensive database of business failures, historical, and market data to foster innovation. "Failure is a learning experience, and the guy who has never failed has never done anything." (Wilson Greatbatch, The Implantable Cardiac Pacemaker) : Although the bootstrapping company is still building and consolidating its business intelligence features, with its data science systems showing potential, they are expecting to release new features on the 29 December 2021. What’s next : Founders can analyze, build, and showcase their fundraising pitch decks to investors, which will be protected and investors need to request for access to view them. Pitch deck analysis ( ) for founders How you benefit: Evidence-based assessment and feedback to improve viability. Problem it solves: Confidential and data-driven evaluation of pitch decks. Why it matters: Powered by industry comparison benchmarks, real market data, and proven frameworks to evaluate fundability. Be the first to try Flipidea’s new features and join our waiting list. : Investors can source for deals according to funding stages, and upon investors’ approval, founders can email to pitch them. Deals sourcing ( ) for investors How you benefit: Access diverse and recommended fundable opportunities. Problem it solves: Increase deal flow velocity and volume from wider geography. Why it matters: Leverage smart-matching to optimize deal sourcing. : The company is offering its Basic Plan at 50% off, only available for annual billing, from now till 3 January 2022 (GMT +8). Promo code: Flipidea3xFestive. Year end special . Claim your 50% discount now Written by , Co-founder & CEO, Flipidea Paul Lee , Business Research Analyst, Flipidea Elina Kamaluddin , Business Research Analyst, Flipidea Sharifah Nadzirah , Associate AI Researcher, Flipidea Nur ‘Aqilah Shaharol , Co-founder & Chief Researcher, Flipidea D.T.C. Lai Last edited on 21 December 2021. Also published at Viewpoints.flipidea.co

After Analyzing Over 8k Companies Worldwide, We Learned that Startup Failure is a Feature, Not a Bug

I have no idea how to become the best programmer in the world. So I figured out the best way to get ahead is to learn from the all time greatest programmers and get responses from some amazing engineers too. Let’s get cracking. 1. Lessons from Dennis Ritchie, the Man Behind the UNIX and C UNIX is basically a simple operating system, but you have to be a genius to understand the simplicity — Dennis Ritchie Dennis Ritchie, Techtricksworld Back in the days before you could go to college and get a degree in computer programming, Dennis Ritchie managed to get a job working at the Massachusetts Institute of Technology (MIT). Computer Labs were not as picky as they now are, and welcomed practically anyone with the patience to help them work on their room-sized computers. For someone who started out as an industry outsider, creating both UNIX and the C language — two of the most widely used technologies in computer history — is a big deal. A very big deal. Here are some of Dennis Ritchie’s accomplishments: Dennis Ritchie created the C programming language, and co-created the UNIX operating system with his buddy, Ken Thompson. In 1983 he was a recipient of the Turing Award from the Association of Computing Machinery(ACM) In 1990, both Ritchie and Thompson received the from the (IEEE) IEEE Richard W. Hamming Medal Institute of Electrical and Electronics Engineers In 1997 he was made a fellow of the Computer History Museum He received the National Medal of Technology from President Clinton in 1999 So how would you go about accomplishing all that? And more to the point, how did Dennis Ritchie even learn to write software? Dennis Ritchie — popularly called the “Father of the C programming language” — was said to be a sweet, kind, unassuming man — and a complete geek! But he didn’t start out as a geek. Ritchie was born in New York and grew up in the Garden city, New Jersey. He had a stable childhood, and did well academically. He went on to study at Harvard University, where he studied science and graduated with a bachelor’s degree in Physics. So when did computers come into Ritchie’s Life? POINT 1: If you look to be good at writing great software, you’re going to have to stay curious. I am neither clever nor especially gifted. I am only very, very curious — Albert Einstein Curiosity fuels the hunger for knowledge. And knowledge my dear, rules the world. While a student, Ritchie somehow attended a lecture on how the worked. Univac I The ( ) was the first commercial computer produced in the United States. UNIVAC I Universal Automated Computer I Below is what it looked like: wikipedia Seriously, what kind of curiosity makes a person seat and actually enjoy a lecture on how that thing works? Apparently, the kind that makes a great programmer. After that encounter, Ritchie went on to further study how the computer really worked. Curiosity kills the cat 🐱. We all know that, but you’re not a Cat. POINT 2: I know you’ve heard this before, but Build stuffs. Lots of stuffs. Instead of focusing on specific projects, I wanted to be around people with a lot of experience and ideas. So I started working on various projects to learn my way around the profession.” — Dennis Ritchie Make building a lot of projects the product of your curiosity. Translate that curiosity into building different projects — and like Ritchie, this will help you learn your way around the profession. POINT 3: Hang Around Those you Consider Better and More Experienced. The obvious reason why you should do this is, you’ll be learning at a much faster pace and wouldn’t get too comfortable with your current knowledge. This was something else Dennis Ritchie was said to do well. If you can’t get physically close to the people you consider better and more experienced, the internet is your friend. Follow them on channels you feel comfortable with. Read their blog posts. Watch their videos. Listen to their podcasts. youtube Just “stay” around them. POINT 4: Solve Problems. “It’s not the actual programming that’s interesting. But it’s what you can accomplish with the end results that are important.” — Dennis Ritchie Dennis Ritchie lived at a time when computers filled a room, and so did many more. But Ritchie knew that smaller computers were being developed, and they did not have easy to use operating systems, so he embarked on a project to build one. This is how Ritchie viewed programming in general. It was about what could be accomplished. The problems that could be solved, and the effect they’d have on people. If a problem bugs you so much, don’t ignore it. If you think it’s being overlooked by many, solve it. Build something. Just do it. Get curious. Study the concepts. Ask for help. You should not look back until you have solved the problem. When something is important enough, you do it even if the odds are not in your favor — Elon Musk. Here are some Examples : , the technology for building desktop applications with Javascript came to life because a part of the Github team wanted to build an hackable editor with web technologies. Electron JS , the predicable state container for Javascript apps was built by because he wanted to create a state management library with minimal API but completely predictable behavior — that’s the way he puts it. Redux Dan Abramov and a couple others built the platform to solve the problem of teaching web technologies in an open source community. Quincy Larson Freecodecamp They saw a problem, and went on to solve it. Key takeaways from the Dennis Ritchie, the Father of the C Programming Language Stay Curious, and keep fueling the fire of knowledge. We can never know all. Understand the fundamentals. The master of the basics, is the true master of the skill. Solve problems. If you think something can be done differently, and should be done, just do it. You’ll get better faster, and better lives while at it Build lots of different projects Hang around people with more expertise, experience and ideas. You can’t trade this for anything else. 2. Lessons from Linus Torvalds, the Man Behind the Linux Kernel OS Linus Torvalds, Softpedia Named by Time magazine as the ‘one of the most influential people in the world, is the creative genius behind the Linux kernel operating system. Linus Torvalds In 1998, he was a recipient of the Electronic Frontier Foundation(EFF) Pioneer Award. In 1999, he was given the title of ‘one of the top 100 innovators, under the age of 35, in the world’ by MIT Technology Review TR100. In 2000, he was the recipient of the Lovelace Medal, which was conferred by the British Computer Society In 2008, he became an inductee into the Hall of Fellows of the Computer History Museum In 2012, he was inducted into the Internet Hall of Fame. In 2012, he was also one of the recipients of the Millennium Technology Prize. Now, that’s worth some cool ride. Linus Torvalds’ license plate. Photo: Jon Snyder/Wired Born in , 1969, and to a family of journalists, Linus says his childhood was nothing very special. Helsinki Influenced largely by his maternal grandfather, Linus wrote his first programs at 10, or technically, 12. He helped his grandfather type in his programs, and until age 12 did he start modifying them and writing his own programs. If being a self taught programmer means teaching yourself to program, regardless of some basic rudimentary computer classes, Linus is equally a self-taught programmer. According to him, “there were programming classes in high school at the time, but they were pretty basic and rudimentary” Point 5: A formal Computer science education is great, but don’t let that stop you. “Computer science education cannot make anybody an expert programmer any more than studying brushes and pigment can make somebody an expert painter.” - Eric Raymond While growing up, Linus Torvalds found it interesting to write games, and he was doing machine code. He didn’t have access to an assembler, so he did all the assembly on paper and wrote them as binary. That’s pretty . badass What’s even more interesting is that everyone in his family (other than those from his maternal side) were journalists. He was the black sheep. In his interview with the Computer History Museum, he says, “I was very much a geek. I stayed inside and read or programmed. And quite frankly, I still read and sit in front of a computer. It’s my bobby” POINT 6: Love What You do. Not Just the Money and Fame it Brings. Most good programmers do programming not because they expect to get paid or get adulation by the public, but because it is fun to program — Linus Torvalds I must state that, many times the love for programming doesn't come when you just start out. For many people, it is as an offshoot of mastering their craft. You learn, make mistakes, build stuffs, see yourself get good, and you just totally love what you do then. Even with those who start out with love, their love is seen to grow even more as they master their craft. If you love programming but don’t seem to be improving, don’t give up. Most persons wore the same shoes — and in bigger sizes ! POINT 7: Be comfortable starting small — but grow. “I just want to build my own Operating system” — Linus Torvalds??? That’s NOT how the story goes. The Linux project didn't start out as an adventure to build an operating system. The details of it may bore you. But here’s the important bit. Linus ordered a , essentially a UNIX-like computer Operating System (OS). It was first released in 1987, with its complete source code made available to universities for study in courses and research. MINIX Linus played around the machine, and wrote his programs to boot off the floppy, with no OS. Linus wanted to play with the CPU itself. So, using the OS would have defeated the purpose of his exercise. Down the line, he didn’t find the program he wrote very useful. He then extended his program to the point where it was an operating system Many successful people start small, but make it big. The danger associated with starting big, is that you may fall into the trap of being overwhelmed. Also, it is perfectly okay to NOT know something. Perfectly okay to be an amateur at a new technology, but grow your wings, and master it as quick as possible. POINT 8: You must do the work. Nobody else will do it for you And I had obviously been reading operating system books anyway — Linus Torvalds I am yet to meet a successful man, who does no work. It’s easy to assume that Linus just magically knew how to build an operating system. That’s not true. He had put in the work required. In his interview with the Computer History Museum, he says, he started working on trying to reorganize the program he built so it acted more like a real operating system. And he had obviously been reading operating system books too. Nothing magical. You do have to put in the hours of work required to get good at programming. Key takeaways from Linus Torvalds A computer science education is great, but don’t let that stop you from being great. Keep loving what you do. Keep doing it well, forget the adulation and money, they’ll come later. It is perfectly okay to start small. Just don’t remain there. Be prepared to put in the hours of work needed. Nothing amazing comes cheap Bonus Points From Other Experienced Developers I personally gathered inputs from some experienced software engineers. What do they think about being the best developer you can be? POINT 9: Outwork Everyone Else Trying to be the Best , is being writing software for over 2 decades now. If you’re curious, interviewed him Bill Sourour Quincy Larson here I reached out to him and here is what he said: The basic answer is, to be the best at something you have to outwork everyone else who is also trying to be the best. That means code, read, learn, work at it every day and all the time. — Bill Sourour In Bill’s words, a more interesting question might be, why do you want to be the BEST in THE WORLD? What will that get you? Is that the real goal? How about trying to be the best that YOU CAN BE and not worrying about the rest of the world? It still means working your ass off, but then you will only be competing against yourself. Make your goal every day, to be better than you were yesterday, and you will get very far. POINT 10: Learn to Think About Abstractions and Software Design More Clearly Dave works as a software engineer in the Boston area, and his vast experience is one I’m come to respect over time. These days, he mostly builds frontend UIs with React and authored the book, Dave Ceddia Pure React If you’re curious, here’s his blog I reached out to Dave a couple months back, and the detail in his response baffled me. Here are his thoughts: 1. At the right time, explore the advantages that come from being exposed to multiple programming languages Learning multiple languages exposes you to new ideas and new ways of approaching problems (especially functional languages). Then there are the lower-level ones like C that will teach you to be mindful of memory management and performance. You’ve got to build things, basically. Build lots of things. 2. Explore even more project types Writing UI (User Interface) code is not like writing high-performance data acquisition code, is not like writing OpenGL code, is not like socket programming… So it’s interesting to branch out from one facet of development like frontend/backend stuff into other things, if only just to see what it’s like. 3. Gather a wide range of experience So part of being a good developer to me is having a wide range of experiences. That might just be me though. Everyone will have their own answer for this. But I think it’s useful to know a little bit about everything. I guess I’d call myself a generalist — I love learning new things, and so I’ve done lots of different stuff. Data acquisition code in C++ talking to custom hardware, GUIs in Qt, little games in OpenGL, boring Java and SQL, webapps in Ruby on Rails, little Raspberry Pi projects like a garage door opener… lots of little things. 4. Get great at Automation and Testing continually Along the way, try to get good at automating things. I think a desire for automation has been the driver behind most of the projects I’ve done, but also, a great reason and motivator for learning Linux and the command line. Command line knowledge seems like an ancillary, secondary thing. But I think it’s really important. It changes how you see problems. Things like become a few lines of bash. “oh crap I have to change that variable name across 30 files? nevermind…” Setting up builds becomes less intimidating because all the commands make sense, or at least you see the commonalities between them. 5. Understand Software Design So the hardest thing for me about improving as a developer is the architecture bit. Software design, how to structure your code so it’s reusable and easy to read and easy to modify. Getting great at refactoring and testing consistently. I must admit I am not always great at testing. But TDD_(Test driven development)_ is actually fun, and you should learn and practice it. I think it’s sort of a shortcut/system for getting better at the “design” side of developing software. One of the best books I’ve read about design was by Sandi Metz . You don’t really have to know Ruby very well to get a lot of benefit out of it. It goes through refactoring a bunch of small examples to make them easier to maintain, and she discusses the tradeoffs and reasons behind every change she makes. Practical OO Design in Ruby Conclusion Where do you go from here? Apply these principles and begin your quest to become a better developer. Plus, you should endeavor to deliberately practice too. In his recent Quora Session, , Creator of Ruby on Rails, puts it this way. DHH “It doesn’t help to practice the same lesson 10 times over. You have to constantly seek the edge of your comfort zone. ” — David Hansson, Creator of Ruby on Rails. Good luck, and cheers to being a better developer! Do recommend the article, and drop your comments. Any tips that have helped you personally? Let’s hear it!

How to Become the Best Programmer in the World

You map concepts to optimized numbers TL;DR: Use real-world constants as constants Problems Bijection Violation
Debugging
Premature Optimization
Maintainability
Type Safety
Limited Extensibility Solutions Use descriptive string constants
Use Enums
Create A Polymorphic Hierarchy Context Numeric constants representing real-world concepts lack readability and make your code harder to understand. It's not clear what each number represents. if you need to add more constants in the future or change the order, you'll have to update all occurrences of these numeric constants manually. New values can introduce errors and make maintenance more difficult. Saving attributes as integers to improve the persistence performance or space is a clear signal of Premature Optimization. Sample Code Wrong public const FORMAT_JPG = 1;
public const FORMAT_GIF = 2;
public const FORMAT_PNG = 3; Right public const string FORMAT_JPG = "JPG";
public const string FORMAT_GIF = "GIF";
public const string FORMAT_PNG = "PNG";

// OR

public enum ImageFormat
{
    JPG,
    GIF,
    PNG
} Detection Semi-Automatic You can tell your linters to warn you about this usage, but they can show you some false positives. Tags Readability Level Beginner AI Generation No models create this premature optimization problem when prompted to list constants. AI Detection ChatGPT and Gemini detected this as a mistake. Conclusion After this correction, your code will be cleaner readable, and self-explanatory for debugging. You can read it and It's clear what each constant represents. If you need to add more formats or change the order, you should update the enumeration definition without affecting the rest of the code. IDEs with auto-completion and error checking will give you better support to work with enums. Relations Code Smell 02 - Constants and Magic Numbers Code Smell 110 - Switches With Defaults Code Smell 20 - Premature Optimization More Info How to Get Rid of Annoying IFs Forever Disclaimer Code Smells are my opinion. Credits Photo by Markus Krisetya on Unsplash Forget this world and all its troubles and if possible its multitudinous Charlatans - everything in short but the Enchantress of Numbers. Ada Lovelace Software Engineering Great Quotes This article is part of the CodeSmell Series. How to Find the Stinky Parts of your Code You map concepts to optimized numbers You map concepts to optimized numbers TL;DR: Use real-world constants as constants TL;DR: Use real-world constants as constants Problems Bijection Violation Debugging Premature Optimization Maintainability Type Safety Limited Extensibility Bijection Violation Debugging Premature Optimization Maintainability Type Safety Limited Extensibility Solutions Use descriptive string constants Use Enums Create A Polymorphic Hierarchy Use descriptive string constants Use Enums Create A Polymorphic Hierarchy Polymorphic Context Numeric constants representing real-world concepts lack readability and make your code harder to understand. It's not clear what each number represents. if you need to add more constants in the future or change the order, you'll have to update all occurrences of these numeric constants manually. New values can introduce errors and make maintenance more difficult. Saving attributes as integers to improve the persistence performance or space is a clear signal of Premature Optimization . integers Premature Optimization Sample Code Wrong public const FORMAT_JPG = 1;
public const FORMAT_GIF = 2;
public const FORMAT_PNG = 3; public const FORMAT_JPG = 1;
public const FORMAT_GIF = 2;
public const FORMAT_PNG = 3; Right public const string FORMAT_JPG = "JPG";
public const string FORMAT_GIF = "GIF";
public const string FORMAT_PNG = "PNG";

// OR

public enum ImageFormat
{
    JPG,
    GIF,
    PNG
} public const string FORMAT_JPG = "JPG";
public const string FORMAT_GIF = "GIF";
public const string FORMAT_PNG = "PNG";

// OR

public enum ImageFormat
{
    JPG,
    GIF,
    PNG
} Detection Semi-Automatic Semi-Automatic You can tell your linters to warn you about this usage, but they can show you some false positives. Tags Readability Readability Level Beginner Beginner AI Generation No models create this premature optimization problem when prompted to list constants. AI Detection ChatGPT and Gemini detected this as a mistake. Conclusion After this correction, your code will be cleaner readable, and self-explanatory for debugging. You can read it and It's clear what each constant represents. If you need to add more formats or change the order, you should update the enumeration definition without affecting the rest of the code. IDEs with auto-completion and error checking will give you better support to work with enums. Relations Code Smell 02 - Constants and Magic Numbers Code Smell 02 - Constants and Magic Numbers Code Smell 110 - Switches With Defaults Code Smell 110 - Switches With Defaults Code Smell 20 - Premature Optimization Code Smell 20 - Premature Optimization More Info How to Get Rid of Annoying IFs Forever How to Get Rid of Annoying IFs Forever Disclaimer Code Smells are my opinion . opinion Credits Photo by Markus Krisetya on Unsplash Markus Krisetya Unsplash Forget this world and all its troubles and if possible its multitudinous Charlatans - everything in short but the Enchantress of Numbers. Forget this world and all its troubles and if possible its multitudinous Charlatans - everything in short but the Enchantress of Numbers. Ada Lovelace Ada Lovelace Software Engineering Great Quotes Software Engineering Great Quotes This article is part of the CodeSmell Series. How to Find the Stinky Parts of your Code How to Find the Stinky Parts of your Code

How to Find the Stinky Parts of Your Code: 249 - Constants as Numbers

The AI Odyssey: A Journey Through its History and Philosophical Implications

Your code smells because there are likely many instances where it could be edited or improved. Most of these smells are just hints of something that might be wrong. Therefore, they are not required to be fixed per se… (You should look into it, though.) Previous Code Smells You can find all the previous code smells (Part I - XLV) . here Let's continue... Code Smell 226 - Mixed Priorities Another crashed spacecraft. Another software problem TL;DR: Design and test the software. It is cheaper than the hardware Problems Fault Bijection Unexpected Defects Solutions Create accurate simulations Make software fault-tolerant Context crashed on the moon's surface on August 19, 2023. Luna-25 4 days before India’s soft landed on Moon's south pole. Chandrayaan-3 A revealed that the instructions shared a bus and were not prioritized correctly. forensic analysis Spacecrafts have a of software faults. long history Sample Code Wrong class TaskManager:
    def __init__(self):
        self.tasks = []

    def add_task(self, task, priority):
        self.tasks.append((task, priority))

    def execute_tasks(self):
        # No sorting

        for task, _ in self.tasks:
            task.execute()

class Task:
    def __init__(self, name):
        self.name = name

    def execute(self):
        print(f"Executing task: {self.name}")

task_manager = TaskManager()
highPriorityTask = Task("Slow down")
mediumPriorityTask = Task("Take Photos")
reviveKlaatu = Task("Klaatu barada nikto")

# unsorted
task_manager.add_task(mediumPriorityTask, 2)
task_manager.add_task(highPriorityTask, 1)
task_manager.add_task(reviveKlaatu, 3)

task_manager.execute_tasks() Right class TaskManager:
    def __init__(self):
        self.tasks = []

    def add_task(self, task, priority):
        self.tasks.append((task, priority))

    def execute_tasks(self):
        # Sort tasks by priority (high to low)
        self.tasks.sort(key=lambda x: x[1], reverse=True)

        for task, _ in self.tasks:
            task.execute()

class Task:
    def __init__(self, name):
        self.name = name

    def execute(self):
        print(f"Executing task: {self.name}")

task_manager = TaskManager()
highPriorityTask = Task("Slow down")
mediumPriorityTask = Task("Take Photos")
reviveKlaatu = Task("Klaatu barada nikto")

# unsorted
task_manager.add_task(mediumPriorityTask, 2)
task_manager.add_task(highPriorityTask, 1)
task_manager.add_task(reviveKlaatu, 3)

task_manager.execute_tasks() Detection Manual [x] This is a design smell Tags Reliability Conclusion Create software components and simulate real and not real conditions Relations Code Smell 198 - Hidden Assumptions More Info https://t.me/roscosmos_gk/11053?embedable=true https://asiatimes.com/2023/08/luna-25-crash-lands-russia-china-space-ambitions/?embedable=true Disclaimer Code Smells are my . opinion The Analytical Engine has no pretensions whatever to originate anything. It can do whatever we know how to order it to perform… But it is likely to exert an indirect and reciprocal influence on science itself. Ada Lovelace Software Engineering Great Quotes Code Smell 227 - Cowboy Coding Leave cowboys to Hollywood movies. TL;DR: Write code as a team programmer Problems Readability Unreliable code People Management Issues Lack of coordination Solutions Write professional code. Use declarative non-cryptic names. Context Cowboy coders don't follow best practices. They don't follow team suggestions. Cowboy coding is generally considered an unprofessional and risky approach to software development because it can lead to code that is hard to maintain and prone to errors. Cowboy Programmers are good people; however, . they cannot work in a group Sample Code Wrong # Very simple example 
# Compute the sum of two numbers without any structure or best practices.

num1 = input("Enter the first number: ")
num2 = input("Enter the second number: ")

# WARNNING!!!! Don't remove the line below !!!!!
# (Unpleasant comment)

res = num1 + num2  # (No data type checking or error handling)

print("The sum is: " + result)  # (No validation or formatting)

# (No good names, no functions, no error handling, no testing, 
# no version control, and no structure.) Right def add_numbers():
    try:
        firstAddend = float(input("Enter the first number: "))
        secondAddend = float(input("Enter the second number: "))
        total = firstAddend + secondAddend
        return total
    except ValueError:
        print("Invalid input. Please enter valid numbers.")
        return None

def main():
    total = add_numbers()
    if total is not None:
        print("The sum is: {:.2f}".format(sum))

if __name__ == "__main__":
    main() Detection Manual [x] You can set environmental rules to prevent these coding practices and enforce team building. Exceptions Very small personal projects Tags Declarative Conclusion Software development is teamwork. Relations Code Smell 06 - Too Clever Programmer Code Smell 02 - Constants and Magic Numbers Code Smell 105 - Comedian Methods More Info https://en.wikipedia.org/wiki/Cowboy_coding?embedable=true https://www.linkedin.com/pulse/software-development-cowboy-coding-hakan-atbaş/ Credits Photo by on Taylor Brandon Unsplash The danger from computers is not that they will eventually get as smart as men, but that we will meanwhile agree to meet them halfway. Bernard Avishai Code Smell 228 - Multiple Classes per File More than one class is a mess. TL;DR: Follow the separation of concerns principle and file organization Problems Code Organization Coupling Autoloading problems Debugging Version control and merge conflicts Solutions Declare a single class per file Use name scoping Context In languages that declare classes using a file system, having one class per file is generally considered a best practice. This approach helps improve code organization and maintainability and reduces potential issues. You can organize namespaces into separate directories within your project structure. This way, you can maintain a logical and efficient codebase while avoiding the issues of declaring multiple classes in a single file. Sample Code Wrong <?

namespace MyNamespace;

class Class1 {
    public function sayHello() {
        echo "Hello from Class1!\n";
    }
}

class Class2 {
    public function sayHello() {
        echo "Hello from Class2!\n";
    }
} Right <?

namespace MyNamespace;

class Class1 {
    public function sayHello() {
        echo "Hello from Class1!\n";
    }
} <?

namespace MyNamespace;

class Class2 {
    public function sayHello() {
        echo "Hello from Class2!\n";
    }
} Detection Automatic [x] Many standards enforce this rule Tags Coupling Conclusion Keep your code organized, and follow known standards. Relations Code Smell 48 - Code Without Standards More Info https://en.wikipedia.org/wiki/Namespace?embedable=true https://rules.sonarsource.com/java/RSPEC-1996/?embedable=true Credits Photo by on Marjan Blan Unsplash Without requirements or design, programming is the art of adding bugs to an empty text file. Louis Srygley Code Smell 229 - Red Tape You overcomplicate your code. TL;DR: Avoid Accidental complexity and bureaucracy Problems Accidental Complexity Readability Fault Bijection Solutions Assign the responsibilities to real-world objects using the . MAPPER Context A "red tape" code smell could relate to unnecessary complexity, bureaucracy, or excessive configuration that makes the codebase harder to understand or maintain. Sample Code Wrong class VotingSystem:
    def __init__(self, config):
        self.config = config

    def validate_voter(self, voter_id):
        if self.config['voter_verification_enabled']:
            # Code to verify the voter's identity goes here

    def cast_vote(self, voter_id, candidate):
        if self.config['voting_enabled']:
            # Code to record the vote goes here

    def generate_vote_report(self):
        if self.config['generate_report']:
            # Code to generate a voting report goes here

    def audit_voting_system(self):
        if self.config['audit_enabled']:
            # Code to perform an audit of the voting system goes here

    # ... other voting-related methods ...

# Usage
config = {
    'voter_verification_enabled': True,
    'voting_enabled': False,
    'generate_report': False,
    'audit_enabled': True
}

voting_system = VotingSystem(config)

# Voter validation, voting, report generation, 
# and auditing are handled based on the configuration. Right class VoterVerification:
    def verify_voter(self, voter_id):
        # Code to verify the voter's identity goes here

class VotingMachine:
    def cast_vote(self, voter_id, candidate):
        # Code to record the vote goes here

class VoteReporter:
    def generate_report(self):
        # Code to generate a voting report goes here

class VotingAuditor:
    def audit_voting_system(self):
        # Code to perform an audit of the voting system goes here

# Usage
voter_verification = VoterVerification()
voting_machine = VotingMachine()
vote_reporter = VoteReporter()
voting_auditor = VotingAuditor()

# Voter verification, vote casting, report generation, 
# and auditing are handled separately. Detection Semi-Automatic [x] Some tools can guess you are bloating your objects with unnecessary responsibilities. Tags Bloaters Conclusion The red tape code smell is evident as developers need to navigate the complex configuration to determine which features are active. This not only adds unnecessary complexity but also increases the likelihood of misconfigurations that could impact the integrity of your system. Relations Code Smell 54 - Anchor Boats Disclaimer Code Smells are my . opinion Credits Photo by on the blowup Unsplash A Fallacy of Software: If it works, and we don't change anything, it will keep working. Jessica Kerr Code Smell 230 - Schrödinger Code Your code is dead and alive. TL;DR: Look carefully for race conditions Problems Principle of Least Surprise Violation Race Conditions Solutions Avoid race conditions Avoid global variables Use proper synchronization Context Schrödinger code is code that can be in two different states at the same time, but the state of the code is not determined until it is executed. This can happen when the code contains a race condition, or when the code depends on the state of a global variable that can be changed by other threads or processes. Sample Code Wrong import threading

cats_alive = 0

def thread_1():
  cats_alive += 1

def thread_2():
  cats_alive -= 1

if cats_alive > 0:
  feedThem()

# The value of cats_alive is indeterminate, 
# so the code can be in either of the two states:
#
# 1. cats_alive > 0 and feedThem() is called.
# 2. cats_alive <= 0 and feedThem() is not called. Right import threading

lock = threading.Lock()
cats_alive = 0

def thread_1():
  with lock:
    cats_alive += 1

def thread_2():
  with lock:
    cats_alive -= 1

if cats_alive > 0:
  feedThem()

# With the lock, the two threads cannot access 
# the `cats_alive` variable at the same time.
# This means that the value of `cats_alive` is always determined, 
# and the program will not exhibit Schrödinger code behavior. Detection Manual [x] Make code reviews on concurrent code Tags Concurrency Globals Conclusion To avoid Schrödinger code, avoid race conditions and avoid depending on the state of global variables that can be changed by other threads or processes. If you need to use a global variable in your code, ensure it is correctly synchronized. Relations Code Smell 198 - Hidden Assumptions Code Smell 32 - Singletons Code Smell 60 - Global Classes Credits Photo by on Yerlin Matu Unsplash The last thing you wanted any programmer to do is mess with internal state Alan Kay Next week, 5 more smells.

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