Red-Black Trees Explained: Rules, Rotations & Real-World Usage
Understand Red-Black trees — the 5 rules, insertion cases, color flips, rotations, comparison with AVL, and why Java TreeMap and Linux use them.
·11 min read · #dsa#trees#advanced
#dsa
277 posts · page 4 of 6
Shortest Path Algorithms: BFS, Dijkstra, Bellman-Ford, Floyd-Warshall
Compare all four shortest path algorithms with Python code, complexity analysis, and a decision flowchart for choosing the right one.
·12 min read · #dsa#graphs#intermediate
Sliding Window: Advanced Patterns and Templates
Master fixed-size and variable-size sliding window techniques. Covers minimum window substring, longest substring with K distinct chars, and string permutation problems.
·11 min read · #dsa#sliding-window#intermediate
Stack-Based Parsing: Parentheses, Decode String & Calculator
Master stack-based parsing patterns — balanced parentheses, minimum removals, longest valid parentheses, decode string, and basic calculator with Python solutions.
·9 min read · #dsa#stacks#intermediate
Sqrt Decomposition and Mo's Algorithm
Learn sqrt decomposition for O(sqrt(n)) range queries and updates, plus Mo's algorithm for answering offline queries efficiently. Full Python implementations included.
·11 min read · #dsa#range-queries#advanced
Sparse Table for Range Queries in O(1)
Master sparse tables for O(1) range minimum/maximum queries with O(n log n) preprocessing. Learn construction, idempotent functions, and when to use sparse tables over segment trees.
·13 min read · #dsa#range-queries#advanced
Stack Expression Evaluation: Infix, Postfix & Calculator
Build a calculator from scratch — learn infix, prefix, and postfix notation, the Shunting Yard algorithm, postfix evaluation, and Python implementation.
·8 min read · #dsa#stacks#intermediate
Stack Next Greater Element & Monotonic Stacks
Master the monotonic stack pattern — solve Next Greater Element, Next Smaller, stock span, and circular array variants with Python templates and visual walkthroughs.
·9 min read · #dsa#stacks#intermediate
Strongly Connected Components: Kosaraju and Tarjan
Master SCCs with Kosaraju's two-pass DFS and Tarjan's low-link algorithm, including condensation graphs and real applications in Python.
·11 min read · #dsa#graphs#advanced
Subarray Sum Patterns: Prefix Sum, Kadane, and Sliding Window
Master subarray sum techniques — prefix sum for range queries, Kadane's algorithm for maximum subarray, hash map for subarray sum equals K, sliding window, and maximum product subarray.
·12 min read · #dsa#arrays#intermediate
Suffix Arrays: Construction, LCP, and Applications
Learn suffix arrays from scratch -- naive and O(n log^2 n) construction, LCP arrays, pattern searching with binary search, and applications like longest repeated substring.
·12 min read · #dsa#strings#advanced
Topological Sort: Algorithms and Applications
Master topological sorting with Kahn's BFS and DFS approaches. Solve course scheduling, build dependencies, alien dictionary, and longest path in DAG problems.
·12 min read · #dsa#graphs#intermediate
Constructing Binary Trees from Traversal Sequences
Build binary trees from inorder + preorder, inorder + postorder, and preorder + postorder. Hashmap optimization, edge cases, and Python recursive solutions.
·10 min read · #dsa#trees#intermediate
Tree Diameter and Path Problems
Find the diameter of a binary tree using DFS, solve maximum path sum, and understand the two-BFS approach for general trees. Full Python implementations.
·9 min read · #dsa#trees#intermediate
Tree Serialization and Deserialization
Serialize binary trees to strings and deserialize them back. BFS and DFS approaches with null handling, Python implementations, and real-world uses.
·9 min read · #dsa#trees#intermediate
Two Pointer: Advanced Patterns and Templates
Master opposite-direction, same-direction, and fast-slow two pointer patterns. Includes templates, container with most water, cycle detection, and sort colors.
·12 min read · #dsa#two-pointer#intermediate
Z-Algorithm for Linear-Time String Matching
Master the Z-algorithm for pattern matching in O(n) time. Learn Z-array construction, the Z-box optimization, and applications like finding string periods and distinct substrings.
·10 min read · #dsa#strings#intermediate
Advanced DP Patterns: Bitmask, Digit, Trees & Intervals
Master advanced dynamic programming patterns — interval DP, tree DP with rerooting, bitmask DP, digit DP, and optimization techniques like Knuth's and divide-and-conquer optimization.
·12 min read · #dsa#dynamic-programming#advanced
Data Structures Comparison Guide: When to Use What
A comprehensive comparison of data structures — arrays vs linked lists, hash maps vs trees vs tries, heaps vs BSTs, stacks vs queues, sets vs Bloom filters, with decision flowcharts and complexity tables.
·12 min read · #dsa#data-structures#comparison
Competitive Programming Patterns: 15 Essential Techniques
The 15 most common competitive programming patterns — prefix sums, difference arrays, coordinate compression, meet in the middle, sqrt decomposition, sparse tables, binary lifting, and Mo's algorithm.
·12 min read · #dsa#competitive-programming#patterns
DSA in Real Systems: From B-Trees to Bloom Filters
How real-world systems use data structures and algorithms — B-trees in databases, skip lists in Redis, inverted indexes in search, Dijkstra in routing, DAGs in Git, consistent hashing, and Bloom filters.
·11 min read · #dsa#system-design#databases
Advanced Graph Algorithms: SCCs, Flows & Bridges
Deep dive into advanced graph algorithms — Tarjan's and Kosaraju's for SCCs, bridges and articulation points, Euler paths, network flow, and 2-SAT with real-world applications.
·11 min read · #dsa#graphs#advanced
Interview Problem Solving: The 5-Step Framework
A complete framework for solving coding interview problems — the 5-step method, pattern recognition, handling stuck moments, communication strategies, common mistakes, and a 100-problem practice roadmap.
·12 min read · #dsa#interviews#problem-solving
Advanced String Algorithms: Z, Rabin-Karp & Suffix Arrays
Master advanced string algorithms — Z-algorithm, Rabin-Karp rolling hash, suffix arrays, Aho-Corasick multi-pattern matching, Manacher's palindrome algorithm, and string hashing techniques.
·11 min read · #dsa#strings#advanced
Advanced Tree Algorithms: HLD, Centroid & Euler Tour
Deep dive into advanced tree algorithms — heavy-light decomposition, Euler tour technique, centroid decomposition, LCA with binary lifting, tree DP with rerooting, and virtual trees.
·11 min read · #dsa#trees#advanced
Binary Search on Answer Technique
Learn to binary search on the answer space — the powerful technique behind problems like splitting arrays, Koko eating bananas, and capacity to ship packages.
·5 min read · #dsa#binary-search#intermediate
Floyd-Warshall Algorithm for All-Pairs Shortest Paths
Master the Floyd-Warshall algorithm — understand the DP recurrence, implement it in Python, detect negative cycles, and know when to pick it over Dijkstra.
·4 min read · #dsa#graphs#intermediate
Graph Coloring and Bipartite Check
Learn graph coloring fundamentals — check if a graph is bipartite using BFS/DFS, solve m-coloring with backtracking, and tackle classic interview problems.
·5 min read · #dsa#graphs#intermediate
KMP String Matching Algorithm Explained
Master the Knuth-Morris-Pratt algorithm — build the failure function, avoid redundant comparisons, and solve pattern matching problems in O(n + m) time.
·5 min read · #dsa#strings#intermediate
Monotonic Stack Patterns for Coding Interviews
Learn the monotonic stack technique — next greater element, stock span, largest rectangle, and trapping rain water solved with clean Python templates.
·5 min read · #dsa#stack#intermediate
Segment Trees Explained
Master segment trees for range queries and updates. Covers build, query, update, lazy propagation, and applications for range sum, min, and max problems.
·10 min read · #dsa#segment-trees#advanced
Trie Data Structure: Implementation and Applications
Complete guide to the Trie data structure. Covers insertion, search, prefix matching, deletion, and real-world applications like autocomplete and word puzzles.
·7 min read · #dsa#trie#intermediate
DSA Time Complexity Cheatsheet for Interviews
A printable cheatsheet of time and space complexities for arrays, hashmaps, trees, heaps, graphs, sorts, and common algorithms. Includes worst-case notes and quick rules of thumb.
·6 min read · #dsa#complexity#interviews
Find Minimum in Rotated Sorted Array — Binary Search
Solve Find Minimum in Rotated Sorted Array in logarithmic time with a modified binary search. Learn the pivot-finding invariant, edge cases, and how to extend the pattern to related problems.
·5 min read · #dsa#leetcode#binary-search
Fizz Buzz — A Clean, Extensible Solution
Solve Fizz Buzz with clean code and explore the string-concatenation pattern that avoids nested if-else. Python, Java, C++, and complexity analysis included.
·5 min read · #dsa#leetcode#beginners
Find Median from Data Stream — Two-Heaps Pattern
Solve Find Median from Data Stream with two heaps. Learn the balance invariant, why it gives O(log n) inserts and O(1) median, and the common pitfalls.
·5 min read · #dsa#leetcode#heap
Jump Game — Greedy Max-Reach Beats DP
Solve Jump Game with a single-pass greedy max-reach approach. Compare it against the dynamic programming solution and learn when greedy is provably optimal.
·4 min read · #dsa#leetcode#greedy
Maximum Product Subarray — Tracking Min and Max
Solve Maximum Product Subarray in linear time by tracking running min and max. Learn why negative numbers flip the role of min and max and see clean code.
·5 min read · #dsa#leetcode#dynamic-programming
Meeting Rooms II — Heap and Sweep Line
Solve Meeting Rooms II two ways: a min-heap of end times and a sweep-line over start and end events. Learn when each shines and how to pick in interviews.
·4 min read · #dsa#leetcode#heap
Merge Intervals — Sort and Sweep
Walk through Merge Intervals step by step. Brute force vs the optimal sort-and-sweep approach, edge cases, and clean code you can ship in an interview.
·5 min read · #dsa#leetcode#intervals
Palindrome Number — Without Converting to a String
Detect integer palindromes by reversing half the digits with integer math. Learn why string conversion is discouraged and how to handle negatives and trailing zeros.
·6 min read · #dsa#leetcode#math
Reverse String — Two-Pointer In-Place Solution
Solve the Reverse String problem in place using the two-pointer technique. Walkthrough, complexity analysis, edge cases, and clean Java, Python, and C++ implementations.
·4 min read · #dsa#leetcode#two-pointers
Rotate Array — The Triple-Reverse Trick
Rotate an array by k steps in O(1) extra space using the triple-reverse trick. Compare it with the extra-array approach and learn why this pattern keeps showing up.
·5 min read · #dsa#leetcode#arrays
Backtracking Patterns: Subsets, Permutations, N-Queens
A practical guide to backtracking: the recursion template, pruning, classic problems with code, and complexity analysis for subsets and permutations.
·6 min read · #dsa#backtracking#intermediate
Bellman-Ford and Negative-Weight Edges
Understand Bellman-Ford's relaxation loop, how it handles negative edges, detects negative cycles, and why it costs more than Dijkstra.
·5 min read · #graphs#shortest-path#intermediate
Dijkstra's Algorithm: Shortest Paths Explained
Learn Dijkstra's shortest path algorithm with a clean Python implementation, complexity analysis, and the priority queue intuition behind it.
·5 min read · #graphs#shortest-path#intermediate
Divide and Conquer: Mental Model with Merge Sort and Quick Sort
Learn the divide-and-conquer pattern through merge sort and quick sort, recurrence relations, the Master theorem, and how to recognize the pattern.
·7 min read · #dsa#divide-and-conquer#intermediate
Fenwick Tree (BIT): Prefix Sums on the Cheap
Implement and understand the Fenwick tree, also called the binary indexed tree, for O(log n) prefix sums and point updates in just a few lines.
·6 min read · #data-structures#fenwick-tree#intermediate