← Back to all tools

⚔️ Which Algorithm is Faster? — Algorithm Battleground

Pick two algorithms, same data, and watch them race. Who finishes first?

Designed with the WJEC specification in mind
CS GCSE §1.4CS A-Level Unit 3

🤔 What is algorithm comparison?

Not all algorithms are created equal! Some work great on small datasets but struggle with large ones. This battleground lets you pit two algorithms against each other to see which performs better on the same task.

🍕 Analogy: It's like a race between a bicycle and a motorbike. The bike might win in a quick sprint, but the motorbike dominates on long journeys!
VS
Merge Sort O(n log n)
Comparisons: 0 Swaps: 0 Time:
Bubble Sort O(n²)
Comparisons: 0 Swaps: 0 Time:
📖

Algorithm Complexities

AlgorithmBestAverageWorstStable?
Bubble SortO(n)O(n²)O(n²)
Insertion SortO(n)O(n²)O(n²)
Selection SortO(n²)O(n²)O(n²)
Merge SortO(n log n)O(n log n)O(n log n)
Quick SortO(n log n)O(n log n)O(n²)
📝

Exam Tips

  • GCSE: Know that some algorithms are faster than others on large datasets
  • A-Level: Understand Big O notation: O(n) beats O(n log n) beats O(n²)
  • Key point: Best case vs worst case can be very different (especially for quick sort)
  • Remember: Sometimes "slower" algorithms work better on small or nearly-sorted data