Algorithms

Linear Search BigO

O(n)

Binary Search BigO

O(log n)

Bubble Sort BigO

O(n²)

Insertion Sort BigO

O(n²)

Merge Sort BigO

O(n log n)

Quick Sort BigO

O(n log n) average, O(n²) worst

Dijkstra’s Algorithm BigO

O((V + E) log V)

A* Algorithm BigO

O((V + E) log V)

Breadth-First Search (BFS)

O(V + E)

Depth-First Search (DFS) BigO

O(V + E)

Linear Search

Checks each item one-by-one until the target is found or end is reached

Binary Search

Repeatedly divides a sorted list in half to find the target

Bubble Sort

Repeatedly compares adjacent items and swaps if needed

Insertion Sort

Inserts each item into its correct place in a sorted part of the list

Merge Sort

Divides list into halves, sorts them recursively, then merges

Quick Sort

Picks a pivot, partitions the list, then sorts partitions recursively

Selection Sort

Repeatedly finds the smallest item and swaps it into the correct position

Dijkstra’s Algorithm

Finds shortest path from a starting node to all others using a priority queue

A* Algorithm

Improves Dijkstra’s by using a heuristic to guide the search faster

Breadth-First Search (BFS)

Uses a queue to explore all neighbours level by level

Depth-First Search (DFS)

Uses a stack (often recursion) to explore as deep as possible before backtracking

Hash Table

Uses a hash function to map keys to indices for fast lookup

Binary Search Tree (BST)

Inserts and finds elements using binary tree rules

Recursive Algorithm

Calls itself with a subset of the input to solve problems

Backtracking

Tries all possible options and backtracks when stuck