Why I still value my early C projects. 🛠️ High-level frameworks like Java Collections may be fast, efficient and powerful, but understanding the foundations is what makes a developer truly versatile. Back in 2022-23, I spent weeks building out core DSA models: Stacks, Queues, Graphs, and Dictionaries - using nothing but C. I decided to polish the README and make this personal archive a public repo. What’s inside: 🔹 Modular C logic (Models, Headers, and Runners). 🔹 Manual implementation of BST, Stack, Queue & Graph. 🔹 A straightforward look at memory and structure. It’s not over-engineered or complex; it’s just honest, foundational logic. If you’re practicing for interviews or just want to see how these structures look without the abstraction, feel free to explore and share your suggestions! Repo: https://lnkd.in/d9uspV6Z #Programming #ComputerScience #DSA #C

#Day-2 of 30 Days/30 Posts challenge. 👉 upgrading the C++ advanced concepts.... 💢 Tired of C++ initialization headaches? 😵💫 C++11 Uniform Initialization is your cure! C++11 didn’t just add features—it changed how we write C++. One feature that looks simple but is incredibly powerful: Uniform Initialization {} Before C++11, initialization was inconsistent and confusing: int x = 10; int x(10); int x = {10}; Now, with uniform initialization, we can use a single, consistent syntax: 👉 int x{10}; 💡 Why it matters: Prevents narrowing conversions (safer code) Makes initialization consistent across types Improves readability 🔹 Types of Uniform Initialization 👉 1. Direct Initialization int x{10}; 👉 2. Copy Initialization int x = {10}; 👉 3. Value Initialization int x{}; (Default initializes → x = 0) 👉 4. List Initialization (for containers) std::vector<int> v{1, 2, 3}; ⚠️ Important Insight Uniform initialization prevents unsafe conversions: int x{10.5}; // ❌ Error (narrowing not allowed) This is a big win for safety. 🧠 My takeaway What seems like a small syntax change actually enforces: 👉 Safer code 👉 Cleaner design 👉 Consistency across the language Modern C++ isn’t just about writing code—it’s about writing correct and expressive code. Still exploring more of C++11, one feature at a time 🚀 #CPP #ModernCPP #CPlusPlus #Programming #SoftwareEngineering #LearningJourney

🔹 Part 1: SFINAE in C++ This short video is part of my "C++ Programming Topics" series 👇 And also included in my broader C++ templates playlist. 💡 The problem: Many developers struggle with controlling which template functions should participate in overload resolution. This can lead to: -Confusing compiler errors -Unintended function matches -Less robust generic code ❌ 📌 This is where SFINAE becomes powerful: 👉 Substitution Failure Is Not An Error allows the compiler to silently discard invalid template instantiations. 💡 The solution: Applying SFINAE techniques to a simple example: int sum(int a, int b) { return a + b; } ✔️ Constrain templates to valid types only ✔️ Prevent invalid overloads from compiling ✔️ Write safer and more expressive generic code ⚙️ Bonus insight from the video: You’ll see how SFINAE works step by step by evolving this basic function: 1️⃣ Basic function behavior Understand the baseline implementation 2️⃣ Applying SFINAE Control when the function is enabled 3️⃣ Safer templates Restrict usage to valid type combinations 🎯 Key takeaway: SFINAE helps you guide the compiler instead of fighting it. It’s a foundational technique for mastering modern C++ templates. 🎥 Watch the video: https://lnkd.in/d7zPHDzb 📚 Full playlist: https://lnkd.in/dDNVWvVC #cpp #moderncpp #programming #softwareengineering #templates #cleancode

✨ extern "C": Use C++ with C extern "C", is a powerful feature that allows C programs to be able to call functions written in C++. Learn more about how this exactly works and how to use it. https://lnkd.in/ghmTHS7i #CProgramming #Development #CPP

🔹 Type Deduction in C++ (auto, decltype) This short video is part of my "C++ Programming Topics" series 👇 And also included in my broader learning playlist. 💡 The problem: Many developers either over-specify types or rely on guesswork when writing modern C++ code. This can lead to: -Verbose and harder-to-read code -Subtle bugs when types are not what you expect -Reduced flexibility when refactoring ❌ 📌 This is where type deduction becomes powerful: 👉 Let the compiler infer the correct type safely and efficiently. 💡 The solution: Using modern C++ features like auto, decltype, and template deduction: ✔️ Write cleaner and more concise code ✔️ Reduce redundancy ✔️ Let the compiler handle complexity ⚙️ Bonus insight from the video: You’ll see how type deduction works in different scenarios: 1️⃣ auto Great for simplifying variable declarations Improves readability when types are obvious 2️⃣ decltype Useful when you need the exact type of an expression Helps in advanced template and generic programming 3️⃣ Template Type Deduction The core concept behind generic programming Enables flexible and reusable code 🎯 Key takeaway: Don’t fight the compiler—use it. Modern C++ gives you tools to write cleaner, safer, and more maintainable code. 🎥 Watch the video: https://lnkd.in/dZSDe2Pi 📚 Full playlist: https://lnkd.in/dDNVWvVC 📚 Source code, examples, and notes: https://lnkd.in/dy2Kp-4f #cpp #moderncpp #programming #softwareengineering #templates #cleancode

Day 102: The Two-Finger Typing Grind ⌨️✌️ Problem 1320: Minimum Distance to Type a Word Today’s solve was about minimizing movement on a 6×5 keyboard layout. The Strategy: • Optimization via Savings: Instead of just calculating distance, I used Dynamic Programming to find the maximum "cost saved" by utilizing a second finger. • Efficient DP State: dp[c] tracks the max distance saved with the second finger at character c, allowing me to find the optimal path in a single pass. By focusing on "distance saved" rather than "total cost," the logic becomes much faster and cleaner. Day 102—keep optimizing. 🚀 #LeetCode #Java #DynamicProgramming #Algorithms #DailyCode

🚀 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. 👇

🔹 Part 1: C++ Concepts vs SFINAE (Practical Guide) This short video is part of my "C++ Programming Topics" series 👇 And also included in my broader C++ templates playlist. 💡 The problem: SFINAE is powerful—but it often leads to complex, hard-to-read template code. This can cause: -Cryptic compiler errors -Reduced code clarity -Higher learning curve for maintainers ❌ 📌 This is where C++20 Concepts shine: 👉 They provide a clean and expressive way to constrain templates. 💡 What you’ll learn in this video: ⚙️ Step-by-step evolution from SFINAE to Concepts: 1️⃣ Using enable_if in template parameters A cleaner alternative than putting it in the return type 2️⃣ Constraining a template class (Wrapper) Allow only integral types using SFINAE 3️⃣ Generic sum function Handle different types and control the return type 4️⃣ Concepts vs SFINAE Clear comparison in readability and maintainability 5️⃣ Writing your own concept Define a requirement for types that support add and sub 6️⃣ Combining Concepts with type_traits Reuse existing utilities for powerful constraints 🎯 Key takeaway: Concepts don’t replace SFINAE—they simplify it. Use Concepts when readability matters, and SFINAE when you need lower-level control. 🎥 Watch the video: https://lnkd.in/dpiQNQcF 📚 Full playlist: https://lnkd.in/dDNVWvVC #cpp #moderncpp #programming #softwareengineering #templates #concepts #metaprogramming #cleancode

What is Escape Analysis in Go Today I learned about an important concept in the Go programming language called Escape Analysis. Escape Analysis is a process used by the Go compiler to decide where a variable should be stored, either in the stack or in the heap. If a variable is used only inside a function, it stays in the stack and is removed when the function execution is completed. But if a variable is needed outside the function (for example, returning its address), it cannot safely stay in the stack. In that case, the compiler moves it to the heap. This is called “escape to heap”. If a value is returned normally (by value), Go simply copies the value, so no escape happens. In simple terms, Go automatically manages memory by deciding whether a variable should stay in the stack or move to the heap using Escape Analysis.

Beyond std::thread: The C++20 Multithreading Revolution. -------------------------------------- C++20 represents a watershed moment for multithreading in the language. While C++11 gave us a solid foundation with std::thread, mutexes, and condition variables, C++20 has addressed many of the pain points that made concurrent programming error-prone and verbose. The headline feature—std::jthread—brings automatic resource management and standardized thread cancellation to the table. But the story doesn't end there: new synchronization primitives (std::latch, std::barrier, std::counting_semaphore), atomic wait/notify operations, and synchronized output streams collectively transform how we write robust, maintainable concurrent code. Read more ... https://lnkd.in/daj3hUNU