OCR · A Level · H446
Computer Science — Keywords & Key Terms — Definitions Glossary (2026)
OCR A Level Computer Science (H446)
Topic-by-topic keywords, key terms and definitions for precise exam language—separate from our revision checklists (topic coverage) and formula sheets (equations).
Keywords & Key Terms — definitions
Examiner-style keywords and definitions organised by syllabus topic. Terms are tagged Essential (start here), Core (typical exam standard), and Advanced for harder distinctions — tick each row when you can recall it. Your progress is saved in this browser for this list.
OCR A Level Computer Science (H446)
OCR A Level Computer Science (H446)
OCR A Level Computer Science (H446)
OCR H446 (2026) covers computer systems (Paper 1), algorithms and programming (Paper 2), and a programming project (NEA) — assesses theoretical understanding alongside computational thinking and problem-solving in code.
Mark schemes: OCR rewards precise technical vocabulary: name registers exactly (PC, MAR, MDR, CIR, ACC, SR), state Big-O complexity classes correctly, and reference protocols by full name. Algorithm trace tables must show every iteration. Programming project mark scheme rewards documented design decisions, iterative testing, and evaluation against measurable success criteria.
Active recall: 0 / 21 terms ticked
| Recalled | Topic | Level | Keyword | Definition |
|---|---|---|---|---|
| Computer architecture & hardware | Essential | Von Neumann architecture | Single shared memory and bus storing both instructions and data sequentially. | |
| Computer architecture & hardware | Core | Fetch–decode–execute cycle | Repeated CPU process retrieving, interpreting, and carrying out each program instruction. | |
| Computer architecture & hardware | Core | CPU registers | Special fast stores: PC, MAR, MDR, CIR, ACC, SR each with defined roles. | |
| Computer architecture & hardware | Core | Memory hierarchy | RAM is volatile working memory, ROM is non-volatile firmware, cache speeds frequent access. | |
| Computer architecture & hardware | Advanced | RISC vs CISC | RISC uses few simple fixed-length instructions, CISC uses many complex variable-length ones. | |
| Algorithms & data structures | Core | Big-O notation | Worst-case time growth: O(1), O(log n), O(n), O(n log n), O(n²), O(2ⁿ). | |
| Algorithms & data structures | Core | Search algorithms | Linear scans every element O(n), binary halves a sorted list O(log n). | |
| Algorithms & data structures | Core | Sorting algorithms | Bubble O(n²), merge O(n log n) divide-and-conquer, quicksort average O(n log n) using pivot. | |
| Algorithms & data structures | Advanced | Graph traversal | Dijkstra's and A* find shortest paths; BFS uses queues, DFS uses stacks. | |
| Algorithms & data structures | Core | Abstract data structures | Stacks, queues, lists, hash tables, trees, and graphs organise data logically. | |
| Programming paradigms | Essential | Procedural programming | Sequence of instructions grouped into procedures or functions modifying shared state. | |
| Programming paradigms | Core | Object-oriented programming | Classes encapsulate data and methods, supporting inheritance and polymorphism. | |
| Programming paradigms | Core | Encapsulation | Bundling attributes and methods inside a class, hiding internal state from outside code. | |
| Programming paradigms | Advanced | Functional programming | Stateless evaluation of pure functions using first-class functions and immutability. | |
| Programming paradigms | Advanced | Declarative paradigm | Programmer specifies what result is required, not the step-by-step procedure. | |
| Networks & data representation | Core | TCP/IP layers | Four-layer stack: application, transport, internet, link handling end-to-end communication. | |
| Networks & data representation | Core | IP addressing | IPv4 uses 32-bit addresses, IPv6 uses 128-bit addresses to overcome exhaustion. | |
| Networks & data representation | Core | Encryption | Symmetric uses one shared key, asymmetric uses public-private pair as in RSA. | |
| Networks & data representation | Core | Two's complement | Standard signed binary where the most significant bit has negative weight. | |
| Networks & data representation | Advanced | IEEE 754 floating point | Standard format storing sign, biased exponent, and normalised mantissa. | |
| Networks & data representation | Advanced | Boolean algebra | Logic simplification using De Morgan's laws, distribution, and absorption rules. |
Pair this with our revision checklists, formula sheets hub and past paper finder.
Computer Science (H446) — Keywords & Key Terms FAQ
- What is on this OCR A Level Computer Science keywords and key terms list?
- It is a topic-organised glossary of important computer science terms with short, exam-style definitions aligned to OCR A Level Computer Science (H446) (H446). It is designed for “define”, “state”, “outline” and “explain” questions where precise vocabulary earns marks.
- How should I use this Computer Science glossary alongside past papers?
- Tick terms when you can recall them without reading the answer, then check your wording against mark schemes. Pair vocabulary practice with past papers for A Level Computer Science (H446) so you apply terms in context.
- Is this the same as a revision checklist or a formula sheet?
- No. Revision checklists help you track which syllabus topics you have covered and your confidence—separate pages on Tutopiya. Formula sheets summarise equations and quantitative relationships. This page is only a definitions and key-terms glossary for Computer Science.
- Can I download this Computer Science keywords and key terms list for free?
- Yes. After a quick free sign-up you can download a UTF-8 CSV (opens in Excel or Google Sheets) or open a print-friendly page and save as PDF. Browsing the list on the page is free.
- Is this Computer Science list aligned to the H446 specification?
- Topic groupings and wording follow OCR A Level Computer Science (H446) for OCR A Level. Always confirm final learning objectives and any regional options in your official specification and recent examiner reports for your exam session.
- Why focus on definitions instead of full notes?
- Mark schemes reward correct technical terms and clear links between ideas. A compact glossary lets you drill the exact language examiners expect for Computer Science at A Level, separate from longer notes or topic trackers.