2.3
Algorithms
Sorting, searching, path-finding, and algorithm analysis
Analysis and design of algorithmsSearching algorithmsSorting algorithmsGraph/tree traversalOptimisation algorithms
Big O notation: O(1) constant, O(n) linear, O(n²) quadratic, O(log n) logarithmic
Linear search: O(n), checks each element sequentially
Binary search: O(log n), requires sorted data, divides search space
Bubble sort: O(n²), swaps adjacent elements, simple but slow
Merge sort: O(n log n), divide and conquer, stable
Quick sort: O(n log n) average, O(n²) worst, in-place
Dijkstra's: Finds shortest path in weighted graph
A*: Uses heuristic for more efficient pathfinding
Exam Tips
- •Always define key terms before explaining concepts
- •Use specific examples where possible to demonstrate understanding
- •Check mark allocation - one point per mark is a good guide