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A-Level Computer Science Revision

Algorithms & Computation

Searching, sorting and graph algorithms, recursion, Big-O complexity and the theory of computation.

Quick check · one tap
Does Big-O notation tell you how many seconds an algorithm will take?

Algorithms & Computation is a core part of A-Level Computer Science. Revise the key concepts and common mistakes below, then lock them in with the free games.

Key concepts

AlgorithmA precise step-by-step method for solving a problem.
Pseudocode & flowchartsWays to express an algorithm before coding.
SearchingLinear search (any list) and binary search (sorted list).
SortingOrdering data, e.g. bubble, merge and insertion sort.
DecompositionBreaking a problem into smaller parts.
AbstractionHiding unnecessary detail to focus on what matters.
Binary TreeA tree where each node has at most two children.
GraphA set of vertices connected by edges, directed or undirected.
DFSDepth-first search — explores as deep as possible before backtracking.
BFSBreadth-first search — explores all neighbours before going deeper.
Merge SortA divide-and-conquer sort with O(n log n) time complexity.
QuicksortA divide-and-conquer sort averaging O(n log n), worst O(n^2).

What your exam board covers

Where Algorithms & Computation sits in each exam board's specification. Tap a board to see what it lists.

AQATheory of computationSpec 7517
  • Abstraction and automation
  • Finite state machines
  • Regular expressions and Backus-Naur Form
  • Turing machines
  • Big-O notation and complexity
  • Computable and non-computable problems

Source: AQA A-level Computer Science (7517) specification — Subject content, accessed 23 June 2026.

OCRComponent 2 — Algorithms and programmingSpec H446
  • Elements of computational thinking
  • Problem solving and programming
  • Algorithms to solve problems and standard algorithms

Source: OCR A Level Computer Science (H446) specification, accessed 23 June 2026.

Learn Algorithms & Computation step by step

Free interactive mini-lessons: short screens, worked examples and quick checks. Pick your exam board:

Common mistakes to avoid

Questions where students often pick the tempting wrong answer — make sure you know the right one:

Does Big-O notation tell you how many seconds an algorithm will take?✗ Yes - O(n) means the algorithm takes n seconds to run.   ✓ No - Big-O describes the growth rate of work relative to input size, ignoring constants and hardware; actual seconds depend on the machine and implementation.
Is quicksort always faster than merge sort?✗ Yes - the name quicksort means it is the fastest sort in all cases.   ✓ No - quicksort averages O(n log n) but degrades to O(n^2) with poor pivots, while merge sort guarantees O(n log n) in every case.
A* differs from Dijkstra's algorithm because A*:✗ Only works on unweighted graphs   ✓ Adds a heuristic estimate of the distance remaining to the goal
What is the worst-case complexity of bubble sort?✗ O(n) because it just passes through the list.   ✓ O(n squared).

Practise Algorithms & Computation — free games

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More A-Level Computer Science topics

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