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What Is Graph Algorithm?
Graph Algorithms
Graph algorithms solve problems on data modeled as nodes (vertices) connected by edges. Social networks, maps, dependency systems, and the internet are all graphs. Key algorithms: BFS and DFS for traversal, Dijkstra for shortest paths, topological sort for dependency ordering.
How Graph Algorithm Works
BFS (Breadth-First Search): explore level by level — finds shortest path in unweighted graphs. Used for social network 'degrees of separation.' DFS (Depth-First Search): explore as deep as possible before backtracking — used for cycle detection, topological sorting, and maze solving.
Key Concepts
- BFS — Breadth-First Search — visit all neighbors before going deeper. Uses a queue. Finds shortest path in unweighted graphs.
- DFS — Depth-First Search — go deep before backtracking. Uses a stack (or recursion). Detects cycles, finds connected components.
- Dijkstra's Algorithm — Finds shortest path in weighted graphs — used in GPS navigation and network routing
- Topological Sort — Orders nodes so dependencies come first — used in build systems, task scheduling, npm install
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Frequently Asked Questions
Where are graph algorithms used in real life?
GPS navigation (shortest path), social networks (friend suggestions), package managers (dependency resolution), web crawlers (page discovery), recommendation systems (collaborative filtering).
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