All Topics

The sliding window technique is used when you need to find a contiguous subarray or substring that satisfies certain conditions. It maintains a window of elements and efficiently moves it across the data structure.

Dijkstra's algorithm finds the shortest path from a source node to all other nodes in a weighted graph with non-negative edge weights. It uses a greedy approach with a priority queue.

Two pointers is a technique where two pointers iterate through the data structure in tandem until one or both pointers hit a certain condition. It's often used to search pairs in sorted arrays or to optimize space complexity.

BFS explores a graph level by level, visiting all neighbors before moving to the next level. It's ideal for finding shortest paths in unweighted graphs and level-order traversals.

Dynamic Programming solves complex problems by breaking them down into simpler subproblems, storing solutions to avoid redundant calculations. It's applicable when problems have optimal substructure and overlapping subproblems.

Binary Search efficiently finds a target value in a sorted array by repeatedly dividing the search space in half. It can also be used to find optimal values in monotonic search spaces.

Union-Find is a data structure that tracks elements partitioned into disjoint sets. It supports two operations: union (merge two sets) and find (determine which set an element belongs to).

Backtracking is an algorithmic technique for solving problems recursively by trying to build a solution incrementally and abandoning solutions that fail to satisfy constraints.

A heap is a tree-based data structure that maintains the property that the parent is always greater (max-heap) or smaller (min-heap) than its children. It's commonly used as a priority queue.

A Trie is a tree-like data structure used to store and search strings efficiently. Each node represents a character, and paths from root to node represent prefixes.