DSA Articles
18 articles on DSA
Why You Keep Failing Technical Interviews Despite Solving 200 LeetCode Problems
The problem isn't how many problems you've solved. It's everything else — how you think out loud, handle pressure, communicate trade-offs, and recover from being stuck. This article fixes all of it.
Sorting Algorithms: When to Use Which, and Why Interviewers Still Ask About Them
You'll never implement bubble sort in production. But sorting interviews are about demonstrating algorithmic thinking — trade-offs, stability, in-place vs extra space. This guide covers every sorting algorithm you need, with real code and the exact interview questions they unlock.
The Binary Search Playbook: Every Variation You'll Ever See in Interviews
Binary search breaks every student's confidence at some point. This guide gives you one template to rule them all, then shows you every variation — first/last occurrence, rotated arrays, search on answer space — with working code.
Linked Lists: Every Pattern You Need, With the Pointer Diagrams Nobody Draws
Linked list problems trip up students because pointer manipulation is unforgiving — one wrong assignment and you've lost the rest of the list. This guide teaches every linked list pattern with step-by-step pointer diagrams so you never lose track again.
5 Patterns That Crack 90% of DSA Interview Questions
Most DSA problems are variations of just 5 core patterns. Learn them once, and you can solve hundreds of problems — even ones you've never seen before.
Monotonic Stack and Deque: The Pattern Behind 15 Hard Interview Problems
Monotonic stacks and deques look intimidating but follow one simple rule. Once you see it, you'll recognise the pattern in problems you previously thought required brute force. Full implementations of every variant.
The Recursion Mindset: How to Stop Being Scared and Start Thinking Recursively
Most students fear recursion because they try to trace through every call mentally. This article gives you the mindset shift that makes recursion click — plus a template that works for every recursive problem.
Tries Explained: The Data Structure That Makes String Search Instant
A trie turns word search, autocomplete, and prefix matching from O(n×m) into O(m). This guide builds one from scratch, then shows every interview problem it unlocks — from word search to IP routing.
Time Complexity Explained: From O(1) to O(n²) With Real Code Examples
Time complexity is the single most important concept in DSA interviews. This guide teaches you to calculate and compare complexities with real Python examples — no maths degree required.
Graph Algorithms Complete Guide: BFS, DFS, Dijkstra, and Union-Find Explained
Graphs are the most feared topic in DSA interviews — because students learn them abstractly. This guide teaches every essential graph algorithm with concrete implementations and the exact problems they unlock.
Python Interview Tricks: 25 Built-ins and Patterns That Make Your Code 3x Faster to Write
Python's standard library is a secret weapon in interviews. While others write 10-line implementations, you can solve the same problem in 2 lines — and spend the remaining time thinking about edge cases. Here are the 25 tricks that matter most.
Heaps and Priority Queues: The Underestimated Pattern That Solves 20+ Interview Problems
Most students treat heaps as an afterthought. This guide shows you why they're one of the most powerful tools in your DSA arsenal — with every pattern from top-K to sliding window maximum, fully implemented.
The 6-Month Campus Placement Roadmap for CS Students in India
A week-by-week plan to go from beginner to placement-ready — covering DSA, aptitude, core CS subjects, HR rounds, and company-specific strategy. No fluff, no paid courses.
Dynamic Programming Demystified: A Step-by-Step Framework for Any DP Problem
Dynamic programming confuses most students because they try to memorise solutions. This guide teaches you a repeatable 4-step framework to solve DP problems from scratch — even in interviews.
Space Complexity and In-Place Algorithms: When Memory Matters and How to Optimise It
Time complexity gets all the attention. But space complexity decides whether your code runs in a memory-constrained environment — and interviewers test it more than most students expect. This guide covers every space optimisation technique with real examples.
The DSA Habit System: How to Make Daily Practice Automatic and Actually Stick
Most students start strong and quit within 3 weeks. The problem isn't willpower — it's system design. This guide builds a practice system that runs on autopilot, tracks your real progress, and recovers from missed days without spiral.
String Manipulation Mastery: Every Pattern From Palindromes to Anagram Matching
Strings are in 40% of coding interview problems. They look simple but hide deep patterns — rolling hash, Z-algorithm, Rabin-Karp, and more. This guide goes from fundamentals to advanced string techniques with full implementations.
Competitive Programming vs DSA Interviews: What's Different and How to Transition
CP and interview DSA look similar but reward completely different skills. Understanding the gap — and how to bridge it — saves months of misdirected preparation. This guide is for students coming from either direction.
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