cycle detection
Applied AI interview questions tagged cycle detection, across every topic.
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Concepts behind "cycle detection"
The curriculum that explains the ideas these questions test.
Foundational
Linked ListsA linked list stores elements in nodes that point to the next node, trading away O(1) random access for O(1) insertion and deletion once you hold a pointer. Interviews use them to test pointer discipline: the dummy-head trick, fast/slow pointers for cycle detection and finding the midpoint, and in-place reversal. Applied-AI interviews probe them because the patterns transfer to streaming buffers, LRU caches, and any structure where you splice without shifting.💻 Coding & Engineering Craft
Foundational
Fast and Slow Pointers (Floyd's Cycle Detection)Fast and slow pointers run two cursors through a sequence at different speeds so geometry, not extra memory, reveals structure. The tortoise and hare detect a cycle, locate where it begins, and find the middle of a list in a single pass with O(1) extra space. Interviews probe this because it tests whether a candidate can trade a hash set for a pointer trick and prove the meeting actually happens.💻 Coding & Engineering Craft
Core
Topological Sort and DAGsA topological sort orders the nodes of a directed acyclic graph so that every edge points forward, which is exactly what dependency resolution needs. Kahn's algorithm peels off zero-indegree nodes while DFS post-order reverses the finish times, and both detect cycles for free when no valid order exists. Applied-AI interviews probe it because build systems, data pipelines, and task schedulers are dependency graphs, and the course-schedule question is its canonical disguise.💻 Coding & Engineering CraftSign in