Understanding Double Pointers in C Programming

🚀 Day 111 of #160DaysOfCode ✅ Topic: Dynamic Programming — Longest String Chain 💡 Platform: GeeksforGeeks (Problem: Longest String Chain) 🧠 Concept Learned: Today I solved the Longest String Chain problem using Dynamic Programming. The goal was to find the longest sequence of words where each word can be formed by adding exactly one letter to the previous word, without changing the order of characters. 📘 Approach Used: Sort all words by length (shorter first). Use a dictionary (dp) to store the longest chain ending at each word. For each word, generate all possible predecessors by removing one character at a time. If the predecessor exists in dp, update: dp[word] = max(dp[word], dp[pred] + 1) Keep track of the maximum chain length in res. 🧩 Example: Input: ["a", "b", "ba", "bca", "bda", "bdca"] Output: 4 Explanation: The longest chain is a → ba → bda → bdca ✅ Result: All test cases passed (1114 / 1114) 🎯 Understood how sorting + dynamic programming + string manipulation can be combined to solve complex sequence problems efficiently.

🚀 Day 61 of #100DaysOfLeetCodeHard — LeetCode 1320: Minimum Distance to Type a Word Using Two Fingers (Hard) My Submission:https://lnkd.in/gdAy6ski Today’s problem was a 5D Dynamic Programming challenge that tested both spatial intuition and state management in recursion. The task was to minimize the total distance required to type a given string on a 2D keyboard using two fingers. Each key has a coordinate on a 6-column grid, and each finger can independently move across the board. 💡 Approach: I defined the state as: dp[ind][x1][y1][x2][y2] → the minimum cost to type from index ind when first finger is at (x1, y1) second finger is at (x2, y2) At each step, I explored both possibilities: Typing the next letter with the first finger, Typing it with the second finger, and recursively computed the minimal total cost. 📘 Key Concepts: Multi-dimensional DP with recursion + memoization Manhattan distance calculation Handling base conditions and free initial finger placement ⏱️ Time Complexity: ~O(n × 6⁴) (optimized with memoization) 💾 Space Complexity: O(n × 6⁴) This problem was one of the most state-heavy DP problems I’ve done so far — but once the transitions clicked, it turned out to be a very elegant solution! 💪 #LeetCode #DynamicProgramming #Recursion #ProblemSolving #C++ #100DaysOfCode #LearningEveryday #CodingChallenge

⚔️ C# — Class vs Struct vs Record (Real Difference Explained) Most devs confuse these three — here’s a simple breakdown that actually makes sense 👇 🧱 Class Reference Type (stored on Heap) Compared by Reference Supports Inheritance & Polymorphism Usually Mutable 🧩 Best For: Objects with behavior + identity that change over time. ⚙️ Struct Value Type (stored on Stack) Copied by Value ❌ No Inheritance Lightweight & performs better for small data 🧩 Best For: Small, fast, independent data like points, colors, coordinates. 🧾 Record Reference Type (C# 9+) Compared by Value Mostly Immutable Supports Record-to-Record inheritance 🧩 Best For: Data models / DTOs where value equality matters. 🧱 Class → Logic + Behavior ⚙️ Struct → Lightweight + Performance 🧾 Record → Immutable + Data-Centric #CSharp #DotNet #DotNetDevelopers #Programming #CleanCode #SoftwareEngineering #CodingTips #Developers #TechCommunity

Made my own programming language in C++ and it’s called Rivet. It includes: > A Lexer (tokenizer) > A Recursive Descent Parser > An Abstract Syntax Tree (AST) > An Interpreter that executes AST nodes directly Features: > Variables (let and var for immutability/mutability) > Numbers, Booleans, Strings, and Arrays > Arithmetic and logical expressions (+ - * / && ||) > If / Else conditionals > While loops > C-style For loops (for (var i = 0; i < 10; i = i + 1)) > For-in loops for arrays and strings (for x in arr { ... }) > Functions and return values > Print statement > Nested scopes and lexical environments Took a day of lexer-parser pain and “why won’t this semicolon die” moments but now it runs its own code and I’m unreasonably proud of it. Check it out link in the comments!

🚀 Understanding Data Types in C Programming In C programming, data types define the type of data a variable can hold. They help the compiler understand how much memory to allocate and what kind of operations can be performed on the data. 🧩 Main Categories: Primary Data Types – int, float, char, double Derived Data Types – array, pointer, structure, union Enumeration Data Type (enum) Void Type – represents no value 💡 Example: int age = 25; // Integer type float salary = 50000; // Floating-point type char grade = 'A'; // Character type Each data type plays a crucial role in writing efficient, type-safe, and memory-optimized C programs. If you understand data types well, you understand half of C programming! #CProgramming #CodingBasics #ProgrammingTips #LearnToCode #DataTypes #SoftwareDevelopment #TechLearning #CodeWithC #BeginnersGuide #CProgrammer

Day 13 of #100DaysOfCode Today, I explored one of the most powerful tools in C++ — the Standard Template Library (STL). 💡 STL is like a treasure chest for developers — it provides ready-to-use data structures and algorithms that make coding more efficient and elegant. Here’s what I learned today: ✅ Containers like vector, list, set, and map — to store and manage data effectively. ✅ Iterators — to traverse elements just like pointers. ✅ Algorithms — for operations such as sorting, searching, and reversing with just one line of code. ✅ How STL helps in writing cleaner, faster, and more reusable code. Understanding STL feels like unlocking superpowers in C++ — it truly saves time and effort in solving complex problems! 💪 #100DaysOfCode #CPlusPlus #STL #LearningEveryday #CodingJourney #ProblemSolving #DevelopersJourney

*I recently developed a Python-based Expense Tracker as part of my practice to strengthen core programming fundamentals. The application allows users to: *Add and store daily expenses *Display all recorded expenses in a clean tabular format *Calculate total expenses categorized by type (e.g., food, travel, etc.) Key concepts applied: *File handling for data storage and retrieval *String formatting for structured console output *Use of dictionaries to aggregate category-wise totals *Modular programming through function-based design This project helped reinforce my understanding of Python data processing and user interaction workflows. I plan to further enhance it with a Tkinter GUI and possibly migrate the storage layer to SQLite for more robust data management. Always working to improve — one project at a time. #Python #Learning #Programming #Projects #SoftwareDevelopment

🤔 Ever Wonder Why malloc() and Memory APIs Return void*? In C, malloc() returns a void* and that’s not just a random design choice. It’s one of the most elegant examples of type abstraction in system programming. Here’s the logic behind it 👇 🧠 1️⃣ The purpose of void* void* is a generic pointer type that can point to any data type. This means malloc() doesn’t need to know what you’ll store integers, structs, or arrays it simply hands you a chunk of raw memory. int *arr = (int *)malloc(10 * sizeof(int)); The cast tells the compiler what type of data you plan to use that memory for. ⚙️ 2️⃣ Consistency across memory APIs Other allocators like calloc(), realloc(), and even system-level functions (mmap(), kmalloc(), etc.) return void* too. This keeps memory allocation universal and reusable across various contexts. 🚫 3️⃣ Why C++ handles it differently C allows implicit conversion from void* to any pointer type. C++ doesn’t it enforces an explicit cast for stronger type safety, preventing subtle pointer-type mismatches. ⚡ Takeaway: Returning void* makes memory APIs generic, flexible, and language-agnostic a simple idea that keeps C powerful after all these years. #CProgramming #EmbeddedSystems #MemoryManagement #FirmwareDevelopment #SystemProgramming #LinuxKernel

𝐇𝐨𝐰 𝐝𝐨 𝐚𝐬𝐬𝐨𝐜𝐢𝐚𝐭𝐞𝐝 𝐭𝐲𝐩𝐞𝐬 𝐬𝐢𝐦𝐩𝐥𝐢𝐟𝐲 𝐠𝐞𝐧𝐞𝐫𝐢𝐜 𝐩𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠? In generic programming, we often need to define a link between related types. For instance, modeling a repository that produces a certain kind of entity. Associated types make this possible by expressing that relationship directly within a trait or concept. This allows the compiler to enforce consistency without requiring extra template or generic parameters. Without associated types, we’d end up with more verbose and repetitive code that’s harder to read and maintain. 🔹 In C++, associated types are usually modeled using nested type aliases combined with concepts. In the example below, the 𝙍𝙚𝙥𝙤𝙨𝙞𝙩𝙤𝙧𝙮 concept requires any type 𝙏 to define a nested type 𝙀𝙣𝙩𝙞𝙩𝙮 and to provide a 𝙂𝙚𝙩() method returning that 𝙀𝙣𝙩𝙞𝙩𝙮. This expresses a clear compile-time relationship between the repository and its data type. The compiler verifies this contract, ensuring that 𝙋𝙧𝙞𝙣𝙩𝙀𝙣𝙩𝙞𝙩𝙮() can safely call 𝙂𝙚𝙩() and handle the returned type. 🔸 In Rust, associated types are built directly into the language and form part of a trait’s definition. Instead of defining a nested alias, the trait declares an internal type that each implementation specifies. This makes the relationship between the trait and its concrete type explicit, without repeating type parameters or extra syntax. ⚖️ In short, both C++ and Rust can represent relationships between types. Understanding associated types can help create cleaner and more expressive generic abstractions. #CppToRustJourney #ModernCpp #RustLang #GenericProgramming #SoftwareArchitecture