DSA for Interviews and Competitive Programming

A Zig based coding practice repository

This repository contains clean, well-structured solutions to common Data Structures and Algorithms (DSA) problems frequently asked in coding interviews and competitive programming.

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Project Goals

• Build a high-quality, easy-to-reference collection of DSA problem solutions.
• Practice writing efficient algorithms in Zig.
• Maintain clean, readable explanations for future revision.
• Provide both pseudocode and Zig implementations.
• Use a standardized file structure for easy navigation.

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Solution Format

Every problem is documented using the following format:

# Problem Title (e.g., LeetCode 11 — Container With Most Water)

## Problem Statement
<Full description copied or rewritten in your own words>

## Explanation
<Clear reasoning, diagrams if needed, complexity analysis>

## Example Input
<Code block containing raw sample input>

## Example Output
<Code block containing raw sample output>

## Pseudocode
<Language-agnostic pseudocode>

## Zig Solution (Zig 0.15.2)
<Full Zig implementation using the correct modern APIs>

This ensures each .md file is clean, uniform, and easy to read.

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Language & Tools

• Zig version: 0.15.2 (installed via ZVM)
• Editor: VS Code
• Language Server: ZLS (configured to use Zig via ZVM)

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Folder Structure

.
├── README.md
├── 01-container-with-most-water-lc11/
│   ├── lc11.md
│   ├── lc11.zig
│   ├── pseudocode.md
├── 02-<next-problem>/
│   └── ...
└── ...

You may name folders using numeric prefixes to preserve order.

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Running a Zig Solution

Use the Zig CLI:

zig run path/to/file.zig

or build/run:

zig build run

To run any specific code from any versin branch against zig master

 zvm run master run .\01-container-with-most-water-lc11\lc11.zig

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Contribution Style (Personal Use)

To keep your notes consistent:

1. Always write the full problem explanation in Markdown.
2. Keep Zig code self-contained — no external dependencies.
3. Ensure the solution compiles on Zig 0.15.2 with the modern I/O and build APIs.
4. Keep explanations concise but informative for revision.

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Why Zig for DSA?

• Low-level control with high-level ergonomics.
• Fast compile times.
• Explicit memory management helps deepen understanding of algorithmic complexity.
• No hidden allocations or runtime surprises.
• Clean syntax ideal for interview preparation.

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Future Plans

• Add solutions for:
  • Two Pointers
  • Binary Search
  • Sliding Window
  • Recursion & Backtracking
  • Dynamic Programming
  • Trees & Graphs
  • Greedy Algorithms
  • Bit Manipulation
• Add benchmark comparisons for certain problems.
• Add a build system for running problem sets.

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License

For personal learning and interview preparation.
Feel free to modify the structure as needed.