Advanced Data Structures and Algorithms Applications - HoseaCodes/OnePercent GitHub Wiki

Graph Algorithms

  1. Pathfinding Visualizer

    • Implement and visualize BFS, DFS, Dijkstra, and A* algorithms.
    • Add options to create weighted graphs and obstacles dynamically.
    • Deploy the project for users to interact with the visualizer.

  2. Social Network Analyzer

    • Build a tool to analyze a graph-based social network (e.g., find influencers, shortest paths, clusters).
    • Use algorithms like PageRank, Connected Components, and Minimum Spanning Tree.

  3. Real-Time Route Optimizer

    • Create a system for finding the shortest path or optimal routes for delivery systems.
    • Use Dijkstra or A* for pathfinding in real-time with live updates.

Dynamic Programming

  1. Dynamic Programming Visualizer

    • Develop a tool that explains DP problems step-by-step with interactive visuals.
    • Include problems like Knapsack, Longest Common Subsequence, and Matrix Chain Multiplication.

  2. Personalized Recommendation System

    • Use dynamic programming to implement a recommendation engine based on user preferences and constraints (e.g., maximum satisfaction under a budget).

Tree and Graph-Based Projects

  1. Autocompletion System

    • Build a text autocompletion feature using Trie and suggest results based on prefix queries.
    • Add a frequency-based ranking for suggested words.

  2. AI-Based Game Solver

    • Develop a Tic-Tac-Toe or Chess AI using Minimax with Alpha-Beta pruning.
    • Visualize the tree of game states.

  3. Dependency Resolver

    • Create a system to resolve package dependencies using Directed Acyclic Graphs (DAG).
    • Implement topological sorting to detect and resolve conflicts.

Search and Sorting Algorithms

  1. Search Engine with Ranking

    • Implement a search engine that ranks results using Inverted Index and PageRank algorithms.
    • Add features for caching and ranking optimizations.

  2. Sorting Algorithm Comparison Tool

    • Build a visual comparison of sorting algorithms (e.g., Merge Sort, Quick Sort, Heap Sort).
    • Allow users to input arrays and observe performance differences.

Greedy Algorithms

  1. Huffman Coding Compressor

    • Implement a file compression tool using Huffman Coding.
    • Add features to compress and decompress text files and analyze space savings.

  2. Event Scheduler

    • Create a scheduling app that uses greedy algorithms to optimize event overlap.
    • Allow users to add constraints like time slots and priorities.

Graph Theory and AI

  1. AI-Powered Navigation App

    • Develop a navigation tool using A* algorithm for real-time traffic data.
    • Include features like rerouting and estimated time of arrival.

  2. Smart City Traffic Management

    • Use graphs to simulate and optimize traffic flow in a smart city.
    • Apply algorithms like Max Flow and Minimum Cut.

Real-World Applications

  1. Distributed Load Balancer

    • Implement a system that distributes workloads across multiple servers using a HashMap and Priority Queue.
    • Optimize for even distribution and minimal latency.

  2. Blockchain Simulation

    • Build a simplified blockchain using HashMaps and linked structures.
    • Include features like transaction validation and proof of work.

  3. Online Coding Platform

    • Create a platform for solving coding challenges with live evaluation.
    • Use a trie for problem tags and dynamic programming to match solutions against constraints.

Advanced Applications

  1. Recommendation Engine for E-Commerce

    • Implement a recommendation engine using collaborative filtering (Matrix Factorization) and graph traversal techniques.

  2. Version Control System

    • Build a simplified version control system with branching and merging using trees and hash functions.

  3. Geo-Spatial Query System

    • Create a system for querying geo-spatial data using Quad Trees or R-Trees.
    • Use it for finding nearest points, regions, or mapping data.

Bonus Project

  1. Custom Algorithm Library
    • Build and document a library of advanced algorithms (e.g., Fenwick Tree, Segment Tree, KMP String Matching).
    • Publish the library on GitHub with test cases and examples.

Tips for Execution

  • Use frameworks like React or D3.js for visualization.
  • Document the projects thoroughly, explaining the problem, approach, and complexity analysis.
  • Deploy the projects online (e.g., GitHub Pages, Heroku, or Vercel) to showcase your work.
  • Write blog posts or create videos explaining the solutions to build a personal brand.