How trinadhgorrela/java-dsa-solutions works
This repository is a pattern-organized Java DSA study guide, not an application with a shared runtime pipeline. The principal learner workflow is to recognize an algorithmic pattern, study its self-contained problem solutions, and practice applying that pattern. The README documents 26 patterns and 491 Java solutions; the supplied tree contains the Java pattern directories but no Database directory. Individual solutions do not import one another, so the graph shows the documented study workflow rather than invented calls between examples. Several pattern contents were not sampled.
Main entry points: Array Array · Math Math · Bit Manipulation Bit Manipulation · String String
Components 28
Core Techniques
- Array
Array - Math
Math - Bit Manipulation
Bit Manipulation - String
String - Prefix Sum
Prefix Sum
Search And Optimization
- Binary Search
Binary Search - Dynamic Programming
Dynamic Programming - Greedy
Greedy - Divide And Conquer
Divide and Conquer - Sliding Window
Sliding Window - Two Pointers
Two Pointers - Game Theory
Game Theory
Data Structures
- Structures
- Hash Table
Hash Table - Heap
Heap - Linked List
Linked List - Stack
Stack - Monotonic Stack
Monotonic Stack - Intervals
Intervals - Segment Tree
Segment Tree - Binary Indexed Tree
Binary Indexed Tree - Union Find
Union Find
Traversal And Modeling
- Backtracking
Backtracking - Graph
Graph - Tree
Tree - Topological Sort
Topological Sort - Matrix
Matrix
Other components
- Learner
Connections 26
- Learner → Array: studies patterns
README.md - Learner → Math: studies patterns
README.md - Learner → Bit Manipulation: studies patterns
README.md - Learner → String: studies patterns
README.md - Learner → Prefix Sum: studies patterns
README.md - Learner → Binary Search: studies patterns
README.md - Learner → Dynamic Programming: studies patterns
README.md - Learner → Greedy: studies patterns
README.md - Learner → Divide And Conquer: studies patterns
README.md - Learner → Sliding Window: studies patterns
README.md - Learner → Two Pointers: studies patterns
README.md - Learner → Backtracking: studies patterns
README.md - Learner → Graph: studies patterns
README.md - Learner → Tree: studies patterns
README.md - Learner → Topological Sort: studies patterns
README.md - Learner → Hash Table: studies patterns
README.md - Learner → Heap: studies patterns
README.md - Learner → Linked List: studies patterns
README.md - Learner → Stack: studies patterns
README.md - Learner → Monotonic Stack: studies patterns
README.md - Learner → Intervals: studies patterns
README.md - Learner → Segment Tree: studies patterns
README.md - Learner → Binary Indexed Tree: studies patterns
README.md - Learner → Union Find: studies patterns
README.md - Learner → Matrix: studies patterns
README.md - Learner → Game Theory: studies patterns
README.md