Breadth-First Search

Breadth-First Search (BFS) is an algorithm that systematically explores a graph or tree structure by visiting all nodes at the current depth level before moving to the next. It is commonly used in web crawlers to explore all links on a website from a starting page, ensuring that each level of links is fully traversed before moving deeper into the link hierarchy.

Also known as: Level-order search.

Comparisons

• BFS vs. DFS: BFS explores all nodes level by level, while Depth-First Search (DFS) explores as far down a branch as possible before backtracking.

• BFS vs. Greedy Search: BFS ensures all paths are explored systematically, while greedy algorithms may prioritize paths based on a heuristic without full exploration.

Pros

• Comprehensive coverage: Ensures all nodes at each depth level are visited, making it useful for wide web exploration.

• Short-path detection: Finds the shortest path to a target node in unweighted graphs.

• Predictable resource usage: Limited to exploring one level at a time, making memory usage more predictable.

Cons

• High memory usage: BFS can consume a lot of memory, especially when applied to deep or large graphs.

• Inefficient for deep exploration: Takes longer to explore deep link hierarchies compared to DFS, as it prioritizes breadth over depth.

• Slow on highly interconnected graphs: On graphs with many connections, BFS may take a long time to process all nodes.

Example

A web crawler using BFS starts at a homepage and systematically explores all links on that page before moving to the next level of links, making it ideal for exploring shallow but wide websites.