A practical mental model for estimating how many steps it takes to reduce a search space using binary search. This method skips log math and instead uses zero-chunking and power-of-two intuition to quickly home in on the answer.
A reference list of the most common patterns in DS&A problems, including hashmaps, two pointers, DFS/BFS, dynamic programming, and more. Useful for interviews, practice, or competitive programming prep.
This section isn’t about data structures and algorithms — it’s about surviving the system. Tips and patterns to help you finish implementation before time runs out, even when your engineering instincts are working against you.
In technical interviews and problem-solving scenarios, the programming paradigm you apply can often matter more than the language itself. This article explores how problem types align with paradigms, how languages express them, and why flexibility in approach is a more valuable asset than syntax memorization.
DSA and Big-O notation aren't just for interviews — they directly impact real-world performance and costs, from serverless runtime billing to optimizing data pipelines. This article explores their practical value through personal experience and potential demos.
You’ve spent years writing clean, modular, maintainable code — but Leetcode problems often demand something different. Here’s how to walk the line between speed and sanity when solving problems under pressure.