Big‑O Time & Space Complexity – OCR A Level Computer Science (H446)

A concise revision / reference sheet covering Big‑O time and space complexity for OCR A Level Computer Science (H446). It summarises common complexity classes, data structures, and algorithms using clear, exam‑appropriate language and examples.

Designed for A Level Computer Science students studying OCR H446, and for teachers looking for a clear reference to support teaching and revision. Suitable for independent study, classroom use, or last‑minute exam preparation.

One professionally formatted PDF
Tables summarising time and space complexity for common data structures and algorithms
Clear explanations of common Big‑O growth rates
Exam‑focused notes highlighting worst‑case vs average‑case behaviour

This resource can be:
Used by students as a revision aid or quick reference
Displayed or projected during lessons
Printed for individual or class use
Used to support answers to “explain why” Big‑O exam questions

Common Big‑O growth rates (e.g. constant, linear, linearithmic, quadratic)
Key assumptions such as worst‑case complexity unless stated otherwise
Clarification of typical causes (loops, recursion, divide‑and‑conquer)

All complexities are aligned with OCR A Level Computer Science (H446) expectations
Insert and delete operations refer to arbitrary positions unless stated otherwise
Provided as a PDF to preserve layout and formatting across devices