DSA Cheatsheets

Small datasets or nearly sorted data; educational purposes

Small datasets; minimal memory writes are important

Small or nearly sorted datasets; online sorting (streaming data)

Large datasets; stable sort required; linked list sorting

Large datasets; average-case performance is excellent

Large datasets with guaranteed O(n log n); limited memory available

Small or unsorted datasets; single search operation

Sorted arrays; frequent search operations; large datasets

Sorted arrays; better than linear search but simpler than binary search

Dynamic sorted data; fast search, insert, and delete operations

When guaranteed O(log n) operations are critical; lookup-heavy workloads

Priority queues; Dijkstra's algorithm; scheduling; K smallest/largest elements

Shortest path in unweighted graphs; level-order traversal; web crawling

Path existence; cycle detection; topological sorting; maze solving

Shortest path in weighted graphs with non-negative edges; GPS navigation

Frequent insertions/deletions at the beginning; no random access needed

When you need efficient deletion from both ends; LRU cache implementation

Function call stack (recursion); expression evaluation; undo/redo; backtracking

BFS traversal; job scheduling; print spooler; buffering; breadth-first algorithms

Sliding window maximum/minimum; palindrome checking; undo-redo with limits

Fast lookups by key; counting frequencies; caching; deduplication

Problems that can be broken into identical subproblems of decreasing size

Problems with overlapping subproblems (DP), sequence generation

Tree operations; expression evaluation; serialization