Articles
Interview prep guides, strategies, and deep dives.
Divide and Conquer Algorithm: How to Spot It
The divide and conquer algorithm framework, with working code, a complexity table, and when it loses to dynamic programming in an interview.
Low-Level Design Interview Questions: A Practical Framework
A practical framework for low-level design interviews, the problems that come up most, a worked parking lot example, and the mistakes that cost points.
Union-Find (Disjoint Set): How to Code It in an Interview
Union-Find tracks connectivity across a changing graph in almost constant time per operation, but only if you add path compression and union by rank, and know which real interview problems actually call for it.
Merge Intervals: The Sort-and-Sweep Pattern Explained
Merge intervals collapses overlapping ranges into the fewest ranges with one sort and one pass. The algorithm, working code, and the insert interval follow-up.
Topological Sort: Kahn's Algorithm and DFS
Topological sort orders a graph so dependencies come first. Here's Kahn's algorithm and the DFS approach, with working code and real cycle detection.
Kadane's Algorithm: Why It's DP, Not Greedy
Kadane's algorithm turns an O(n squared) scan into a single O(n) pass. It's dynamic programming, not greedy, even though the trick looks greedy.
Quickselect Algorithm: Find the Kth Largest Element
Quickselect finds the kth largest element in O(n) average time, no full sort needed. Here's the partition step and when a heap beats it instead.
Monotonic Stack: When to Reach for One in an Interview
A monotonic stack answers next-greater and next-smaller questions in one pass, but only if you know which direction to keep it sorted and what to store on it.
BFS vs DFS: The Decision Framework for Coding Interviews
BFS vs DFS in coding interviews: the cue words that reveal which one a problem wants, Python code, real complexity, and the mistakes that cost points.
Two Pointers Algorithm: When to Use Which Direction
Two pointers turns an O(n squared) scan into a single pass, but only if you pick the right setup: opposite ends, same direction, or fast and slow.
Heap Interview Questions: How to Recognize and Solve Them
A heap interview question tests whether you reach for a priority queue instead of sorting a list you only need part of. Here's how to spot one and solve it.
System Design Interview Questions: What Repeats
The system design interview questions that actually repeat across companies, grouped by what each one tests, with real walkthroughs linked in.
Bit Manipulation Interview Questions: When XOR Beats a Loop
Bit manipulation questions ask for O(1) space instead of a hash map. Here's how to spot the pattern and pick the right trick fast.
Backtracking Algorithm: One Template, Four Real Problems
Backtracking algorithm explained with one template, four worked interview problems, real time complexity, and the mistakes that cost candidates points.
Dynamic Programming Patterns: How to Recognize Them
Dynamic programming patterns explained: recognize a DP problem, pick the right pattern family, and go from brute force to a space-optimized solution.
Linked List Interview Questions: 3 Patterns to Know
Reverse, detect a cycle, or merge sorted lists: almost every linked list interview question comes down to three reusable pointer patterns.
What Is a Live Coding Interview? Format, Tools, and Tips
A live coding interview means writing code on a shared screen while someone watches every keystroke. Here's what it tests and how to prepare.
Sliding Window Algorithm: How to Spot It Before You Code
The sliding window algorithm turns a nested loop into one pass by tracking a moving range instead of restarting the count each time.
How to Implement Binary Search in C
Binary search in C with pointers, overflow-safe midpoint, and interview-ready code for sorted integer arrays.
How to Implement Binary Search in Python
Iterative and recursive binary search in Python, the bisect module, and interview-ready templates with O(log n) complexity.
How to Implement Binary Search in C++
C++ binary search with STL lower_bound, upper_bound, and hand-written templates for coding interviews.
Sorting Algorithms: Time Complexity Cheat Sheet for Interviews
Best, average, and worst-case time and space complexity for every sorting algorithm interviewers expect you to know, plus when to say which one and why.
Big O Cheat Sheet: How to Analyze Time Complexity in Coding Interviews
The Big O cheat sheet interviewers actually expect: every complexity class ranked from best to worst, plus how to reason about loops, recursion, and space before you write a line of code.
LeetCode Patterns: How to Spot Them Before You Code
LeetCode patterns matter less as a memorized list and more as signals in the problem statement you learn to catch before writing a line of code.
How to Implement Binary Search in Go
Binary search in Go with slices, sort.Search, and idiomatic interview templates for sorted integer arrays.
How to Implement Binary Search in Java
Java binary search with iterative and recursive implementations, Arrays.binarySearch, and overflow-safe midpoint for coding interviews.
Binary Search Algorithm: A Coding Interview Guide
How binary search works on sorted arrays, two implementation patterns interviewers expect, and when O(log n) beats a linear scan.
How to Approach OOD Interviews
A practical framework for object-oriented design interviews — from requirements to class diagrams and follow-ups.
SQL Patterns Every SDE Should Know
Window functions, aggregations, and joins that appear repeatedly in data-heavy SDE interview loops.
A 45-Minute System Design Framework
Structure any system design interview with requirements, estimation, API design, data model, and scaling.