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bfs

AI, ML & GenAI interview questions tagged bfs, across every topic.

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Concepts behind "bfs"

The curriculum that explains the ideas these questions test.

Foundational
💻 Coding & Engineering Craft
Stacks and QueuesA stack is last-in-first-out and a queue is first-in-first-out, and most interview value comes from spotting which problems conceal one. The high-leverage patterns are the monotonic stack for next-greater-element and stock-span problems, queues for breadth-first traversal, and constructing one structure from the other (two stacks for a queue, a deque for both). Applied-AI interviews test this because the recognition skill (bracket matching, span, BFS frontier) is the real exam, not the data structure itself.
Core
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Trees, BSTs, and TraversalA binary tree connects each node to at most two children, and a binary search tree adds the invariant that everything left is smaller and everything right is larger, which yields O(log n) search on a balanced tree. The traversal skills interviews check are the three depth-first orders (pre, in, post), breadth-first level order, and moving between recursion and an explicit stack. Applied-AI interviews test this because in-order traversal of a BST produces sorted output, and the recursion-to-stack conversion is the same skill behind iterative DFS everywhere.
Core
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Graphs: BFS, DFS, and Shortest PathsA graph is nodes and edges, and most of the work is realizing a problem is a graph to begin with. BFS finds shortest paths in unweighted graphs and explores level by level, DFS goes depth-first and reveals connectivity and cycles, and Dijkstra handles non-negative weighted shortest paths with a priority queue. Applied-AI interviews test it because dependency graphs, retrieval graphs, and reachability questions are everywhere once you learn to spot them.