Trie Data Structure Interview Patterns: Autocomplete, Word Search & XOR
5 min read Trie Data Structure Interview Patterns: Autocomplete, Word Search & Prefix Problems A Trie (prefix tree) is the go-to data structure […] Read article
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.
5 min read Trie Data Structure Interview Patterns: Autocomplete, Word Search & Prefix Problems A Trie (prefix tree) is the go-to data structure […] Read article
5 min read Graph Algorithms Interview Patterns: BFS, DFS, Dijkstra & More Graph problems appear in roughly 25% of FAANG algorithm interviews. Mastering Read article
4 min read Why Math in Coding Interviews? Math problems appear in interviews at all levels — they test logical reasoning and knowledge Read article
7 min read Why Concurrency in Interviews? Concurrency problems appear at senior-level interviews (SDE-2 and above) at companies like Apple, Google, and Databricks. Read article
7 min read Why Hash Maps Are Fundamental Hash maps (dictionaries in Python, HashMaps in Java) provide O(1) average-case lookup, insertion, and deletion. Read article
5 min read Why Sorting Algorithms Matter in Interviews Sorting knowledge signals deep CS understanding. Interviewers ask about sorting to evaluate: time/space complexity Read article
7 min read What Is Topological Sort? A topological sort of a directed acyclic graph (DAG) produces a linear ordering of vertices such Read article
7 min read Grid DP Overview Grid DP problems involve a 2D grid where you make decisions at each cell and need to Read article
7 min read When Do You Need These? Segment trees and Fenwick trees (Binary Indexed Trees / BIT) solve range query problems efficiently. Read article
6 min read The Recursion Mindset Recursion solves a problem by defining it in terms of a smaller version of the same problem. Read article
7 min read The Divide and Conquer Paradigm Divide and conquer solves problems by: (1) Divide — split the problem into smaller subproblems Read article
6 min read What Is Union-Find? Union-Find (also called Disjoint Set Union or DSU) is a data structure that efficiently tracks which elements Read article
7 min read What Is a Monotonic Stack? A monotonic stack is a stack that maintains its elements in either monotonically increasing or Read article
7 min read Tree Traversal Fundamentals Binary tree problems appear in nearly every technical interview. The foundation is traversal order, which determines which Read article
8 min read String dynamic programming problems — longest common subsequence, edit distance, palindromic subsequences — appear frequently in senior engineering interviews. These Read article