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OCR GCSE Computer Science revision notes

Concise notes per spec point, written in plain English with worked examples. AI-generated, admin-verified.

  1. 1.1.1The CPU — purpose, the fetch–decode–execute cycle, common CPU components (ALU, CU, cache, registers)
  2. 1.1.2CPU performance: clock speed, cache size, number of cores; how each affects performance
  3. 1.1.3Embedded systems: definition, characteristics and examples (washing machines, microwaves, vehicle ECUs)
  4. 1.2.1Primary storage (memory): RAM and ROM, the need for primary storage, virtual memory and the role of cache
  5. 1.2.2Secondary storage: optical, magnetic and solid-state; comparing capacity, speed, durability, cost and reliability
  6. 1.2.3Units: bit, nibble, byte, KB, MB, GB, TB, PB; converting between units
  7. 1.2.4Number representations: denary, binary and hexadecimal; converting between them; binary addition and binary shifts
  8. 1.2.5Character encoding: ASCII (7-bit) and Unicode; representing text and storage requirements
  9. 1.2.7Sound representation: sampling, sample rate, bit depth; calculating audio file size
  10. 1.2.8Compression: lossy vs lossless, the need for compression and trade-offs
  11. 1.3.1Networks and topologies: LAN/WAN, factors affecting performance, client–server vs peer-to-peer, star and mesh topologies
  12. 1.3.2Wired vs wireless networks: hardware (NIC, switch, router, transmission media) and the differences in speed, range, security
  13. 1.3.3Protocols: TCP/IP, HTTP/HTTPS, FTP, SMTP, IMAP, the 4-layer TCP/IP model and why layers are used
  14. 1.4.1Threats: malware, social engineering (phishing, blagging), brute-force attacks, denial-of-service, data interception, SQL injection
  15. 1.4.2Identifying and preventing vulnerabilities: penetration testing, anti-malware, firewalls, user-access levels, passwords, encryption, physical security
  16. 1.5.1Operating systems: user interface, memory and process management, peripheral and device management, file management, user management
  17. 1.5.2Utility software: encryption, defragmentation, data compression and back-up software
  18. 1.6.1Ethical issues: AI bias, censorship, surveillance, the digital divide; weighing benefits and harms
  19. 1.6.2Legal issues and key legislation: Data Protection Act 2018, Computer Misuse Act 1990, Copyright Designs and Patents Act 1988, software licences
  20. 1.6.3Cultural and environmental issues: data centres, e-waste, manufacture, disposal; circular-economy and recycling strategies
  21. 2.1.1Computational thinking: abstraction, decomposition, algorithmic thinking; using these in problem-solving
  22. 2.1.2Designing, creating and refining algorithms: pseudocode, flowcharts and trace tables
  23. 2.1.3Searching algorithms: linear search and binary search; preconditions, step counts and trade-offs
  24. 2.1.4Sorting algorithms: bubble sort, merge sort, insertion sort; tracing each pass and comparing efficiency
  25. 2.2.1Programming concepts: variables, constants, sequence, selection (IF), iteration (WHILE, FOR), input/output
  26. 2.2.2Operators: arithmetic (+, −, *, /, MOD, DIV, ^), comparison (=, ≠, <, ≤, >, ≥), Boolean (AND, OR, NOT)
  27. 2.2.3Data types: integer, real, Boolean, character, string; choosing an appropriate type
  28. 2.2.5Arrays: 1D and 2D arrays; iterating, reading and writing values
  29. 2.2.8Subroutines (procedures and functions): parameters and return values; local vs global variables; benefits
  30. 2.3.1Defensive design: input sanitisation/validation, anticipating misuse, authentication, code maintainability
  31. 2.3.2Testing: iterative vs final testing, types of test data (normal, boundary, invalid/erroneous) and refining solutions
  32. 2.4.1Logic gates AND, OR, NOT; constructing logic circuits and truth tables; combining gates
  33. 2.4.2Simplifying logic: writing Boolean expressions for simple problems; testing equivalence with truth tables
  34. 2.5.1Languages: high-level vs low-level; characteristics and uses; need for translators
  35. 2.5.2Translators: compilers vs interpreters; assemblers