Data Structures

A data structure organizes state so that a chosen set of operations is efficient. There is no universally best structure: select one from the operations, invariants, ordering requirements, memory constraints, and concurrency model.

Structure	Important operations	Typical use
Dynamic array	Indexed access, append	Ordered sequences and iteration
Linked list	Local insertion/removal	Node-oriented algorithms
Stack	Push and pop	Parsing, DFS, undo
Queue	Enqueue and dequeue	Scheduling, BFS
Hash table	Lookup by key	Indexes, sets, caches
Search tree	Ordered lookup	Range queries and sorted maps
Heap	Find/remove priority extreme	Schedulers and graph algorithms
Disjoint set	Merge and connectivity	Kruskal and components
Graph	Relationships	Networks, dependencies, routes

Complexities on the following pages assume valid inputs and conventional implementations. Expected bounds for hashing depend on a suitable hash function and resizing policy.

A hash table can implement lookup inside memoization or an application cache, but the data structure alone does not define lifetime, freshness, eviction, or concurrency semantics.