October 6, 2020Breadth-first search (BFS) is a fundamental graph and tree traversal algorithm that explores nodes level by level, systematically visiting all neighbors at the current depth before moving to nodes at the next depth level. Unlike depth-first search which plunges deeply into one path, BFS spreads outward like ripples on water, ensuring that nodes closer to the starting point are always explored before more distant ones.
October 6, 2020Depth-first search (DFS) is a fundamental algorithm for traversing or searching tree and graph data structures. The core principle of DFS is to explore as deeply as possible along each branch before backtracking to explore alternative paths. This “go deep first” strategy distinguishes it from breadth-first search, which explores nodes level by level.
The algorithm begins at a root node (or an arbitrary starting node in the case of a graph) and systematically explores each branch to its deepest point before moving to the next branch. This exhaustive exploration pattern makes DFS particularly useful for problems involving path finding, cycle detection, topological sorting, and solving maze-like puzzles.
June 20, 2020Tree data structures are one of the most fundamental concepts in computer science and software engineering. Unlike linear data structures such as arrays or linked lists, trees represent hierarchical relationships between elements. This hierarchical nature makes them incredibly powerful for organizing data in ways that mirror real-world relationships, from file systems on your computer to the DOM structure of web pages, from organizational charts to decision trees in artificial intelligence.