Data Structures & Algorithms

Big-O intuition, the core data structures, and the pattern-recognition mindset everything else builds on.

Hash maps and sets as the universal O(1) lookup weapon, plus prefix/suffix products.

Squeezing a sorted search space from both ends instead of brute-forcing pairs.

Fixed and elastic windows over arrays and strings, plus the monotonic deque for window maximums.

LIFO thinking, expression evaluation, and the monotonic stack for next-greater problems.

Halving on indices, rotated arrays, and the powerful binary-search-on-the-answer trick.

Pointer surgery, dummy nodes, fast/slow pointers, and k-way merging.

Recursion on binary trees, BFS by level, BST ordering, and the bubble-up answer pattern.

Top-k selection, streaming medians, quickselect, and repeated take-the-best scheduling.

Systematically exploring all choices with the choose-explore-undo loop.

Prefix trees for dictionaries, wildcards, and multi-word grid search.

Flood fill, multi-source BFS, topological ordering, and union-find connectivity.

Weighted shortest paths, minimum spanning trees, and Eulerian paths.

From Fibonacci to LIS: caching overlapping subproblems along one dimension.

Two shrinking dimensions: string alignment, knapsacks, grids, and interval DP.

Locally optimal choices that provably never need regretting.

Sorting, merging, and sweeping over ranges of time.

Matrix choreography, digit arithmetic, and geometric counting tricks.

XOR cancellation, bit counting tricks, and carry-free arithmetic.