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GCSE Computer Science Revision
Master GCSE Computer Science with our AI revision tool, built by qualified computing teachers. Covering AQA, Edexcel, and OCR specifications, get instant help with programming concepts, algorithms, and theory topics. Our intelligent system breaks down complex coding problems and explains technical concepts in ways that make sense, not more confusion.
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Decomposition: breaking problems into smaller partsAbstraction: removing unnecessary detailUsing decomposition + abstraction to model real-world problemsWhy subprograms help (reuse, readability, testing)What an algorithm is (inputs, processing, outputs)Flowcharts: reading and writing standard symbolsPseudocode: writing clear, language-agnostic stepsProgram code as an algorithm representationSequence: writing steps in the correct orderSelection: making decisions with conditionsRepetition: count-controlled loopingRepetition: condition-controlled loopingIteration over a data structure (looping through items)Variables and constants in algorithmsOne-dimensional data structures in algorithms (arrays, strings)Two-dimensional data structures in algorithms (2D arrays/tables)Records as a way to group related fieldsArithmetic operators in algorithms (modulus, integer division, exponentiation)Relational operators in algorithms (comparisons)Logical operators in algorithms (AND, OR, NOT)Trace tables: tracking variable values step-by-stepPredicting the output for given test dataTypes of errors: syntax, runtime and logicFinding and fixing logic errors in an algorithmLinear search: how it works and when to use itBinary search: how it works and when to use itBubble sort: how it works and how many passes it needsMerge sort: splitting and merging step-by-stepChoosing test data (normal, boundary and erroneous)Judging fitness for purpose using logical reasoning + test dataComparing algorithm efficiency (compares, loop passes, memory use)Truth tables with AND, OR, NOT (up to three inputs)Using truth tables to solve logic problems
Why computers use binary for data and instructionsCounting states: how many values a bit pattern can representUnsigned integers in binaryTwo’s complement signed integers: what it representsConverting denary to 8-bit binary (0 to 255)Converting denary to 8-bit binary with two’s complement (-128 to +127)Converting binary back to denary (unsigned and signed)Binary addition (positive numbers)Logical shifts: shifting bits and the effect on valuesArithmetic shifts: preserving sign in signed numbersOverflow: when values don’t fit the available bitsWhy hexadecimal is usefulConverting binary ↔ hexadecimalCharacter encoding with 7-bit ASCIIBitmap images: pixels, resolution and colour depthCalculating bitmap image file sizeAnalogue sound concepts: amplitude and samplingSound representation: sample rate, bit depth and sample intervalCalculating sound file sizeLimits of representation when bits are constrained (rounding/precision)Storage units in binary multiples (bit to tebibyte)File size and storage capacity calculationsWhy compression is needed (storage + transmission)Lossless vs lossy compression: what changes and when to use eachLossless compression example: Run-Length Encoding (RLE)Lossless compression example: Huffman coding (basic idea and purpose)
The stored program concept (von Neumann idea)The CPU’s role in processing and controlControl unit: what it does in a CPUALU: what it does in a CPURegisters: why they’re fast and what they storeRAM: purpose and why it’s needed while programs runThe system clock: why clock speed mattersAddress bus, data bus and control bus (what each carries)Fetch stage of the fetch-decode-execute cycleDecode stage of the fetch-decode-execute cycleExecute stage of the fetch-decode-execute cycleSecondary storage: why it’s needed (non-volatile storage)Magnetic storage: how it stores data and typical usesOptical storage: how it stores data and typical usesSolid state storage: how it stores data and typical usesChoosing storage: speed, capacity, portability and cost trade-offsEmbedded systems: what they areEmbedded systems: real-world uses and constraintsOperating system jobs: file managementOperating system jobs: process managementOperating system jobs: peripheral managementOperating system jobs: user managementUtility software: file repairUtility software: backup (including why it matters)Utility software: data compression tools (what they do)Utility software: disk defragmentation (why it’s used)Utility software: anti-malware (what it protects against)Robust software: why it mattersFinding vulnerabilities using audit trailsFinding vulnerabilities using code reviewsLow-level vs high-level languages: characteristics and purposeTranslators overview: why translation is neededCompilers vs interpreters: key differences and impacts
Why computers are connected in networks (shared resources + communication)LANs vs WANs: features and typical examplesHow the internet is structured (routers + IP addressing)IP addresses: what they are used for (basic purpose)Routers: what they do in directing dataWired vs wireless: speed, range, latency and bandwidthNetwork speed units (bits per second: kilobit/megabit/gigabit)Calculating transfer time from file size and transmission rateCalculating required transmission rate for a given time limitWhy protocols are needed (standards for communication)Ethernet and Wi-Fi: what they are used forTCP/IP: why it matters as a protocol suiteHTTP vs HTTPS: what changes and why it mattersFTP: what it’s used forEmail protocols: SMTP, POP3 and IMAP (what each does)TCP/IP 4-layer model: what a “layer” meansApplication layer: what it’s responsible forTransport layer: what it’s responsible forInternet layer: what it’s responsible forLink layer: what it’s responsible forBus topology: structure, strengths and weaknessesStar topology: structure, strengths and weaknessesMesh topology: structure, strengths and weaknessesWhy network security mattersNetwork vulnerabilities: what they are and why they happenPenetration testing: what it is used forEthical hacking: what it is and why it’s doneAccess control as a protection methodPhysical security as a protection methodFirewalls as a protection method
Environmental impacts of digital devices: energy consumptionEnvironmental impacts of digital devices: manufacture of hardwareEnvironmental impacts of digital devices: replacement cyclesEnvironmental impacts of digital devices: disposal and e-wastePersonal data: what it is and why it’s valuablePrivacy risks from collecting personal dataData ownership and consent (what “informed consent” looks like)Misuse of personal data (common examples)Data protection principles (what laws try to enforce)AI/ML/robotics: what makes them ethically challengingAccountability in AI decisions (who is responsible?)Safety risks in automated systemsAlgorithmic bias: how it happens and why it mattersLegal liability for AI/robotics failures (basic idea)Copyright: protecting creative software and digital contentPatents: protecting inventions and technical ideasTrademarks: protecting brand identityLicensing: rules for using software legallyMalware overview: what it is and what it doesViruses, worms and Trojans: how they differRansomware: how it attacks and what it demandsKey loggers: what they capture and whyExploiting unpatched software: why updates matterOut-of-date anti-malware: why protection can failSocial engineering: manipulating users to gain accessProtecting systems with anti-malwareProtecting data with encryption (basic purpose)Acceptable use policies: what they do and whyBackup and recovery procedures: reducing damage after attacks
Turning a problem statement into a plan using decompositionUsing abstraction to decide what details to include in codeReading code to understand purpose, inputs and outputsTracing program execution to predict outputsRefining code for clarity and maintainabilityConverting flowcharts into working programsConverting pseudocode into working programsConstants, variables, initialisation and assignmentInput, processing and output in a programSequence in real programsSelection in real programs (if/else style decisions)Repetition: count-controlled loops in programsRepetition: condition-controlled loops in programsIteration through each item in a data structureSingle entry/exit code blocks (structured programming idea)Primitive data types in code (integer, real, Boolean, char)Strings: storing and using textArrays: storing multiple values in one structureTwo-dimensional arrays: storing grid/table dataRecords: grouping fields for one “thing”Choosing variables vs constants appropriatelyString manipulation: length and positionsString manipulation: substringsString manipulation: case conversionValidating user input: length checksValidating user input: presence checksValidating user input: range checksValidating user input: pattern checksAuthentication in code: ID/password and lookup approachWriting programs that respond appropriately to user inputReading from CSV text filesWriting to CSV text filesArithmetic operators in programs (modulus and integer division)Exponentiation in programs (when and why)Relational operators in programs (comparisons)Logical operators in programs (AND, OR, NOT)Using pre-existing (built-in/library) subprograms appropriatelyWriting procedures: structure and purposeWriting functions: structure and purposeParameters and arguments: passing data into subprogramsReturn values: getting data back from a functionGlobal vs local variables: scope and good practiceDebugging: spotting syntax errors quicklyDebugging: fixing runtime errors safelyDebugging: finding logic errors using test data
