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Algorithms & Data Structures - CSES Problem Set

This repository contains my solutions to the CSES Problem Set, with a focus on building strong fundamentals in algorithms, data structures, and problem-solving for large-scale software engineering roles.

The emphasis is on correctness, optimal time–space complexity, and clean, readable implementations rather than competitive-programming shortcuts.


Focus Areas

Most of the solutions fall into the following core categories:

  • Trees

    • Tree traversals
    • Binary lifting (LCA)
    • Subtree DP
    • Rerooting techniques
  • Graphs

    • BFS / DFS
    • Shortest paths (Dijkstra, Bellman–Ford)
    • Topological sorting
    • Connected components
    • Strongly connected components
  • Dynamic Programming

    • Classic 1D / 2D DP
    • DP on trees
    • State optimization
    • Time and space tradeoff analysis

These topics closely mirror real-world problem-solving patterns used in backend and distributed systems interviews.


Languages Used

  • C++

All solutions are written with attention to:

  • Documenting the approach and thought process behind the solution to the problem
  • Clear naming
  • Modular logic
  • Avoiding unnecessary macros or tricks

Why CSES?

The CSES Problem Set provides a structured way to practice:

  • Algorithmic thinking
  • Edge-case handling
  • Writing efficient code under constraints

It is particularly useful for interview preparation at companies that emphasize fundamentals, such as Google.


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Algorithms and data structures solutions (trees, graphs, DP) from the CSES Problem Set.

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