Francisco Manuel Soto Ramírez’s Post

Most programmers focus on writing code — but those who understand how that code becomes machine-executable often think and debug on a whole different level. A practical knowledge of compilation systems—from lexical analysis and parsing to code generation and optimization pays a lot when you are programmer.It gives you insight into what happens “under the hood.” It sharpens your ability to: ⚙️ Write more efficient & predictable programs 🐛 Understand compiler errors beyond surface messages 🚀 Optimize performance 🧠 Think like the compiler, not just the coder When you know how compilers translate high-level constructs into low-level instructions, you stop guessing and start reasoning with precision. It’s one of those invisible skills that quietly distinguishes excellent programmers from the rest. #Programming #SoftwareDevelopment #Debugging

Learned How To find Factorial Of A Number Using Recursion:- Code Summary :- I created a user defined function" fact" that will return an integer type value ( factorial of a number given by user) →Using Conditional Statements:- ▶️ If the number is 0 or 1 then it returns 1. ▶️If the number is greater than 1, then it will use recursion and will return value. If we take the number 5 then, →Function Calls:- 1st call:- return 5*fact(4) 2nd call:-5*4*fact(3) 3rd call:- 5*4*3*fact(2) 4 th call:-5*4*3*2*fact(1) Here the value of x becomes 1 and it returns 1 where the function was called last (i.e. in the else part of the user defined function "fact()") 5 th(Last):- return 5*4*3*2*1 It again returns to where last time the function was called (i.e. in the "int main") and displays answer 120. #cprogramming #engineering #coding

🚀 Build a new programming language in 3 months—with an #LLM The CURSED language by Gavin Huntley isn’t just a technical stunt. It’s a sign of a deep shift in what’s possible. https://lnkd.in/dwUD_xqx A few years ago, creating a new programming language took teams of experts, years of compilers, parsers, design docs, and formal proofs. Now? A single person + a large language model can prototype one in months. That’s not just speed. That’s leverage. It means that: • Creativity can scale faster than institutions. • Experimentation has become practical, not theoretical. • The bottleneck has moved from “Can I build this?” to “Should I build this?”

💡 Linked List — Deletion at the Beginning Let’s understand one of the simplest operations in a Linked List — deleting the first node. 🧩 How it works: The head pointer initially points to the first node (Node A). To delete it, we move the head to point to the second node (Node B). Node A is now disconnected and removed from the list. ✅ After Deletion: The list continues from Node B → Node C → ... → NULL. This operation helps us learn how memory links are updated and how dynamic data structures manage elements efficiently. 📘 A clear grasp of these basic concepts forms the foundation for more complex data structures and algorithms! #DataStructures #LinkedList #Programming #CodingBasics #ComputerScience #LearnCoding #Students

⚙️ 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗧𝗼𝗽𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗦𝗼𝗿𝘁 — 𝗧𝗵𝗲 “𝗢𝗿𝗱𝗲𝗿 𝗼𝗳 𝗗𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝗶𝗲𝘀” 𝗶𝗻 𝗚𝗿𝗮𝗽𝗵𝘀 Have you ever wondered how systems know what to execute first when everything seems connected? That’s where 𝗧𝗼𝗽𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗦𝗼𝗿𝘁𝗶𝗻𝗴 quietly powers the world of dependencies. 🧩 𝗧𝗵𝗲 𝗜𝗻𝘁𝘂𝗶𝘁𝗶𝗼𝗻 Imagine you’re building a project with tasks: Task A → Task B → Task C You can’t start B until A is done, and C depends on B. 𝗧𝗼𝗽𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗦𝗼𝗿𝘁 gives you the valid order to finish all tasks without breaking dependencies. This is why it’s used in: Build systems (like make, Maven, Gradle) Course scheduling problems Dependency resolution in compilers and package managers (like npm, pip, apt) ⚙️ 𝗪𝗵𝗮𝘁 𝗜𝘁 𝗜𝘀 A 𝗧𝗼𝗽𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗦𝗼𝗿𝘁 is a 𝗹𝗶𝗻𝗲𝗮𝗿 𝗼𝗿𝗱𝗲𝗿𝗶𝗻𝗴 𝗼𝗳 𝘃𝗲𝗿𝘁𝗶𝗰𝗲𝘀 in a 𝗗𝗶𝗿𝗲𝗰𝘁𝗲𝗱 𝗔𝗰𝘆𝗰𝗹𝗶𝗰 𝗚𝗿𝗮𝗽𝗵 (𝗗𝗔𝗚) where for every directed edge u → v, node u comes before v in the ordering. 🧠 𝗖𝗼𝗿𝗲 𝗜𝗱𝗲𝗮 There are two main approaches: 1️⃣ Kahn’s Algorithm (BFS-based) Find nodes with no incoming edges Process them, remove outgoing edges, and repeat Great for dependency graphs 2️⃣ DFS-based Approach Explore deeply and push nodes to a stack after visiting all neighbors Reverse the stack → gives the topological order 🧩 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 For the graph: A → C B → C C → D Valid topological orders could be: A, B, C, D or B, A, C, D (both satisfy all dependency directions) 🧠 𝗞𝗲𝘆 𝗣𝗿𝗼𝗽𝗲𝗿𝘁𝗶𝗲𝘀 ✅ Works only for 𝗗𝗶𝗿𝗲𝗰𝘁𝗲𝗱 𝗔𝗰𝘆𝗰𝗹𝗶𝗰 𝗚𝗿𝗮𝗽𝗵𝘀 (𝗗𝗔𝗚𝘀) ✅ Detects 𝗰𝘆𝗰𝗹𝗲𝘀 (if no valid ordering exists) ✅ Used in 𝗷𝗼𝗯 𝘀𝗰𝗵𝗲𝗱𝘂𝗹𝗶𝗻𝗴, 𝗯𝘂𝗶𝗹𝗱 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, 𝗰𝗼𝗺𝗽𝗶𝗹𝗲𝗿 𝗱𝗲𝘀𝗶𝗴𝗻 💬 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆 𝗧𝗼𝗽𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗦𝗼𝗿𝘁 teaches one of the most important lessons in engineering: “You can’t move forward without clearing your dependencies first.” Master this — and you’ll start seeing 𝗗𝗔𝗚𝘀 everywhere, from database migrations to async task queues. #DSA #Graph #TopologicalSort #Algorithms #ProblemSolving #SoftwareEngineering #Programming #TechCareer #FAANG #Coding #DataStructures #InterviewPreparation #100DaysOfCode #TechCommunity

Our lead developer quit and took 400 lines of "magic" code with him. The entire feature broke. No one could fix it. We were staring at a week of downtime and a panicked client. That was the day we banned "clever" code. Now, our #1 rule is: "Code must be readable enough that the newest intern can understand its core logic in 10 minutes." We document religiously. We write simple functions. We comment not on what the code does, but why it does it. It’s not the most "genius" code. But it’s indestructible. The most sophisticated systems aren't built on brilliance. They're built on clarity. Agree or disagree? #SoftwareDevelopment #Programming #Tech #Code #Engineering

Most engineers think AI in IDEs is just for generating code. I use Cursor to generate all documents for a project in minutes. The real productivity win? Navigating, exploring, and auditing code with AI while it writes it. I finish tasks faster, avoid errors, and save hours each week. IDEs aren't only about writing code. They are the productivity workstation for software engineers ♻️ REPOST to help someone today 👉 Follow strategizeyourcareer.com for more #softwareengineering #coding #programming

🚀 Day 49 of #100DaysOfLeetCode 🔄 Revision Day — Strengthening Binary Tree Fundamentals: ✅ LeetCode 94 — Binary Tree Inorder Traversal (Recursive & Iterative using Stack) ✅ LeetCode 102 — Binary Tree Level Order Traversal (BFS using Queue) ✅ LeetCode 236 — Lowest Common Ancestor of a Binary Tree (DFS + Recursion Insight) 💡 Pattern Insight: All three problems focus on tree traversal and recursive reasoning. Revisiting them reinforced the understanding of DFS vs BFS, recursion stack behavior, and node relationship tracking — vital for solving complex binary tree and graph problems efficiently. #LeetCode #100DaysOfCode #DSA #ProblemSolving #Coding #CodeNewbie #LearnToCode #MAANG #Programming #DataStructures #Algorithms #Tech #CodingJourney #SoftwareEngineering #CompetitiveProgramming

On Day 289 of my #300daysofcode challenge, I'm sharing my solution to LeetCode Problem 3370, "Maximum Length of Semi-Decreasing Subarrays III." This complex problem is a great test of optimization skills. My video provides a clear walkthrough of the most efficient approach (likely involving Two Pointers or a Monotonic Stack), which is a valuable skill for advanced technical interviews and a great way to think about improving time complexity. #DataStructures #Algorithms #LeetCode #CodingInterview #Programming #Optimization #300daysofcode

🧠 𝗛𝗼𝘄 𝗮 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗖𝗼𝗺𝗽𝗶𝗹𝗲𝗿 𝗪𝗼𝗿𝗸𝘀 𝗥𝗲𝗰𝗲𝗻𝘁𝗹𝘆, I’ve been diving deep into compiler design, and it’s been fascinating to understand how our high-level code turns into something the computer can actually execute! From what I’ve learned, a compiler typically goes through six main stages: 𝟭. 𝗦𝗼𝘂𝗿𝗰𝗲 𝗖𝗼𝗱𝗲 📝  This is where we write our program in a human-readable programming language like C++, Go, or Rust. 𝟮. 𝗟𝗲𝘅𝗶𝗰𝗮𝗹 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 (𝗟𝗲𝘅𝗲𝗿) ✂️  The lexer takes the source code and breaks it down into small units called tokens (keywords, identifiers, operators, etc.). 𝟯. 𝗦𝘆𝗻𝘁𝗮𝘅 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 (𝗣𝗮𝗿𝘀𝗲𝗿) 🌳  The parser organizes these tokens into a structured form called an Abstract Syntax Tree (AST), representing the grammatical structure of the code. 𝟰. 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 ✅  This step checks whether the AST makes logical sense — verifying things like type correctness, variable declarations, and function definitions. 𝟱. 𝗜𝗻𝘁𝗲𝗿𝗺𝗲𝗱𝗶𝗮𝘁𝗲 𝗥𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 (𝗜𝗥) ⚙️  The compiler then transforms the AST into an intermediate code (like LLVM IR), which serves as a bridge between high-level languages and machine code. This layer also enables cross-language interoperability. 𝟲. 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗖𝗼𝗱𝗲 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 & 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 🚀  Finally, the compiler converts the IR into optimized machine code (binary), which the CPU can execute directly. Toolchains like LLVM handle much of this optimization process. Compilers are truly one of the most elegant pieces of engineering — translating human logic into machine instructions with precision and efficiency! 💡 #Programming #CompilerDesign #ComputerScience #LLVM #SystemsProgramming #LearningJourney