⚙️ Data structures v2

Personal project for in-depth learning and exploring the most important data structures in computer science. Why? Because practice makes perfect! Especially when practising the fundamentals 😉

Also it's a great way to find out how much I've improved in my coding skills over the years since the project's built upon my old university assignment from Wrocław University of Science and Technology where I implemented (in C++) and then measured time complexities of 3 basic data structures: dynamic array, linked list, heap and finally binary search tree.

• ⚙️ Data structures v2
  • 🎯 Goals
  • 🚀 Quickstart
  • 📇 Project structure
    • Data Structures Library
    • Benchmarks
    • Benchmark analyzer
    • Data Structures Analyzer

🎯 Goals

• 👨🏻‍💻 Implement various data structures in low-level language (C++).

• ⏱️ Measure time & memory complexities of the implemented data structures & compare them to their equivalents from STL and higher-level languages: Python, Java and TypeScript.

• 📚 Dive into source code of these data structures in higher level languages to gain more in-depth understanding of those languages.

• 🖼️ App with visualizations for implemented data structures that would allow users to follow how they work step by step.

You can check the current progress in the Versions document.

🚀 Quickstart

📇 Project structure

Data Structures Library

Library written in C++ that contains my implementations for various data structures (DS). It should allow to use those DS in 2 modes:

1. Release: Standard usage of the DSes for maximal performance.
2. Debug: Allows for step-by-step work of the DSes for easy visualization.

Benchmarks

Applications with CLI (or simple Web for TS) interfaces that would allow to measure time and memory complexities of data structures. Included types of benchmarks:

• Library benchmark: Benchmarking for my C++ implementations and Standard Template Library (STL). A C++ application with CLI interface.
• Python benchmark: Benchmarking for Python implementations of the data structures (both builtin & third-party libs). A Python application with CLI interface.
• Java benchmark: Benchmarking for Java implementations of the data structures (both builtin & third party lib). A Java application with CLI interface.
• TS benchmark: Benchmarking for TypeScript implementations of the data structures (both builtin & third party lib). Simple Web application.

All benchmarks generate output CSV files with results that follow the same schema.

Benchmark analyzer

Python CLI application that analyzes targeted benchmark CSV files. It allows to:

• Compare implementations of data structures both numerically & graphically.
• Present time & memory complexities of DS operations both numerically and graphically.

It generates PDF reports as an output as well as SVG files for as graphical analysis output.

Data Structures Analyzer

A Python desktop application with GUI that would allow to analyze inner-workings of the implemented data structures step-by-step. In other words this app runs implemented data structures in the debug mode.