#bfs
7 articles
Graphs: Everything Is Connected
The graph data structure models the real world — maps, social networks, dependencies — better than any other. Learn how nodes and edges work, how to represent them, and how BFS and DFS let you actually do something useful with them.
Queues and Deques
The queue data structure enforces one rule — first in, first out — and that rule shows up everywhere from BFS to task schedulers. Learn how to get O(1) on both ends without the hidden tax of a naive array.
Graphs
The data structure that models everything connected — social networks, road maps, dependency chains, and more. Master representations, traversals, and the "model it as a graph" reframe that unlocks whole categories of problems.
Binary Trees and Traversals
Master binary tree traversal — inorder, preorder, postorder, and level-order — and the recursive mindset that makes dozens of tree problems click instantly.
Topological Sort
Order the nodes of a DAG so every edge points forward — the algorithm that drives build systems, package managers, course schedulers, and anything else that lives and dies by dependency ordering.
Shortest Paths (Dijkstra, Bellman-Ford, BFS)
Pick the right shortest-path algorithm the first time: BFS for unweighted graphs, Dijkstra with a heap for non-negative weights, Bellman-Ford when negative edges appear. Concrete worked examples, a decision table, and every gotcha that costs people the interview.
BFS Patterns
Queue-driven level-by-level traversal and why breadth-first search is the only guaranteed way to find shortest paths in unweighted graphs. Templates, traps, and four worked problems.