Data Structures and Algorithms - The-Learners-Community/RoadMaps-and-Resources GitHub Wiki

ROADMAP

Welcome to the Data Structures and Algorithms Roadmap! This guide is designed to take you from a beginner to an expert in data structures and algorithms. Each section covers essential topics and skills you need to become proficient and dangerous.

Checkout roadmap.sh/datastructures-and-algorithms

PROJECTS - Beginner to Master

Beginner Level

1. Implement Basic Data Structures

Implement fundamental data structures like:

  • Stack
  • Queue
  • Singly Linked List
  • Doubly Linked List

Use them in simple programs to understand their operations.

2. Sorting Algorithm Visualizer

Create a visual tool that demonstrates how sorting algorithms work step by step:

  • Bubble Sort
  • Selection Sort
  • Insertion Sort

Visualize the comparisons and swaps between elements.

3. Simple Calculator Using Expression Trees

Build a calculator that:

  • Parses mathematical expressions into an Expression Tree
  • Supports operations like addition, subtraction, multiplication, and division
  • Evaluates the expression by traversing the tree

4. Word Frequency Counter

Write a program that:

  • Reads text from a file
  • Uses a Hash Map to count the frequency of each word
  • Displays the top N most frequent words

5. Maze Solver

Develop a maze-solving application using:

  • Depth-First Search (DFS)
  • Breadth-First Search (BFS)

Visualize the path from the start to the end point in a grid-based maze.

6. Implement Basic Search Algorithms

Implement linear search and binary search algorithms and compare their efficiencies.

7. Fibonacci Sequence Generator

Create a program that generates the Fibonacci sequence using:

  • Recursion
  • Iteration

Compare the performance and discuss the pros and cons.

8. Palindrome Checker

Develop a program that checks if a given string is a palindrome using stacks and queues.

9. Anagram Finder

Write a function to check if two strings are anagrams of each other using sorting or hash maps.

10. Parentheses Balancer

Create a program that uses a stack to check if a string of parentheses is balanced.

Intermediate Level

11. Binary Search Tree Implementation

Create a Binary Search Tree (BST) with the following features:

  • Insertion and deletion of nodes
  • Search functionality
  • Tree traversals:
    • In-order
    • Pre-order
    • Post-order

12. Graph Traversal Algorithms

Implement a graph data structure and perform:

  • Breadth-First Search (BFS)
  • Depth-First Search (DFS)

Visualize the order in which nodes are visited.

13. Heap Implementation and Heapsort

Build:

  • A Max Heap and a Min Heap
  • Implement Heapsort algorithm
  • Include heap operations like insert and extract

14. Pathfinding Algorithms

Implement algorithms to find the shortest path in a weighted graph:

  • Dijkstra's Algorithm
  • A* Search Algorithm

Apply them to real-world maps or grid-based games.

15. LRU Cache

Design an LRU (Least Recently Used) Cache with the following:

  • Fixed capacity
  • Operations: get(key) and put(key, value)
  • Utilize a Hash Map combined with a Doubly Linked List for efficiency

16. String Pattern Matching Algorithms

Implement advanced string search algorithms:

  • Knuth-Morris-Pratt (KMP) Algorithm
  • Rabin-Karp Algorithm

Use them to find pattern substrings within larger texts efficiently.

17. Implement a Trie (Prefix Tree)

Create a Trie data structure to:

  • Store a dictionary of words
  • Implement insertion and search operations
  • Provide auto-complete suggestions based on a given prefix

18. Balanced Binary Search Trees

Implement a self-balancing BST:

  • AVL Tree or Red-Black Tree
  • Include rotations during insertion and deletion to maintain balance
  • Provide all standard BST operations

19. Disjoint Set (Union-Find) Data Structure

Build a Disjoint Set data structure to:

  • Perform find and union operations
  • Implement Path Compression and Union by Rank
  • Use it to detect cycles in an undirected graph

20. Implement Huffman Coding

Create a program that:

  • Builds a Huffman Tree based on character frequencies
  • Generates Huffman codes for data compression
  • Encodes and decodes text files

Advanced Level

21. Build a Simple Compiler

Design a compiler for a simple programming language:

  • Lexical Analysis: Tokenize the input code
  • Syntax Analysis: Build an Abstract Syntax Tree (AST)
  • Semantic Analysis: Check for semantic errors
  • Code Generation: Generate intermediate or executable code

Focus on utilizing data structures like trees and graphs for parsing and representing code.

22. Implement Advanced Graph Algorithms

Implement complex graph algorithms such as:

  • Kruskal's Algorithm for Minimum Spanning Tree
  • Prim's Algorithm for Minimum Spanning Tree
  • Bellman-Ford Algorithm for shortest paths with negative weights
  • Floyd-Warshall Algorithm for all-pairs shortest paths

23. Build a Concurrent Data Structure

Implement thread-safe data structures like:

  • Concurrent Queue
  • Concurrent Hash Map

Learn about synchronization mechanisms like mutexes and semaphores.

24. Implement Neural Network from Scratch

Create a simple neural network using only basic data structures and algorithms:

  • Implement forward and backward propagation
  • Use matrices and vectors for computations
  • Train on simple datasets like the XOR problem

25. Create a Custom Memory Allocator

Design a memory management system:

  • Implement functions similar to malloc, free, calloc, and realloc
  • Manage memory allocation using data structures like linked lists and trees
  • Handle fragmentation and optimize for performance

Happy coding and deep diving into data structures and algorithms!