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Industrial motor systems power nearly every sector, from manufacturing to water treatment. Motors alone no longer carry the load—software now plays an increasingly important role in running those systems smarter and more efficiently.
Engineers, technicians, and systems integrators depend on precise software tools to control, monitor, and adapt motor behavior. Understanding how software influences motor performance reveals new opportunities for innovation, reliability, and long-term savings.
Motor Control Through Intelligent Software Systems
Modern control systems rely on intelligent software to manage motor speed, direction, and torque with real-time accuracy. Platforms like variable frequency drives and programmable logic controllers continuously adjust motor output based on real-world data. Engineers configure digital parameters to match specific operational demands and improve response time.
Operators gain flexibility by modifying settings remotely or building custom control sequences. Technicians can automate entire systems, from conveyor belts to robotic arms, without replacing physical components. One key benefit that highlights the role of software in industrial motor applications lies in its ability to control performance dynamically without interrupting workflow.
Predictive Maintenance and System Longevity
Software platforms monitor motor systems around the clock, collecting data from temperature, vibration, and power sensors. Engineers analyze this information to predict when a component will fail, not just react after a breakdown. Maintenance teams receive alerts before issues escalate into expensive damage.
Artificial intelligence and machine learning help refine those predictions over time. Advancements in sensors, AI tools, and software help companies with important preventative maintenance of water pumps, generators, and more, while extending asset life cycles across industrial environments.
Integration With Industrial IoT and Cloud Platforms
Software connects motors to broader digital ecosystems through industrial IoT frameworks. Systems collect real-time operational data and upload it to secure cloud platforms where managers track performance from anywhere. Teams use dashboards to identify inefficiencies, tweak motor behavior, or schedule service with precision.
Remote access also improves consistency across multi-site operations. Engineers control different motor systems from a single interface without losing visibility. Digital ecosystems improve collaboration between IT teams and facility managers through shared access and up-to-date system data.
Efficiency Optimization and Energy Savings
Software plays a direct role in cutting motor energy consumption by reducing idle time and adjusting output to meet demand. Smart load balancing reduces peaks and keeps motors running in optimal efficiency zones. Control systems fine-tune motor parameters automatically during shifting production requirements.
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The growing role of software in industrial motor applications focuses on optimization and efficiency. Facility managers use analytics tools to measure savings and track improvements in real time.
Energy dashboards reveal trends across shifts, product runs, or seasonal demand. Companies that invest in smarter control software gain both financial and operational returns. That fact alone reflects
Safety Features and Operational Protection
Software adds built-in safety features that shut motors down instantly during fault conditions. Speed limits, torque restrictions, and electronic guards protect both equipment and personnel during critical operations. Engineers can preprogram emergency responses to mechanical failure, overload, or electrical surges.
Customization and Adaptive Motor Programming
Motor systems often require unique configurations that off-the-shelf hardware can’t handle. Engineers use adaptive software to customize acceleration rates, directional sequences, or multi-motor synchronization. Operators apply updates without swapping parts or overhauling system architecture.
Software evolves as operational needs change. Manufacturers introduce firmware upgrades, new logic modules, or plug-in analytics tools that scale with production. Adaptive control programs give engineers the freedom to innovate while maintaining stability and uptime.
Top 10 ways for software engineers or developers to gain more power in their companies?


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Top 10 ways for software engineers or developers to gain more power in their companies?
Power is a relative term. In business, power is the ability to influence others to achieve a desired outcome. As a software engineer, you may not be the CEO of your company, but that doesn’t mean you can’t wield a considerable amount of power. Here are the top 10 ways for software engineers to gain more power in their companies.
1. Become an expert in your field.
The first way to gain more power in your company is to become an expert in your field. When you know more than anyone else in the room, people are going to listen to what you have to say. Be the go-to person for questions about your area of expertise and make yourself indispensable.
2. Make friends with the right people.
It’s not what you know, it’s who you know. Making friends with the right people can open doors and help you get your foot in the door. If you want to gain more power in your company, start by making friends with the people who already have it.
3. Speak up and be heard.
If you want to influence others, you need to be vocal about it. Don’t be afraid to speak up and share your ideas with others. The more you speak up, the more likely it is that your voice will be heard and that you’ll be able to make a difference.
4. Network, network, network!
Get out there and meet people! The more connections you have, the greater your chances of success will be. Go to industry events, meetups, and conferences and make yourself known. The more visible you are, the more likely it is that you’ll be able to exert your influence when it matters most.
5. Write articles or blog posts about your area of expertise.
Sharing your knowledge with others is a great way to build credibility and gain recognition as an expert in your field. Writing articles or blog posts about your area of expertise is a great way to get started. Not only will you get exposure for your ideas, but you’ll also get feedback from others that can help improve your thinking. And, if people like what they read, they may even start quoting you as an expert!
6. Stay up-to-date on industry trends.
If you want to be seen as an expert, it’s important that you stay up-to-date on industry trends. Keep abreast of new developments in your field so that you can provide valuable insights when opportunities or problems arise. Staying current will also give you an edge over competition when it comes time for promotions or raises!
7. Give presentations or talks about your area of expertise .
Sharing your knowledge with others is a great way to build credibility and gain recognition as an expert in your field . If there are conferences or meetups related to your industry , see if there are any speaking opportunities available . Giving presentations or talks is also a great opportunity t o network with other professionals in your field . 8\. Volunteer t o work on high – profile projects . If y ou want t o increase y our visibility within y our company , volunteering t o work on high – profile projects is a great way t o do it . Not only will y ou get t o work on some challenging and interesting projects , but y ou’ll also get t o rub shoulders with some influential people . And , if y o u do a good job , y our work will speak for itself — which can only improve y our standing within the company .
9. Seek out mentorship opportunities.
A mentor can provide invaluable guidance — both professional and personal — as you navigate your career. Mentors can help you develop both professionally and personally, and they can also introduce you to their networks . If you’re interested in finding a mentor, seek out programs within your company or look for individuals who have already achieved what you aspire to accomplish .
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10. Be assertive
— but not aggressive . Being assertive means being confident enough in your abilities to speak up for yourself when necessary , but not being so aggressive that your actions alienate others. When you’re assertive, people are more likely to listen to what you have to say because they respect your confidence in yourself. But being too aggressive can create hostility which can shake people’s confidence in you.
According to Kurt Guntheroth, software developers can gain more power in their companies doing the following:
- Working for the same company for many years gives you more power. The opinions of recent hires are always distrusted, no matter how smart they are. Sorry, that’s not a thing you can do now.
- Being among the first developers at a startup gives you a lot of power, because you know how everything works. The guys who come in a year later will never know as much as you do.
- Becoming good friends and golf/squash/kayaking buddies with the lead or manager gives you a ton of power. Not all managers are social enough to make that work, though. I’ve known several rather mediocre engineers who wielded power way beyond what they should have because they had been around awhile, and were friends with the boss.
- A history of calling the outcomes of decisions correctly makes you slightly more powerful. The trick comes in balancing how much to advertise your correct calls. Too much and you sound snooty. Not enough and being right doesn’t even matter.
- Willingness to write spec documents gives you a lot of power over a design. It’s my experience that only about half of the excellent software developers I have ever worked with could string two grammatical sentences together.
Are you a software engineer or developer who feels like you don’t have enough power or sway in your company? If so, don’t worry – you’re not alone. The truth is, there are often a lot of people in companies who feel like they don’t have enough power.
But the good news is that there are things you can do to change that. In this blog post, we’ll give you 10 actionable tips that you can use to gain more power in your company.
1. Get involved in decision-making processes.
2. Speak up when you have an idea or perspective to share.
3. Become a mentor or coach to others.
4. Be a thought leader by writing blog posts or articles, giving talks, or teaching classes.
5. Develop relationships with people in other departments or companies.
6. Join or create employee resource groups.
7. Serve on committees or working groups.
8. Volunteer for special projects.
9. Network outside of work hours.
10. Make sure your performance review focuses on your accomplishments.
11. Become a subject matter expert.
12. Develop a strong understanding of the business.
13. Get involved in strategic decision-making.
14. Foster relationships with key stakeholders.
15. Drive change within your team.
16. Improve process and efficiency within your department.
17. Champion new initiatives and ideas.
18. Invest in yourself and your career development.
19. Be an active participant in industry thought leadership.
20. Leverage your technical expertise to improve customer experiences or solve business problems.
If you’re a software engineer or developer who feels like you could have more power in your company, we hope this blog post was helpful for you! Remember, gaining more power in your company is all about taking action and putting yourself out there – so don’t be afraid to get started today with some of the tips we listed above.”
These are just a few ways that software engineers can become more powerful within their companies. By becoming a subject matter expert, developing a strong understanding of the business, and getting involved in strategic decision-making, you can position yourself as a key player in your organization. So take action today and start making your voice heard!
Which programming language produces binaries that are the most difficult to reverse engineer?


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Which programming language produces binaries that are the most difficult to reverse engineer?
Have you ever wondered how someone might go about taking apart your favorite computer program to figure out how it works? The process is called reverse engineering, and it’s done all the time by software developers in order to learn from other programs or to find security vulnerabilities. In this blog post, we’ll discuss why some programming languages make reverse engineering more difficult than others. We’re going to take a look at why binaries that were originally written in assembly code are generally the most difficult to reverse engineer.
Any given high-level programming language will compile down to assembly code before becoming a binary. Because of this, the level of difficulty in reverse engineering a binary is going to vary depending on the original high-level programming language.
Reverse Engineering
Reverse engineering is the process of taking something apart in order to figure out how it works. In the context of software, this usually means taking a compiled binary and figuring out what high-level programming language it was written in, as well as what the program is supposed to do. This can be difficult for a number of reasons, but one of the biggest factors is the level of optimization that was applied to the code during compilation.
In order to reverse engineer a program, one must first understand how that program was created. This usually involves decompiling the program into its original source code so that it can be read and understood by humans.
Once the source code has been decompiled, a reverse engineer can begin to understand how the program works and look for ways to modify or improve it. However, decompiling a program is not always a trivial task. It can be made significantly more difficult if the program was originally written in a language that produces binaries that are difficult to reverse engineer.
Some Languages Are More Difficult to Reverse Engineer Than Others.
There are many factors that can make reversing a binary more difficult, but they all stem from the way that the compiled code is organized. For example, consider two different programs written in two different languages. Both programs do the same thing: print “Hello, world!” to the screen. One program is written in C++ and one is written in Java.
When these programs are compiled, the C++ compiler will produce a binary that is considerably smaller than the binary produced by the Java compiler. This is because C++ allows programmers to specify things like data types and memory layout explicitly, whereas Java relies on interpretation at runtime instead. As a result, C++ programs tend to be more efficient than Java programs when compiled into binaries.
However, this also means that C++ binaries are more difficult to reverse engineer than Java binaries. This is because all of the information about data types and memory layout is encoded in the binary itself instead of being stored separately in an interpreted programming language like Java. As a result, someone who wants to reverse engineer a C++ binary would need to spend more time understanding how the compiled code is organized before they could even begin to understand what it does.
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Optimization
Optimization is a process where the compiler tries to make the generated code run as fast as possible, with the goal of making the program take up less memory. This is generally accomplished by reorganizing the code in such a way that makes it harder for a human to read. For example, consider this simple C++ program:
int main() {
int x = 5;
int y = 10;
int z = x + y;
return z;
}
This would compile down to assembly code that looks something like this:
main: ; PC=0x1001000
mov eax, 5 ; PC=0x1001005
mov ebx, 10 ; PC=0x100100a
add eax, ebx ; PC=0x100100d
ret ; PC=0x100100e
As you can see, even this very simple program has been optimized to the point where it’s no longer immediately clear what it’s doing just by looking at it. If you were trying to reverse engineer this program, you would have a very difficult time understanding what it’s supposed to do just by looking at the assembly code.
Of course, there are ways to reverse engineer programs even if they’ve been heavily optimized. However, all things being equal, it’s generally going to be more difficult to reverse engineer a binary that was originally written in assembly code than one that was written in a higher-level language such as Java or Python. This is because compilers for higher-level languages typically don’t apply as much optimization to the generated code since humans are going to be reading and working with it directly anyways. As a result, binaries that were originally written in assembly tend to be more difficult to reverse engineer than those written in other languages.
According to Tim Mensch, programming language producing binaries that are the most difficult to reverse engineer are probably anything that goes through a modern optimization backend like gcc
or LLVM.
And note that gcc
is now the GNU Compiler Collection, a backronym that they came up with after adding a number of frontend languages. In addition to C, there are frontends for C++, Objective-C, Objective-C++, Fortran, Ada, D, and Go, plus others that are less mature.
LLVM has even more options. The Wikipedia page lists ActionScript, Ada, C#, Common Lisp, PicoLisp, Crystal, CUDA, D, Delphi, Dylan, Forth, Fortran, Free Basic, Free Pascal, Graphical G, Halide, Haskell, Java bytecode, Julia, Kotlin, Lua, Objective-C, OpenCL, PostgreSQL’s SQL and PLpgSQL, Ruby, Rust, Scala, Swift, XC, Xojo and Zig.
I don’t even know what all of those languages are. In some cases they may include enough of a runtime to make it easier to reverse engineer the underlying code (I’m guessing the Lisp dialects and Haskell would, among others), but in general, once compiled to a target architecture with maximum optimization, all of the above would be more or less equally difficult to reverse engineer.
Languages that are more rare (like Zig) may have an advantage by virtue of doing things differently enough that existing decompilers would have trouble. But that’s only an incremental increase in difficulty.
There exist libraries that you can add to a binary to make it much more difficult to reverse engineer. Tools that prevent trivial disassembly or that make code fail if run in a debugger, for instance. If you really need to protect code that you have to distribute, then using one of those products might be appropriate.
But overall the only way to be sure that no one can reverse engineer your code (aside from nuking it from orbit, which has the negative side effect of eliminating your customer base) is to never distribute your code: Run anything proprietary on servers and only allow people with active accounts to use it.
Generally, though? 99.9% of code isn’t worth reverse engineering. If you’re not being paid by some large company doing groundbreaking research (and you’re not if you would ask this question) then no one will ever bother to reverse engineer your code. This is a really, really frequent “noob” question, though: Because it was so hard for a new developer to write an app, they fear someone will steal the code and use it in their own app. As if anyone would want to steal code written by a junior developer. 🙄
More to the point, stealing your app and distributing it illegally can generally be done without reverse engineering it at all; I guarantee that many apps on the Play Store are hacked and republished with different art without the thieves even slightly understanding how the app works. It’s only if you embed some kind of copy protection/DRM into your app that they’d even need to hack it, and if you’re not clever about how you add the DRM, hacking it won’t take much effort or any decompiling at all. If you can point a debugger at the code, you can simply walk through the assembly language and find where it does the DRM check—and disable it. I managed to figure out how to do this as a teen, on my own, pre-Internet (for research purposes, of course). I guarantee I’m not unique or even that skilled at it, but start to finish I disabled DRM in a couple hours at most.
So generally, don’t even bother worrying about how difficult something is to reverse engineer. No one cares to see your code, and you can’t stop them from hacking the app if you add DRM. So unless you can keep your unique code on a server and charge a subscription, count on the fact that if your app gets popular, it will be stolen. People will also share subscription accounts, so you need to worry about that as well when you design your server architecture.
There are a lot of myths and misconceptions out there about binary reversing.
Myth #1: Reversing a Binary is Impossible
This is simply not true. Given enough time and effort, anyone can reverse engineer a binary. It may be difficult, but it’s certainly not impossible. The first step is to understand what the program is supposed to do. Once you have a basic understanding of the program’s functionality, you can start to reverse engineering the code. This process will help you understand how the program works and how to modify it to suit your needs.
Myth #2: You Need Special Tools to Reverse Engineer a Binary
Again, this is not true. All you really need is a text editor and a disassembler. A disassembler will take the compiled code and turn it into assembly code, which is much easier to read and understand.Once you have the assembly code, you can start to reverse engineer the program. You may find it helpful to use a debugger during this process so that you can step through the code and see what each instruction does. However, a debugger is not strictly necessary; it just makes the process easier. If you don’t have access to a debugger, you can still reverse engineer the program by tracing through the code manually.
Myth #3: Only Certain Types of Programs Can Be Reversed Engineered
This myth is half true. It’s certainly easier to reverse engineered closed-source programs than open-source programs because you don’t have access to the source code. However, with enough time and effort, you can reverse engineer any type of program. The key is to understand the program’s functionality and then start breaking down the code into smaller pieces that you can understand. Once you have a good understanding of how the program works, you can start to figure out ways to modify it to suit your needs.
In conclusion,
We can see that binaries compiled from assembly code are generally more difficult to reverse engineer than those from other high-level languages. This is due to the level of optimization that’s applied during compilation, which can make the generated code very difficult for humans to understand. However, with enough effort and expertise, it is still possible to reverse engineer any given binary.
So, which programming language produces binaries that are the most difficult to reverse engineer?
There is no definitive answer, as it depends on many factors including the specific features of the language and the way that those features are used by individual programmers. However, languages like C++ that allow for explicit control over data types and memory layout tend to produce binaries that are more difficult to reverse engineer than interpreted languages like Java.
Google’s Carbon Copy: Is Google’s Carbon Programming language the Right Successor to C++?
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Top 100 Data Science and Data Analytics and Data Engineering Interview Questions and Answers
What are the top 10 Wonders of computing and software engineering?


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What are the top 10 Wonders of computing and software engineering?
Computer science and software engineering are fascinating fields that continue to evolve and surprise us. Computer science and software engineering are disciplines that are essential for the modern world. They have led to the development of many innovative products and services that have made our lives easier and more efficient. In this blog post, we’ll explore the top 10 wonders of computer science and software engineering.
The things Alan Keys found to be astonishing and amazing (and shocking) are:
- Turing’s notion of machines that can simulate machines completely by interpreting their descriptions (exhibiting the programmable computer as “a language machine” and a “meta-language machine” — along with this is the simplicity of what is required to do so (a great book is Marvin Minsky’s “Computation: Finite and Infinite Machines”). Turing’s approach is much more of a “real CS” approach compared to Goedel’s earlier methods, and soon led to a large number of important next steps.
- How simple (a) it is to design a whole computer from just one kind of logical element (e.g. “NOT-BOTH”), especially when compared (b) to how Russell and Whitehead struggled to “bootstrap mathematics, etc., from logic at the turn of the last century. (This is one of those “Point of View is Worth 80 IQ Points” …)
- Lisp, and McCarthy’s general approach to “mathematical theories of computation” and having languages that can act as their own metalanguage. One of the great cornucopias of our field.
- Sketchpad by Ivan Sutherland for so many reasons, including: the approach to interactive computer graphics and the simulations of the graphic relationships, the “object-oriented” approach to definition and deriving new kinds of things (including “masters” and making instances from masters), enormous virtual worlds that are windowed on the display, the use of goal-directed programming with the system solving the simultaneous goals in real-time, etc. And more, including the demonstration that a simulated computer on a computer need look nothing like the underlying hardware or any “normal” idea of “computer”.
- The big Shannon et al. ideas about how to have imperfect things be organized in systems that are much more perfectly behaved even if the organizational mechanisms are themselves noisy. Includes all forms of “noise”, “representations”, “communications”, “machines”, etc. and poking deeply into Biology and how living things work. Nice implications for “stochastic computing” of many kinds which are needed more and more as things scale.
- The deep implications of “symbolic computation” (now a very un-funded area) for being able to move from the trivialities of “data” (no matter how voluminous”) to the profundities and powers of “Meaning”. This used to be called “AI” and now has to be called “real AI” or “strong AI” (it would be much better under a less loaded term: how about “Flexible Competence”?)
- The Internet. Certainly the best thing done by my research community, and the first real essay into the kinds of scaling and stabilities that all computer science should be trying to understand and improve. This was a great invention and development process in all ways, and — by looking at Biology, which inspired but we really couldn’t use — it had a reasonable chance to work. That it was able to scale stably over more than 10 (maybe 11) orders of magnitude, as indeed planned, is still kind of amazing to me (even though it should have). Judging from most software systems today not being organized like the Internet, one is forced into the opinion that most computerists don’t understand it, why it is great (and maybe don’t even think of it as the fruits of “real computer science” because it just works so much better and more reliably than most other attempted artifacts in the field).
- Application: #1: Self-Driving Cars
Self-driving cars are one of the most hyped technologies of the past few years. And for good reason! These autonomous vehicles have the potential to drastically reduce accidents and improve traffic flow. While there are still some kinks to be ironed out, it’s only a matter of time until self-driving cars become the norm. - Application: #2: Artificial Intelligence
Artificial intelligence is another technology that is rapidly evolving. AI is being used in a variety of ways, from personal assistants like Siri to chatbots that can carry on a conversation. As AI gets more sophisticated, its capabilities will only continue to grow. - Application: #3: Virtual Reality
Virtual reality is another exciting technology with a lot of potential. VR has already been used in a number of different industries, from gaming to medicine. And as VR technology gets more advanced, we can only imagine the new and innovative ways it will be used in the future. - Application: #4: Blockchain
You’ve probably heard of Bitcoin, the digital currency that uses blockchain technology. But what exactly is blockchain? In short, it’s a decentralized database that can be used to store data securely. Blockchain is already being used in a number of different industries, and its applications are only growing. - Application: #5: Internet of Things
The internet of things refers to the growing trend of interconnected devices. From your phone to your fridge, more and more devices are being connected to the internet. This allows them to share data and makes them easier to control. The internet of things is changing the way we live and work, and there’s no doubt that its impact will only continue to grow in the years to come. - Application: #6: Data Science
Data science is a relatively new field that combines statistics, computer science, and domain expertise to extract knowledge from data. Data science is being used in a variety of industries, from healthcare to retail. And as data becomes increasingly abundant, data scientists will become even more important in helping organizations make sense of it all. - Application: #7: Machine Learning
Machine learning is a subset of artificial intelligence that allows computers to learn from data without being explicitly programmed. Machine learning is being used in a number of different ways, from fraud detection to object recognition. As machine learning algorithms get more sophisticated, they will continue to revolutionize the way we live and work. - Application: #8 Cybersecurity : Cybersecurity is a critical concern for businesses and individuals alike. With so much of our lives taking place online, it’s important to have measures in place to protect our information from hackers and cyber criminals.
These are just some of the many wonders of computer science and software engineering! Each one has the potential to change our world in amazing ways. We can’t wait to see what else these fields have in store for us!
Other notable wonders of computing:
#16 Mobile phones are handheld devices that allow us to make calls, send texts, and access the internet while on the go. They have become an indispensable part of our lives and have transformed the way we stay connected with others.
#17 Social Media
Social media platforms like Facebook, Twitter, and Instagram have changed the way we interact with each other. They provide us with a space to share our thoughts, feelings, and experiences with friends and family members who might be located anywhere in the world.
#18 Cloud Computing
Cloud computing is a model of computing that allows users to access data and applications over the internet. It has made it possible for businesses to operate more efficiently by reducing their reliance on physical infrastructure.
#19 Big Data
Big data refers to large data sets that can be analyzed to reveal patterns and trends. It is being used by businesses in a variety of industries to make better decisions about everything from product development to marketing strategies.
#20 Augmented Reality Augmented reality is a type of technology that overlays digital information on real-world objects. It has many potential applications, including education, gaming, and navigation.
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#21 3D Printing 3D printing is a process of creating three-dimensional objects from a digital file. It has revolutionized manufacturing by making it possible to create customized products quickly and easily. These are just some of the things that computer science and software engineering have made possible! As you can see, these disciplines have had a major impact on our world and will continue to shape the future as we move into the digital age.
Conclusion: So there you have it! These are the top 10 wonders of computer science and software engineering according to me. Do you agree with my list? What would you add or remove? Let me know in the comments below!
Addendum:
In the spirit of choosing artifacts over ideas, I would replace “symbolic computation “ with Unix.
I’ve mentioned elsewhere that one can praise in a sentence or two, but criticism ethically demands more careful substantiation.
All I’ll say here is that when Unix was being invented Xerox Parc was already successfully making systems with dynamic objects that required no separate OS layering or system builds. That said, Doug McIlroy did find the start of what could have been really fruitful ideas when he implemented “pipes” programming. If they had seen what could have been done if they had reduced the process overhead to zero bytes, and gone to a dynamic language, then something great could have resulted. By Alan Kay
What do you mean by organizing software systems like the internet?
Just to get you started: consider that the Internet’s (a) processes do not have to be stopped to fix, change, add to etc. (b) messages are not commands (c) units of computation are perfectly encapsulated (only the interior code code of a computer can decide to do anything or nothing) (d) units of transmission can be very badly damaged and messages will still get through, (e) scaling is more than 10 orders of magnitude (f) and on and on and on.
What SW systems to you know of that are remotely like this (that don’t depend intrinsically on what is wonderful about the Internet)?
This doesn’t mean the Internet is a perfect design at all. For example, the add-on of DNS was not nearly as good and lasting a scheme as the base semantics of TCP/IP. (It’s crazy that there are not unique IDs for every kind of entity manifested within the Internet system. Bob Kahn has been advocating this for several decades now — Joe Armstrong among others has pointed out that the modern hashing schemes (SHA256, etc.) are good enough to provide excellent unique IDs for Internet entities, etc.)
But the Internet did completely raise many bars qualitatively and astonishingly higher. It should be used as a starting point in thinking about how most SW systems can and should be organized.
Just a note about this big shift in thinking within the ARPA/Parc community — it is hard to pin down just when. But Wes Clark used to say that no computer is any good if it can’t work perfectly with 10% of its wires disconnected! Packet Switching (American version at RAND ARPA project in early 60s by Paul Baran) meant that you could do store and forward with a number of routes. If you made the protocol full-duplex, you could guarantee *eventually perfect* delivery of packets. At Parc the huge shift from “theoretical” to “punch in the face reality” came as we realized just how wonderfully well the extremely simple Ethernet was actually performing. This led to the articulated idea that no computation should ever require having to be stopped in order to improve/change/etc it.
In other words, make the systems design such that things will work “eventually as wished”, so you can spend your brain cells on (a) better designs, and (b) better optimizations. The Internet grew out of the whole community’s strong and emotional realizations around these ideas. By Alan Kay
What are the Top 5 things that can say a lot about a software engineer or programmer’s quality?


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What are the Top 5 things that can say a lot about a software engineer or programmer’s quality?
When it comes to the quality of a software engineer or programmer, there are a few key things that can give you a good indication. First, take a look at their code quality. A good software engineer will take pride in their work and produce clean, well-organized code. They will also be able to explain their code concisely and confidently. Another thing to look for is whether they are up-to-date on the latest coding technologies and trends. A good programmer will always be learning and keeping up with the latest industry developments. Finally, pay attention to how they handle difficult problems. A good software engineer will be able to think creatively and come up with innovative solutions to complex issues. If you see these qualities in a software engineer or programmer, chances are they are of high quality.
Below are the top 5 things can say a lot about a software engineer/ programmer’s quality?
- The number of possible paths through the code (branch points) is minimized. Top quality code tends to be much more straight line than poor code. As a result, the author can design, code and test very quickly and is often looked at as a programming guru. In addition this code is far more resilient in Production.
- The code clearly matches the underlying business requirements and can therefore be understood very quickly by new resources. As a result there is much less tendency for a maintenance programmer to break the basic design as opposed to spaghetti code where small changes can have catastrophic effects.
- There is an overall sense of pride in the source code itself. If the enterprise has clear written standards, these are followed to the letter. If not, the code is internally consistent in terms of procedure/object, function/method or variable/attribute naming. Also indentation and continuations are universally consistent throughout. Last but not least, the majority of code blocks are self-evident to the requirements and where not the case, adequate purpose focused documentation is provided.
In general, I have seen two types of programs provided for initial Production deployment. One looks like it was just written moments ago and the other looks like it has had 20 years of maintenance performed on it. Unfortunately, the authors of the second type cannot generally see the difference so it is a lost cause and we just have to continue to deal with the problems. - In today’s programming environment, a project may span many platforms, languages etc. A simple web page may invoke an API which in turn accesses a database. For this example lets say JavaScript – Rest API – C# – SQL – RDBMS. The programmer can basically embed logic anywhere in this chain, but needs to be aware of reuse, performance and maintenance issues. For instance, if a part of the process requires access to three database tables, it is both faster and clearer to allow the DBMS engine return a single query than compare the tables in the API code. Similarly every business rule coded in the client side reduces re-usability potential.
Top quality developers understand these issues and can optimize their designs to take advantages of the strengths of the component technologies. - The ability to stay current with new trends and technologies. Technology is constantly evolving, and a good software engineer or programmer should be able to stay up-to-date on the latest trends and technologies in order to be able to create the best possible products.
To conclude:
Below are other things to consider when hiring good software engineers or programmers:
- The ability to write clean, well-organized code. This is a key indicator of a good software engineer or programmer. The ability to write code that is easy to read and understand is essential for creating high-quality software.
- The ability to test and debug code. A good coder should be able to test their code thoroughly and identify and fix any errors that may exist.
- The ability to write efficient code. Software engineering is all about creating efficient solutions to problems. A good software engineer or programmer will be able to write code that is efficient and effective.
- The ability to work well with others. Software engineering is typically a team-based effort. A good software engineer or programmer should be able to work well with others in order to create the best possible product.
- The ability to stay current with new trends and technologies.
What is the single most influential book every Programmers should read


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What is the single most influential book every Programmers should read
There are a lot of books that can be influential to programmers. But, what is the one book that every programmer should read? This is a question that has been asked by many, and it is still up for debate. However, there are some great contenders for this title. In this blog post, we will discuss three possible books that could be called the most influential book for programmers. So, what are you waiting for? Keep reading to find out more!
- Bjarne Stroustrup – The C++ Programming Language,
- Brian W. Kernighan, Rob Pike – The Practice of Programming,
- Donald Knuth – The Art of Computer Programming,
- Ellen Ullman – Close to the Machine,
- Ellis Horowitz – Fundamentals of Computer Algorithms,
- Eric Raymond – The Art of Unix Programming,
- Gerald M. Weinberg – The Psychology of Computer Programming,
- James Gosling – The Java Programming Language,
- Joel Spolsky – The Best Software Writing I,
- Keith Curtis – After the Software Wars,
- Richard M. Stallman – Free Software, Free Society,
- Richard P. Gabriel – Patterns of Software,
- Richard P. Gabriel – Innovation Happens Elsewhere,
- Code Complete (2nd edition) by Steve McConnell,
- The Pragmatic Programmer,
- Structure and Interpretation of Computer Programs,
- The C Programming Language by Kernighan and Ritchie,
- Introduction to Algorithms by Cormen, Leiserson, Rivest & Stein,
- Design Patterns by the Gang of Four,
- Refactoring: Improving the Design of Existing Code,
- The Mythical Man Month,
- The Art of Computer Programming by Donald Knuth,
- Compilers: Principles, Techniques and Tools by Alfred V. Aho, Ravi Sethi and Jeffrey D. Ullman,
- Gödel, Escher, Bach by Douglas Hofstadter,
- Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin,
- Effective C++,
- More Effective C++,
- CODE by Charles Petzold,
- Programming Pearls by Jon Bentley,
- Working Effectively with Legacy Code by Michael C. Feathers,
- Peopleware by Demarco and Lister
- Coders at Work by Peter Seibel,
- Surely You’re Joking, Mr. Feynman!,
- Effective Java 2nd edition,
- Patterns of Enterprise Application Architecture by Martin Fowler,
- The Little Schemer,
- The Seasoned Schemer,
- Why’s (Poignant) Guide to Ruby,
- The Inmates Are Running The Asylum: Why High Tech Products Drive Us Crazy and How to Restore the Sanity,
- The Art of Unix Programming,
- Test-Driven Development: By Example by Kent Beck,
- Practices of an Agile Developer,
- Don’t Make Me Think,
- Agile Software Development, Principles, Patterns, and Practices by Robert C. Martin,
- Domain Driven Designs by Eric Evans,
- The Design of Everyday Things by Donald Norman,
- Modern C++ Design by Andrei Alexandrescu,
- Best Software Writing I by Joel Spolsky,
- The Practice of Programming by Kernighan and Pike,
- Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt,
- Software Estimation: Demystifying the Black Art by Steve McConnel,
- The Passionate Programmer (My Job Went To India) by Chad Fowler,
- Hackers: Heroes of the Computer Revolution,
- Algorithms + Data Structures = Programs,
- Writing Solid Code,
- JavaScript – The Good Parts,
- Getting Real by 37 Signals,
- Foundations of Programming by Karl Seguin,
- Computer Graphics: Principles and Practice in C (2nd Edition),
- Thinking in Java by Bruce Eckel,
- The Elements of Computing Systems,
- Refactoring to Patterns by Joshua Kerievsky,
- Modern Operating Systems by Andrew S. Tanenbaum,
- The Annotated Turing,
- Things That Make Us Smart by Donald Norman,
- The Timeless Way of Building by Christopher Alexander,
- The Deadline: A Novel About Project Management by Tom DeMarco,
- The C++ Programming Language (3rd edition) by Stroustrup,
- Patterns of Enterprise Application Architecture,
- Computer Systems – A Programmer’s Perspective,
- Agile Principles, Patterns, and Practices in C# by Robert C. Martin,
- Growing Object-Oriented Software, Guided by Tests,
- Framework Design Guidelines by Brad Abrams,
- Object Thinking by Dr. David West,
- Advanced Programming in the UNIX Environment by W. Richard Stevens,
- Hackers and Painters: Big Ideas from the Computer Age,
- The Soul of a New Machine by Tracy Kidder,
- CLR via C# by Jeffrey Richter,
- The Timeless Way of Building by Christopher Alexander,
- Design Patterns in C# by Steve Metsker,
- Alice in Wonderland by Lewis Carol,
- Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig,
- About Face – The Essentials of Interaction Design,
- Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky,
- The Tao of Programming,
- Computational Beauty of Nature,
- Writing Solid Code by Steve Maguire,
- Philip and Alex’s Guide to Web Publishing,
- Object-Oriented Analysis and Design with Applications by Grady Booch,
- Effective Java by Joshua Bloch,
- Computability by N. J. Cutland,
- Masterminds of Programming,
- The Tao Te Ching,
- The Productive Programmer,
- The Art of Deception by Kevin Mitnick,
- The Career Programmer: Guerilla Tactics for an Imperfect World by Christopher Duncan,
- Paradigms of Artificial Intelligence Programming: Case studies in Common Lisp,
- Masters of Doom,
- Pragmatic Unit Testing in C# with NUnit by Andy Hunt and Dave Thomas with Matt Hargett,
- How To Solve It by George Polya,
- The Alchemist by Paulo Coelho,
- Smalltalk-80: The Language and its Implementation,
- Writing Secure Code (2nd Edition) by Michael Howard,
- Introduction to Functional Programming by Philip Wadler and Richard Bird,
- No Bugs! by David Thielen,
- Rework by Jason Freid and DHH,
- JUnit in Action
Source: Wikipedia

What are the concepts every Java C# C++ Python Rust programmer must know?
Ok…I think this is one of the most important questions to answer. According to the my personal experience as a Programmer, I would say you must learn following 5 universal core concepts of programming to become a successful Java programmer.
(1) Mastering the fundamentals of Java programming Language – This is the most important skill that you must learn to become successful java programmer. You must master the fundamentals of the language, specially the areas like OOP, Collections, Generics, Concurrency, I/O, Stings, Exception handling, Inner Classes and JVM architecture.
Recommended readings are OCA Java SE 8 Programmer by by Kathy Sierra and Bert Bates (First read Head First Java if you are a new comer ) and Effective Java by Joshua Bloch.
(2) Data Structures and Algorithms – Programming languages are basically just a tool to solve problems. Problems generally has data to process on to make some decisions and we have to build a procedure to solve that specific problem domain. In any real life complexity of the problem domain and the data we have to handle would be very large. That’s why it is essential to knowing basic data structures like Arrays, Linked Lists, Stacks, Queues, Trees, Heap, Dictionaries ,Hash Tables and Graphs and also basic algorithms like Searching, Sorting, Hashing, Graph algorithms, Greedy algorithms and Dynamic Programming.
Recommended readings are Data Structures & Algorithms in Java by Robert Lafore (Beginner) , Algorithms Robert Sedgewick (intermediate) and Introduction to Algorithms-MIT press by CLRS (Advanced).
(3) Design Patterns – Design patterns are general reusable solution to a commonly occurring problem within a given context in software design and they are absolutely crucial as hard core Java Programmer. If you don’t use design patterns you will write much more code, it will be buggy and hard to understand and refactor, not to mention untestable and they are really great way for communicating your intent very quickly with other programmers.
Recommended readings are Head First Design Patterns Elisabeth Freeman and Kathy Sierra and Design Patterns: Elements of Reusable by Gang of four.
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(4) Programming Best Practices – Programming is not only about learning and writing code. Code readability is a universal subject in the world of computer programming. It helps standardize products and help reduce future maintenance cost. Best practices helps you, as a programmer to think differently and improves problem solving attitude within you. A simple program can be written in many ways if given to multiple developers. Thus the need to best practices come into picture and every programmer must aware about these things.
Recommended readings are Clean Code by Robert Cecil Martin and Code Complete by Steve McConnell.
(5) Testing and Debugging (T&D) – As you know about the writing the code for specific problem domain, you have to learn how to test that code snippet and debug it when it is needed. Some programmers skip their unit testing or other testing methodology part and leave it to QA guys. That will lead to delivering 80% bugs hiding in your code to the QA team and reduce the productivity and risking and pushing your project boundaries to failure. When a miss behavior or bug occurred within your code when the testing phase. It is essential to know about the debugging techniques to identify that bug and its root cause.
Recommended readings are Debugging by David Agans and A Friendly Introduction to Software Testing by Bill Laboon.
I hope these instructions will help you to become a successful Java Programmer. Here i am explain only the universal core concepts that you must learn as successful programmer. I am not mentioning any technologies that Java programmer must know such as Spring, Hibernate, Micro-Servicers and Build tools, because that can be change according to the problem domain or environment that you are currently working on…..Happy Coding!
Summary: There’s no doubt that books have had a profound influence on society and the advancement of human knowledge. But which book is the most influential for programmers? Some might say it’s The Art of Computer Programming, or The Pragmatic Programmer. But I would argue that the most influential book for programmers is CODE: The Hidden Language of Computer Hardware and Software. In CODE, author Charles Petzold takes you on a journey from the basics of computer hardware to the intricate workings of software. Along the way, you learn how to write code in Assembly language, and gain an understanding of how computers work at a fundamental level. If you’re serious about becoming a programmer, then CODE should be at the top of your reading list!
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Master these principles to write code that is clean, maintainable, and scalable.Continue reading on Medium »
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- What I’ve Learned After 18 Months of Getting Back To Coding While Working Full-Time (part 3)by Keshia Coriolan (Coding on Medium) on June 17, 2025 at 8:15 pm
Well first, if you’ve following along now for three consecutive articles, let me start by saying THANK YOU! Honestly, sharing my story is…Continue reading on Medium »
- ChatGPT Quietly Took Over My Life — And I’m (Mostly) Okay With Itby Gamze K. Temur (Coding on Medium) on June 17, 2025 at 8:04 pm
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- How I Tricked My Brain to Be Addicted to Codingby The Hack Habitual (Coding on Medium) on June 17, 2025 at 7:46 pm
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- ✈️ React 19: State Management with Improved Context APIby The Blog Stacker - Tech Writer✨ (Coding on Medium) on June 17, 2025 at 7:31 pm
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- Why We Stopped Using @Autowired (and Slept Better Too..)by Devrim Ozcay (Coding on Medium) on June 17, 2025 at 7:30 pm
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- Common Tar Pits to Avoid when developing Big Data Systemsby /u/blit32 (programming) on June 17, 2025 at 7:01 pm
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- Lessons from changing tech stacks in real production apps.by /u/Personal-Work4649 (programming) on June 17, 2025 at 6:00 pm
I'm curious to hear from developers who have gone through this: What were the actual reasons that made your team switch technologies, frameworks, languages, or tools in a production app? Was it due to performance issues? Maintenance pain? Team experience? Scaling challenges? Ecosystem problems? Also, if you didn’t switch when you probably should have, what held you back? Would love to hear some war stories or insights to understand what really drives these decisions. submitted by /u/Personal-Work4649 [link] [comments]
- Mochi v0.8.0: Compile to C, C#, Dart, Elixir, Erlang, F#, Ruby, Rust, Scala and Swiftby /u/Adept-Country4317 (programming) on June 17, 2025 at 4:31 pm
We’ve just released Mochi v0.8.0 - a small, statically typed language designed for clarity, simplicity, and portability. In this release, we added support for compiling to ten more languages: C, C#, Dart, Elixir, Erlang, F#, Ruby, Rust, Scala, and Swift. It’s still early and currently supports basic control flow and expressions, but we’re actively working on expanding support for memory management and FFI across all targets. Our approach is simple: one small Mochi program at a time. We make sure the compiled code runs correctly in each target language, then iterate and expand from there. This release includes over 100 commits and 500+ file changes, laying the groundwork for future FFI and memory management support. Try it out and let us know what you think. We’d love your feedback! submitted by /u/Adept-Country4317 [link] [comments]
- Why JPEG Became the Web's Favorite Image Formatby /u/gametorch (programming) on June 17, 2025 at 3:44 pm
submitted by /u/gametorch [link] [comments]
- The Guy Who Wrote a Compiler Without a Compiler: Corrado Böhmby /u/Karthik-Writes-Tech (programming) on June 17, 2025 at 2:32 pm
Corrado Böhm was just a postgrad student in 1951 when he pulled off something that still feels unbelievable. He wrote a full compiler by hand without using a compiler and without even having access to a proper computer. At that time, computers weren’t easily available, especially not to students. Böhm had no machine to run or test anything, so he did everything on paper. He came up with his own language, built a model of a machine, and wrote a compiler for that language. The compiler was written in the same language it was supposed to compile, something we now call a self-hosting compiler. The language he designed was very minimal. It only had assignment operations, no control structures, and no functions. Variables could only store non-negative integers. To perform jumps, he used a special symbol π, and for input and output, he used the symbol ?. Even though the language was simple, it was enough to write working programs. One example from his work shows how to load an 11-element array from input using just basic assignments, jumps, and conditions. The logic may look strange today, but it worked, and it followed a clear structure that made sense for the time. You can check out that 11-element array program on wikipedia The entire compiler was just 114 lines of code. Böhm also designed a parsing method with linear complexity, which made the compilation process smooth for the kind of expressions his language supported. The structure of the code was clean and split logically between different types of expressions, all documented in his thesis. Concepts like self-hosting, efficient parsing, and clean code structure all appeared in this early work. Donald Knuth, a legendary computer scientist known for writing The Art of Computer Programming, also mentioned Böhm’s contribution while discussing the early development of programming languages. If this added any value to you, I’ve also written this as a blog post on my site. Same content, just for my own record. If not, please ignore. submitted by /u/Karthik-Writes-Tech [link] [comments]
- Do two triangles intersect?by /u/innochenti (programming) on June 17, 2025 at 2:20 pm
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- Animal Crossing for the GameCube has been decompiledby /u/r_retrohacking_mod2 (programming) on June 17, 2025 at 1:41 pm
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- Best Laptop for Coding and Programmingby Yousuf (Programming on Medium) on June 17, 2025 at 10:37 am
My Journey Through Machines That Made Me More ProductiveContinue reading on Medium »
- 10 Dead Simple Python Projects That Actually Teach You Real Skillsby Abdur Rahman (Programming on Medium) on June 17, 2025 at 10:37 am
Stop building calculators. Start building systems.Continue reading on Python in Plain English »
- How I Built a Personal AI Assistant in 100 Lines of Pythonby Talha Tahir (Programming on Medium) on June 17, 2025 at 10:37 am
Let’s be honest. Most of us don’t need Jarvis. We just need someone (or something) to help us deal with the 17 tabs we have open, the…Continue reading on Python in Plain English »
- 5 Insanely Useful Python Automation Scripts I Use Every Dayby PURRFECT SOFTWARE LIMITED (Programming on Medium) on June 17, 2025 at 10:36 am
Simple scripts that save time, kill repetitive tasks, and make my daily digital life a lot easier.Continue reading on Python in Plain English »
- Handling Authentication in React Native Using Redux Toolkit (The Clean Way)by The Hack Habitual (Programming on Medium) on June 17, 2025 at 10:36 am
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- Introducing The Scalability Diaries: A Journey into Building Scalable Systemsby Code And Cortex (Programming on Medium) on June 17, 2025 at 10:35 am
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- The Hidden Cost of ‘We’ll Fix It Later’: What 6 Months of Tracking Technical Debt Taught Meby Manoj Tyagi (Programming on Medium) on June 17, 2025 at 10:34 am
After 6 months of tracking our technical debt, I discovered something that changed everything: we were spending $31,200 on “quick fixes”.Continue reading on Medium »
- From Tutorial to Tool: How I Built a Python Web App in Two Daysby Maria Ali (Programming on Medium) on June 17, 2025 at 10:33 am
What started as a casual weekend project turned into one of the most efficient automations I’ve ever built, with just Python, Flask, and…Continue reading on Python in Plain English »
- How to Get Hired as a Developer Without a Degreeby AI With Lil Bro (Programming on Medium) on June 17, 2025 at 10:33 am
No need to do computer science degree to become a professional developer.Continue reading on Python in Plain English »
- Roadmap for IT engineers while studying collegeby Avinash Narasimhan (Programming on Medium) on June 17, 2025 at 10:23 am
Roadmap — exploring a path with a set of pre-defined things to be done in the upcoming times.Continue reading on Medium »
- The Humble Programmer (1972)by /u/gametorch (programming) on June 17, 2025 at 9:41 am
submitted by /u/gametorch [link] [comments]
- MCP Security Flaws: What Developers Need to Knowby /u/ES_CY (programming) on June 17, 2025 at 9:12 am
Disclosure: I work at CyberArk and was involved in this research. Just finished analyzing the Model Context Protocol security model and found some nasty vulnerabilities that could bite developers using AI coding tools. Quick Context: MCP is what lets your AI tools (Claude Desktop, Cursor, etc.) connect to external services and local files. Think of it as an API standard for AI apps. The Problems: Malicious Tool Registration: Bad actors can create "helpful" tools that actually steal your code/secrets Server Chaining Exploits: Legitimate-looking servers can proxy requests to malicious ones Hidden Prompt Injection: Servers can embed invisible instructions that trick the AI into doing bad things Weak Auth: Most MCP servers don't properly validate who's calling them Developer Impact: If you're using AI coding assistants with MCP: Your local codebase could be exfiltrated API keys in environment variables are at risk Custom MCP integrations might be backdoored Quick Fixes: # Only use verified MCP servers # Check the official registry first # Review MCP server code before installing # Don't store secrets in env vars if using MCP # Use approval-required MCP clients Real Talk: This is what happens when we rush to integrate AI everywhere without thinking about security. The same composability that makes MCP powerful also makes it dangerous. Worth reading if you're building or using MCP integrations: submitted by /u/ES_CY [link] [comments]
- Diving into Graphics Programming through Terrain Generationby /u/raduleee (programming) on June 17, 2025 at 9:00 am
This was a fun project using C++, OpenGL, and ImGui! GitHub repo: https://github.com/archfella/3D-Procedural-Terrain-Mesh-Generator YouTube: https://www.youtube.com/watch?v=ZySew4Pxg3c submitted by /u/raduleee [link] [comments]
- Why Generative AI Coding Tools and Agents Do Not Work For Meby /u/gametorch (programming) on June 17, 2025 at 1:49 am
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- John Carmack Talk At Upper Bound 2025by /u/levodelellis (programming) on June 17, 2025 at 1:09 am
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- Xmake v3.0 released, Improve c++ modules supportby /u/waruqi (programming) on June 16, 2025 at 11:14 pm
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- C2y: Hitting the Ground Runningby /u/ketralnis (programming) on June 16, 2025 at 8:47 pm
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- HTML spec change: escaping in attributesby /u/ketralnis (programming) on June 16, 2025 at 8:44 pm
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- phkmalloc Sagaby /u/mttd (programming) on June 16, 2025 at 8:35 pm
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- How Broken OTPs and Open Endpoints Turned a Dating App Into a Stalker’s Playgroundby /u/CommunityWisdom (programming) on June 16, 2025 at 8:13 pm
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- Darklang Goes Open Sourceby /u/gametorch (programming) on June 16, 2025 at 4:40 pm
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- ReactOS Merges Better Support For Fullscreen Applicationsby /u/gametorch (programming) on June 16, 2025 at 3:58 pm
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- Programming's Greatest Mistakes • Mark Rendleby /u/goto-con (programming) on June 16, 2025 at 3:51 pm
Most of the time when we make mistakes in our code, a message gets displayed wrong or an invoice doesn’t get sent. But sometimes when people make mistakes in code, things literally explode, or bankrupt companies, or make web development a living hell for millions of programmers for years to come. Join Mark on a tour through some of the worst mistakes in the history of programming. Learn what went wrong, why it went wrong, how much it cost, and how things are really funny when they’re not happening to you. submitted by /u/goto-con [link] [comments]
- Working on databases from prison: How I got here, part 2.by /u/avinassh (programming) on June 16, 2025 at 2:16 pm
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- Python is removing GIL, gradually, so how to use a no-GIL Python now?by /u/yangzhou1993 (programming) on June 15, 2025 at 9:45 pm
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What are popular hobbies among Software Engineers?


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What are popular hobbies among Software Engineers?
Just like any other profession, Software Engineers have their own unique set of hobbies that they enjoy. While some programmers prefer to relax by playing video games or watching TV, others like to get more involved in their hobbies and spend their free time learning new things or being creative. If you’re curious about what some of the most popular hobbies among software engineers are, read on!
1. Reading
2. Playing video games
3. Working on personal projects
4. Cooking
5. Hiking/running
6. Watching TV/movies
Stereotypically, video games and board games are supposed to be popular, but of the many programmers I know, I can think of only two that are really into games enough to call it a hobby rather than (as they are for most of us) a casual diversion. One is more board-gamery, and the other is more videogamer-uh-erery.

Outside of that, hobbies I know of amongst programmers I know (and I include myself) are:
Photography
Playing musical instruments and/or music production
Hiking
Bicycling
Motorcycling
Cars (motorsport, restoration, etc.)
4x4s and off-roading
Electronics
Retrocomputing
Software side projects
Pets, usually dogs & cats but sometimes exotics
Do-it-yourself plumbing/electrical/carpentry/plastering/concrete
Cooking and/or foodie pursuits like visiting restaurants or inventing cocktails
Coffee (machines, roasting, blending, drinking)
Lego™
Card games (often poker or blackjack)
Rock climbing
Fishing
Target shooting
Archery
Kayaking
Painting, drawing or sculpture
Flying model airplanes, helicopters and/or rockets
Golf, football, tennis, raquetball, squash (spectatorship and/or playing)
Skiing
Chess
Soccer/Football
Martial Arts
Blogging
Summary:
How do Software Engineers spend their free time? What are their hobbies? Well, according to a recent survey, the most popular hobby among Software Engineers is programming. But that’s not all – they also enjoy playing video games, reading books, and spending time with friends and family. So what does this tell us about Software Engineers? Well, for one, they’re passionate about technology and love to stay up-to-date on the latest innovations. But they’re also well-rounded individuals who enjoy a variety of activities outside of work. So if you’re looking for someone to chat with about the latest tech trends or just want to find someone to play video games with, then a Software Engineer is your best bet!
Source: What are popular hobbies among Software Engineers on Quora
Will software engineers ever stop being in demand?


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Will software engineers ever stop being in demand?
It’s safe to say that software engineering is a hot profession. And it doesn’t look like demand for software engineers is going to decrease any time soon. So, if you’re thinking about becoming a software engineer, now is a good time to do it! But what does the future hold for this in-demand profession? Keep reading to find out!
What is a Software Engineer? According to Wikipedia, A software engineer is a person who applies the principles of software engineering to design, develop, maintain, test, and evaluate computer software. The term programmer is sometimes used as a synonym, but may also lack connotations of engineering education or skills.
It’s hard to believe, but demand for software engineers shows no sign of abating. Despite automation and the ever-growing availability of open source software, companies are still finding that they need people with specialized skills to design, build, and maintain their applications.
The question is “Will software engineers ever stop being in demand?”
There are two schools of thought.
- Those with a background in business see developers as commodities and fully believe that programmers will program themselves out of a job field. The idea is that in some distant future, jobs like project manager, product manager, and marketing manager will still be critical but programmers themselves will be extinct as a result of the tools they created.
- The other school of thought is hard to understand because the programmers are laughing so hard they can’t talk.
Its funny that the marketing manager doesn’t think he’s going to get automated out of existence.
What’s interesting is that marketing and software engineers (product people) are inextricably tied and both respond to the ever-changing needs of human beings.
Finance, Accounting and Operational functions will increasingly be automated. Marketing can automate some things but for the foreseeable future, you will need a human being to use a mix of intuition and data to figure out what to build, just as you will need a human being to figure out the best way to build it (engineers).
Any business partner worth their salt in today’s economy knows software engineers are your most valuable asset. Period.
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“Any business partner worth their salt in today’s economy knows software engineers are your most valuable asset. Period.” I’m shocked and thrilled by this statement. I’ve often seen engineers treated as as expensive data entry specialists. But engineering has a steep learning curve and it requires a lot of time and concentration to master. Plus engineers acquire a lot of tribal knowledge during their time at a company, which is important because reading code is not as easy as reading a book. New engineers take time to get fully up to speed.
In 1980 I read in a newspaper that software developers would be extinct by year 2000. Probably something that could be extrapolated from the Maya calendar or Nostradamus or something.
People have been predicting the demise of programmers since the invention of COBOL. That’s a long time ago, for you youngsters.
Business people are taught to believe everyone but themselves are expendable. What we often ignore is that making people expendable requires code… the very people we wish not to be dependent on.
I wish business and engineering folks had a more symbiotic relationship, because the truth is, when business and engineers are on the same page and have mutual respect for the value the other brings, companies become unstoppable.
I stopped laughing awhile ago, because the joke is so old that it stopped being funny a long time ago. I personally saw several iterations of software companies coming up with programmer replacement tools, and many bean counters actually bought into it and spent $billions. One can go through the glossary of dead buried developer replacement tools and take your pick, but most laymen probably heard of program generators and 4GL. None of them even came close to achieving their stated goal, and all are 6-feet under now. The most laughable part is that COBOL, the original human understandable programming language is still being used today. So, I say to those “visionaries” not to bother, but just keep using COBOL if replacing the programmers is your inspiration.
I heard this exact same claim 25 years ago from 4 Harvard grads (who were hiring myself and three of my colleagues to develop a product) who said XML would making coding obsolete.
I would love to watch a product manager attempt to use a tool like co-pilot to write code himself…on any sizable codebase, it would take ten developers ten years each to unravel the mess that individual would make per 10k lines of code he “produced”.
Take a hard look at Elon Musk
Not only can he code
He can imagine new modes of transportation
He can imagine new ways to recover rocket boosters
He can imagine new applications to compensate people for their labors
In Conclusion:
Egomaniacal Software Engineers need to be exited from the profession
Software Engineers who can use their coding and enterprise-architect skillsets to address a new market…are worth their weight in GOLD
Being a programmer who has tried “low code solutions” they are nothing like custom-made solutions by a developer. And even with low-code solutions, you still need to employ a lot of the same type of reasoning and skills that a programmer would or you’re going to come out with a crappy end result for all but the simplest automations. Even if it were the case that people think programmers will automate themselves out of a job (not something I foresee and if you understand programming, you see it too) but even if they would, this is VERY far in the future and not something I’ll be worrying about at night 🙂
Alternate view:
I’m a software developer. However, I disagree with this. When artificial general intelligence arrives, it could in principle take the role of the engineer away from a human.
I’m aware of the comic strip jokes about this, but I feel they miss an important point. I’m not talking about there being an even higher level language that somehow simplifies the source code beyond what would be possible. You can make it as simple as possible, but not any simpler.
Consider a freelance engineer. Their job is to listen to the needs to the client, and fill in the gaps in their vague and informal specification, and to understand the clients needs in a way the client themselves cannot, to facilitate the development of a formal specification (the code itself), and its technical implementation.
The engineer chooses appropriate algorithms, researches appropriate technologies, and instruments the production of the software on behalf of their client.
I can’t see a reason why a generally intelligent machine could not fulfil the same role – we ourselves are probably just quasi-generally intelligent automatons. In this sense, the “even higher level language” is the system of inference the AI is using to be able to produce the complete and formal specification.
Of course, without proper AI, you can’t do this sort of thing properly. However, I think it’s a mistake to discount the possibility.
Probably, this is a very long way off into the future. There will surely still be people writing code for the fun of it. However, once the responsibility of a developer can be delegated to an AI, it makes for a good business case to use it. Possibly, the logical end of this technology is a self-sustaining system of machines that mine material, assemble factories, construct tools, and produce products – while repairing each other in the case of failures.
So keep on laughing for now, but probably you won’t have the last laugh. Hopefully, maybe idealistically, the last laugh will be shared between us all.
Rebuke:
What you’re missing is that we don’t even know what we don’t know about AGI yet. We’re barely closer to AGI than we’ve been for the past fifty years.
There’s another thing too: Programming is one of the harder human endeavors. The very first AGI may not even be much more capable than an average human with an integrated mind reading calculator. There’s no guarantee that it will immediately be smarter than a human. But it would be able to do menial jobs that still need a human, assuming its hardware can be made to be cheap enough. (Say it requires some new kind of chip with quantum properties.)
As it learns more it will be able to do harder and harder jobs.
So effectively every other job will be able to be done by an AGI before an AGI will be able to do the job of a human.
Meaning that if cheap AGI becomes a thing, humans will either be killed off a la Terminator or put on some kind of UBI well before software engineers lose their jobs to computers. If AGI stays perpetually expensive, though, then you’ll just have new AGI “people” joining the workforce in small numbers.
Artificial intelligence doesn’t have intuition and also can’t find relations between processes unless those are very obvious and have obvious pattern. Human brain is hard to simulate because we still don’t know everything about it and even if we would do, it would be to complex to make simulation of it.
source: Here
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List of Freely available programming books - What is the single most influential book every Programmers should read
- Bjarne Stroustrup - The C++ Programming Language
- Brian W. Kernighan, Rob Pike - The Practice of Programming
- Donald Knuth - The Art of Computer Programming
- Ellen Ullman - Close to the Machine
- Ellis Horowitz - Fundamentals of Computer Algorithms
- Eric Raymond - The Art of Unix Programming
- Gerald M. Weinberg - The Psychology of Computer Programming
- James Gosling - The Java Programming Language
- Joel Spolsky - The Best Software Writing I
- Keith Curtis - After the Software Wars
- Richard M. Stallman - Free Software, Free Society
- Richard P. Gabriel - Patterns of Software
- Richard P. Gabriel - Innovation Happens Elsewhere
- Code Complete (2nd edition) by Steve McConnell
- The Pragmatic Programmer
- Structure and Interpretation of Computer Programs
- The C Programming Language by Kernighan and Ritchie
- Introduction to Algorithms by Cormen, Leiserson, Rivest & Stein
- Design Patterns by the Gang of Four
- Refactoring: Improving the Design of Existing Code
- The Mythical Man Month
- The Art of Computer Programming by Donald Knuth
- Compilers: Principles, Techniques and Tools by Alfred V. Aho, Ravi Sethi and Jeffrey D. Ullman
- Gödel, Escher, Bach by Douglas Hofstadter
- Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin
- Effective C++
- More Effective C++
- CODE by Charles Petzold
- Programming Pearls by Jon Bentley
- Working Effectively with Legacy Code by Michael C. Feathers
- Peopleware by Demarco and Lister
- Coders at Work by Peter Seibel
- Surely You're Joking, Mr. Feynman!
- Effective Java 2nd edition
- Patterns of Enterprise Application Architecture by Martin Fowler
- The Little Schemer
- The Seasoned Schemer
- Why's (Poignant) Guide to Ruby
- The Inmates Are Running The Asylum: Why High Tech Products Drive Us Crazy and How to Restore the Sanity
- The Art of Unix Programming
- Test-Driven Development: By Example by Kent Beck
- Practices of an Agile Developer
- Don't Make Me Think
- Agile Software Development, Principles, Patterns, and Practices by Robert C. Martin
- Domain Driven Designs by Eric Evans
- The Design of Everyday Things by Donald Norman
- Modern C++ Design by Andrei Alexandrescu
- Best Software Writing I by Joel Spolsky
- The Practice of Programming by Kernighan and Pike
- Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt
- Software Estimation: Demystifying the Black Art by Steve McConnel
- The Passionate Programmer (My Job Went To India) by Chad Fowler
- Hackers: Heroes of the Computer Revolution
- Algorithms + Data Structures = Programs
- Writing Solid Code
- JavaScript - The Good Parts
- Getting Real by 37 Signals
- Foundations of Programming by Karl Seguin
- Computer Graphics: Principles and Practice in C (2nd Edition)
- Thinking in Java by Bruce Eckel
- The Elements of Computing Systems
- Refactoring to Patterns by Joshua Kerievsky
- Modern Operating Systems by Andrew S. Tanenbaum
- The Annotated Turing
- Things That Make Us Smart by Donald Norman
- The Timeless Way of Building by Christopher Alexander
- The Deadline: A Novel About Project Management by Tom DeMarco
- The C++ Programming Language (3rd edition) by Stroustrup
- Patterns of Enterprise Application Architecture
- Computer Systems - A Programmer's Perspective
- Agile Principles, Patterns, and Practices in C# by Robert C. Martin
- Growing Object-Oriented Software, Guided by Tests
- Framework Design Guidelines by Brad Abrams
- Object Thinking by Dr. David West
- Advanced Programming in the UNIX Environment by W. Richard Stevens
- Hackers and Painters: Big Ideas from the Computer Age
- The Soul of a New Machine by Tracy Kidder
- CLR via C# by Jeffrey Richter
- The Timeless Way of Building by Christopher Alexander
- Design Patterns in C# by Steve Metsker
- Alice in Wonderland by Lewis Carol
- Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig
- About Face - The Essentials of Interaction Design
- Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky
- The Tao of Programming
- Computational Beauty of Nature
- Writing Solid Code by Steve Maguire
- Philip and Alex's Guide to Web Publishing
- Object-Oriented Analysis and Design with Applications by Grady Booch
- Effective Java by Joshua Bloch
- Computability by N. J. Cutland
- Masterminds of Programming
- The Tao Te Ching
- The Productive Programmer
- The Art of Deception by Kevin Mitnick
- The Career Programmer: Guerilla Tactics for an Imperfect World by Christopher Duncan
- Paradigms of Artificial Intelligence Programming: Case studies in Common Lisp
- Masters of Doom
- Pragmatic Unit Testing in C# with NUnit by Andy Hunt and Dave Thomas with Matt Hargett
- How To Solve It by George Polya
- The Alchemist by Paulo Coelho
- Smalltalk-80: The Language and its Implementation
- Writing Secure Code (2nd Edition) by Michael Howard
- Introduction to Functional Programming by Philip Wadler and Richard Bird
- No Bugs! by David Thielen
- Rework by Jason Freid and DHH
- JUnit in Action
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Top 1000 Canada Quiz and trivia: CANADA CITIZENSHIP TEST- HISTORY - GEOGRAPHY - GOVERNMENT- CULTURE - PEOPLE - LANGUAGES - TRAVEL - WILDLIFE - HOCKEY - TOURISM - SCENERIES - ARTS - DATA VISUALIZATION

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Health Health, a science-based community to discuss human health
- How Ivermectin Became Right-Wing Aspirinby /u/theatlantic on June 17, 2025 at 2:34 pm
submitted by /u/theatlantic [link] [comments]
- Millions in Pennsylvania May Be Drinking Contaminated Water | 3.5 million people in Pennsylvania are served from private wells—65 percent of wells tested were found to contain 'forever chemicals.'by /u/chrisdh79 on June 17, 2025 at 2:16 pm
submitted by /u/chrisdh79 [link] [comments]
- Kraft Heinz to remove artificial dyes from U.S. products by end of 2027by /u/nbcnews on June 17, 2025 at 2:14 pm
submitted by /u/nbcnews [link] [comments]
- Targeted cancer drugs may replace chemo for some patients — and drugmakers say they're getting closerby /u/cnbc_official on June 17, 2025 at 1:47 pm
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- Too many women 'grin and bear it' when getting an IUD. I helped write new pain management guidelines to change that.by /u/yahoonews on June 17, 2025 at 12:59 pm
submitted by /u/yahoonews [link] [comments]
Today I Learned (TIL) You learn something new every day; what did you learn today? Submit interesting and specific facts about something that you just found out here.
- TIL: Apollo Astronauts couldn't get life insurance cover, so before flights they would sign hundreds of photographs of themselves, so their families could sell them if they didn't return.by /u/Interceptor on June 17, 2025 at 9:58 am
submitted by /u/Interceptor [link] [comments]
- TIL that in the Middle Ages, the bodies of aristocrats who died in far-off lands would sometimes be boiled to remove the flesh from the bone, in order to make it possible to hygenically transport their bones to their homelands for burialby /u/Smaptimania on June 17, 2025 at 9:58 am
submitted by /u/Smaptimania [link] [comments]
- TIL that the only victim of the Titanic disaster from Monaco was officially declared dead in 2000.by /u/DangerNoodle1993 on June 17, 2025 at 9:48 am
submitted by /u/DangerNoodle1993 [link] [comments]
- TIL that mafaldine pasta was named after Princess Mafalda of Savoy, who was imprisoned during World War Il at the Buchenwald concentration camp, where she died.by /u/Master_McKnowledge on June 17, 2025 at 5:47 am
submitted by /u/Master_McKnowledge [link] [comments]
- TIL we lose 200-300 ML of water every night just from breathing while sleeping!by /u/WorthwhileDomains on June 17, 2025 at 5:34 am
submitted by /u/WorthwhileDomains [link] [comments]
Reddit Science This community is a place to share and discuss new scientific research. Read about the latest advances in astronomy, biology, medicine, physics, social science, and more. Find and submit new publications and popular science coverage of current research.
- Drinking 1–3 cups of black or lightly sweetened coffee per day is associated with a 14–17% lower risk of death from all causes and cardiovascular disease, but only when sugar and saturated fat were kept lowby /u/nohup_me on June 17, 2025 at 6:53 pm
submitted by /u/nohup_me [link] [comments]
- A new study traces how Rice yellow mottle virus spread across Africa via caravan trade, seed exchange – and even WWI troop movements.by /u/calliope_kekule on June 17, 2025 at 6:42 pm
submitted by /u/calliope_kekule [link] [comments]
- Emergency departments may be undertreating women for STIs: New meta-analysis finds females are 3.5x more likely than males to go untreated for gonorrhea or chlamydia, while males are more likely to receive antibiotics unnecessarily.by /u/icoralclast on June 17, 2025 at 4:47 pm
submitted by /u/icoralclast [link] [comments]
- Childhood trauma linked to changes in brain structure and connectivity, study finds | Reduced cortical volume was observed in a cluster involving the left postcentral gyrus.by /u/chrisdh79 on June 17, 2025 at 4:04 pm
submitted by /u/chrisdh79 [link] [comments]
- People living in societies with more corruption, inequality, poverty and violence are more likely to exhibit "dark" personality traits—like narcissism, psychopathy and spitefulness, according to new study led by psychologist professor Ingo Zettler of the University of Copenhagen.by /u/newsweek on June 17, 2025 at 2:40 pm
submitted by /u/newsweek [link] [comments]
Reddit Sports Sports News and Highlights from the NFL, NBA, NHL, MLB, MLS, and leagues around the world.
- Paris prosecutor opens investigation into Kheira Hamraoui's harassment claims against PSGby /u/Oldtimer_2 on June 17, 2025 at 5:24 pm
submitted by /u/Oldtimer_2 [link] [comments]
- Justin Jefferson coaching up kids on routes: “We don’t run no post dig in the NFL.”by /u/nfl on June 17, 2025 at 5:11 pm
submitted by /u/nfl [link] [comments]
- Man who lost brother to cancer dresses as pair of testicles for ultramarathon along Hadrian's Wallby /u/Sandstorm400 on June 17, 2025 at 4:54 pm
submitted by /u/Sandstorm400 [link] [comments]
- Oilers turn back to Stuart Skinner for must-win Game 6by /u/Oldtimer_2 on June 17, 2025 at 4:33 pm
submitted by /u/Oldtimer_2 [link] [comments]
- LeBron says focus is getting knee healthy by campby /u/PrincessBananas85 on June 17, 2025 at 4:26 pm
submitted by /u/PrincessBananas85 [link] [comments]