Master fundamental and advanced algorithms essential for technical interviews at top companies. This category covers sorting algorithms, search algorithms, graph algorithms, and optimization techniques that form the foundation of computer science problem-solving.
What You’ll Learn:
Sorting algorithms: Quick sort, merge sort, heap sort
Search techniques: Binary search and variations
Graph algorithms: DFS, BFS, Dijkstra’s, topological sort
Optimization: Dynamic programming, greedy algorithms
Time and space complexity analysis
Difficulty Progression: Start with basic sorting and searching, then progress to graph algorithms and dynamic programming.
Interview Frequency: Extremely high – algorithms appear in 80%+ of technical interviews at Google, Amazon, Facebook, Microsoft, and Apple.
10 min read Range query problems appear frequently in competitive programming and technical interviews. Knowing which data structure to reach for – and […] Read article
8 min read Monotonic Deque Pattern – Sliding Window Maximum LeetCode 239. Given an array and window size k, return the maximum in Read article
7 min read Core Probability Concepts Probability questions test your ability to reason about uncertainty and expected behavior. Three concepts appear repeatedly in Read article
4 min read Advanced Array Interview Patterns Mastering a handful of array techniques unlocks dozens of LeetCode problems. This guide covers the six Read article
4 min read Monotonic Stack Review A monotonic stack maintains elements in strictly increasing or decreasing order. Increasing monotonic stack: pop when the Read article
5 min read Thread Safety Fundamentals A race condition occurs when two threads read and write shared state concurrently without synchronization, producing non-deterministic Read article
6 min read Reverse Linked List: Iterative, Recursive, and K-Groups Reversing a linked list (LC 206) is the foundational operation. Iterative: maintain prev=None, Read article
5 min read Sliding Window Maximum – Monotonic Deque (LC 239) O(n) solution using a monotonic decreasing deque storing indices. Each element is Read article
6 min read Chinese Remainder Theorem (CRT) CRT solves systems of congruences: given x ≡ ai (mod mi) where mi are pairwise coprime, Read article
6 min read Backtracking Template Backtracking = DFS + undo. The universal template: choose (add to path), recurse (explore), unchoose (remove from path). Read article
8 min read Why Sorting Algorithms Still Matter in Interviews Interviewers at top tech companies still ask about sorting not to test memorization, Read article
6 min read Cycle Detection in Undirected Graphs from collections import deque # DFS approach: track parent to distinguish back edge from tree Read article
5 min read 2D Grid BFS and DFS Fundamentals from collections import deque DIRS = [(0,1),(0,-1),(1,0),(-1,0)] # right, left, down, up def bfs_grid(grid, Read article
6 min read Core Bit Operations Reference # Fundamental bit tricks n & (n-1) # clear lowest set bit (check power of 2: Read article
6 min read Naive String Search and Why to Avoid It Naive string search: for each position i in text (0..n-m), compare pattern[0..m-1] Read article
