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DSAPath

Map the structures. Understand the tradeoffs. Choose the right algorithm.

A source-backed guide to data structures, algorithms, complexity, and the concept graph that connects them.

Start with the core path

Learn the cost model first, then move through the structures and algorithm families that most software systems reuse.

  1. 01Complexity Analysis
  2. 02Arrays
  3. 03Binary Search
  4. 04Hash Tables
  5. 05Heaps
  6. 06Graphs
  7. 07Dynamic Programming

Choose the right family

Most DSA decisions are not trivia. They are choices about representation, access pattern, and failure mode.

Represent data

Use structures when the question is where data lives and how quickly it can be found or updated.

Move through a problem

Use algorithm patterns when the question is how work should be ordered, pruned, or reused.

Build the concept graph

DSAPath is organized as a map: complexity explains cost, structures shape access, and algorithms move through state.

Make the algorithms executable

Use notebooks for exploration, Python for the first real implementation, C++ for performance-critical comparisons, and tests before claiming an algorithm works.

Read the atlas, then implement the idea.

Continue with code verification