C++26 Changes: Input-Only Views and Pipeline Correctness

Here is an article about Type Punning in C/C++. What it is and why we should care as developers doing low-level engineering It discusses a possible case that could fail under the umbrella of optimisation in production code. Feel free to share your thoughts! #LowLevel #EmbeddedSystems #UndefinedBehavior #StrictAliasing #SoftwareEngineering

🚀 One small C++ mistake that can silently hurt performance I used to write this confidently: return std::move(obj); Thinking: “I’m forcing a move → this must be faster.” ❌ But in modern C++ (C++17+), this can be WRONG When you write: return obj; 👉 The compiler can apply RVO (Return Value Optimization) 👉 The object is constructed directly in the caller 👉 No copy. No move. Zero overhead. ⚠️ What happens with std::move? return std::move(obj); Now you are telling the compiler: “No RVO. Treat this as an rvalue.” 👉 RVO is disabled 👉 A move constructor is forced 👉 Extra step added 🧠 So the irony is: “Optimized” code → slower “Simple” code → faster 💡 Rule I follow now Never use std::move in return unless you really know why. 🔥 Takeaway Modern C++ is smart. Sometimes the best optimization is: Do less. Let the compiler do more. #cpp #moderncpp #performance #softwareengineering #developers

I used to add std::move everywhere to "optimise" my C++. Turns out... I was sometimes making things slower. Two surprising cases: 1. It can block compiler optimisations. For instance, this: return std::move(local); can prevent Named Return Value Optimisation (NRVO/RVO) because it forces the compiler to treat local as an rvalue, preventing it from eliding the copy/move entirely. So instead of zero-cost, I was forcing an extra move. 2. It is pointless for small types. For trivially copyable types, moving is effectively the same as copying. Example: struct Point { int x,y; } Point a{1,2}; Point b = std::move(a); //no real gain since a is effectively copied We are not saving anything here; in fact, it could potentially add extra noise. One big takeaway for me is: std::move is not an optimisation, it is more of a signal. It tells the compiler "I am done with the object, you can steal its resources". So now, I only use it when it actually matters, such as types that own heap memory. What surprised you most about std::move when you learned it properly? #CPlusPlus #optimization #moderncpp

🚀 5 Modern C++ Practices That Will Save You Hours of Debugging After reviewing hundreds of C++ codebases and mentoring dozens of developers, I’ve noticed the same costly patterns repeating. The good news? Most are easy to fix once you know what to look for. Here are 5 practical tips that will immediately improve your C++ code – whether you're on C++17, C++20, or already experimenting with C++23. 1. Prefer std::unique_ptr over raw new/delete Not just for safety – it makes ownership explicit and eliminates whole classes of memory leaks. Your future self (and your code reviewers) will thank you. 2. Use constexpr and consteval aggressively Move computation to compile time when possible. It’s not just about performance – it catches errors earlier and makes intent crystal clear. 3. Stop writing raw loops <algorithm> + lambdas often produce clearer, safer, and sometimes faster code. std::transform, std::find_if, and std::accumulate are your friends. 4. Embrace std::optional and std::variant Replace output parameters (bool + reference) and error-prone unions. Your function signatures become self-documenting. 5. Turn on all warnings and treat them as errors -Wall -Wextra -Wpedantic -Werror (or the MSVC equivalent). This single change catches more bugs than any linter. Bonus: Run your tests under AddressSanitizer and UndefinedBehaviorSanitizer weekly. The hidden issues you’ll find are often the ones that would have exploded in production. I’ve written a deeper dive with code examples and before/after comparisons – here down you can view it and dowload it. What’s one C++ practice that changed how you write code? Let’s discuss below. 👇

Every C++ developer eventually encounters a memory leak. You allocate something on the heap, write some logic, hit an early return at runtime and suddenly that heap memory is gone forever. https://lnkd.in/dYsWQari

C++26 will introduce 𝗿𝗲𝗳𝗹𝗲𝗰𝘁𝗶𝗼𝗻 and we are all very excited about it. But there currently exist many 𝗹𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀 that offer reflection for C++, how is that possible? Most of them use the __𝗣𝗥𝗘𝗧𝗧𝗬_𝗙𝗨𝗡𝗖𝗧𝗜𝗢𝗡__ compiler trick. This trick has been around for quite a while in modern compilers like GCC, Clang and MSVC and it’s very useful for this situation. It basically prints a string with 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻 𝘀𝗶𝗴𝗻𝗮𝘁𝘂𝗿𝗲 information at compile time. With some 𝘁𝗲𝗺𝗽𝗹𝗮𝘁𝗲 𝗺𝗲𝘁𝗮𝗽𝗿𝗼𝗴𝗿𝗮𝗮𝗺𝗶𝗻𝗴 techniques (like really heavy machinery) it is actually possible to achieve a functional reflection for pre-C++26 standards. It’s limited, but kind of works for lot of situations. The trick itself is 𝗻𝗼𝘁 𝗳𝘂𝗹𝗹𝘆 𝗽𝗼𝗿𝘁𝗮𝗯𝗹𝗲 and must be used carefully, as every compiler produces different output formats. Luckily, some developers have already squeezed this into heavily templated, ready-to-use libraries that do all the hard work for you. C++26 reflection will likely replace these approaches with a 𝘀𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝗶𝘇𝗲𝗱 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻. Until then, this is what “reflection” in modern C++ looks like in practice. reflect-cpp: https://lnkd.in/ejaVevUa magic enum: https://lnkd.in/eK4tPPPe #cpp #c #cplusplus #modernc #moderncpp #cpp17 #cpp20 #cpp23 #cpp26 #coding #code #programming #reflection #array #pointer #arithmetic #typesafety #tech #future #embedded #software #firmware #cleancode #distributed #systems #compiler #gcc #clang #msvc

🚫 Stop passing 𝒄𝒐𝒏𝒔𝒕 𝒔𝒕𝒅::𝒔𝒕𝒓𝒊𝒏𝒈& when you don't need to. There's a better way, and it's been in C++17 since 2017. Meet 𝒔𝒕𝒅::𝒔𝒕𝒓𝒊𝒏𝒈_𝒗𝒊𝒆𝒘. Here's a classic mistake I see in C++ codebases. When you pass "hello" to a 𝒄𝒐𝒏𝒔𝒕 𝒔𝒕𝒅::𝒔𝒕𝒓𝒊𝒏𝒈&, the runtime silently allocates a new 𝒔𝒕𝒅::𝒔𝒕𝒓𝒊𝒏𝒈. With 𝒔𝒕𝒓𝒊𝒏𝒈_𝒗𝒊𝒆𝒘? Nothing. Zero overhead. It's just a pointer + length pair pointing to an existing buffer. Where it really shines is substring parsing, no new, no heap, no copy. You're just sliding a window over existing memory. 🧠 Key insight: 𝒔𝒕𝒓𝒊𝒏𝒈_𝒗𝒊𝒆𝒘 is perfect for read-only string processing parsers, tokenizers, log analyzers, and protocol handlers. Anywhere you're slicing and inspecting strings without modifying them. Two caveats worth knowing: · Don't store a 𝒔𝒕𝒓𝒊𝒏𝒈_𝒗𝒊𝒆𝒘 if the underlying string can be destroyed, dangling reference territory. · It's non-owning by design. That's the whole point. Available since C++17. If you're not using it, you're leaving free performance on the table. This is Day 1 of my C++ deep-dive series. Follow along if you want to write faster, leaner C++. What's your go-to use case for string_view? Drop it below 👇 #cpp #cplusplus #programming #softwareengineering #performanceprogramming

Built a Multithreaded Matrix Library in C++ Yesterday, I implemented a custom matrix class from scratch in C++, focusing on both correctness and performance. Key highlights: • Implemented full Rule of 5 (copy/move semantics) • Designed cache-friendly contiguous memory layout • Added operator overloading for intuitive usage • Built multithreaded matrix multiplication using std::thread • Handled thread partitioning and hardware concurrency properly Then I benchmarked it Matrix Size → Time (Multithreaded) • 800 × 800 → ~0.25 sec • 1000 × 1000 → ~0.50 sec • 10000 × 10000 → ~571 sec Some interesting takeaways: • Performance scales roughly with O(n³) as expected • Multithreading helps, but memory bandwidth becomes the bottleneck at large sizes • Proper data layout (contiguous memory) is critical for performance This was a great exercise in: • Systems-level thinking • Concurrency in C++ • Performance engineering #Cplusplus #Multithreading #Performance #SystemsProgramming #LearningInPublic

Mutex might sound like the solution here, but you also essentially lose the parallelism by making the thread wait for other threads to finish work. Things LIKE atomics should be considered the defacto answer, mutexes are a last resort.