AQA A Level Computer Science specification (7517)
Understanding the exam specification is key to doing well in your AQA A Level Computer Science exam. It lays out exactly what you need to learn, how you'll be assessed, and what skills the examiners seek. Whether you're working through the course for the first time or revising for your final exams, the specification helps you stay focused and confident in your preparation.
We've included helpful revision tools to support you in putting the specification into practice. Wherever you're starting from, you'll find everything you need to feel prepared, from the official specification to high-quality resources designed to help you succeed.
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In the next section, you'll find a simplified summary of the official AQA A Level Computer Science specification, along with a breakdown of key topics, assessment structure, and useful study resources. We've also included links to topic-level guides and revision tools to help you put the specification into practice.
Contents
Disclaimer
This page includes a summary of the official AQA A Level Computer Science (7517) specification, provided to support your revision. While we've made every effort to ensure accuracy, Save My Exams is not affiliated with the awarding body.
For the most complete and up-to-date information, we strongly recommend consulting the official AQA specification PDF.
Specification overview
This A-level Computer Science qualification offers students a strong foundation in both the theoretical and practical aspects of computing. It aims to develop a deep understanding of computational thinking, software design, and systems architecture, encouraging students to apply mathematical skills and logic to solve real-world problems. The course balances rigorous academic principles with opportunities for creativity and independent problem-solving through programming. With an emphasis on both analytical thinking and practical implementation, students gain skills highly valued in higher education and the workplace.Subject content breakdown
4.1 Fundamentals of programming
- Data types including integer, float, Boolean, string, date/time, pointers, arrays
- Programming constructs: selection, iteration, subroutines
- Exception handling, recursion, use of local/global variables
- Object-oriented and procedural paradigms, encapsulation, inheritance
4.2 Fundamentals of data structures
- Arrays, files, records; abstract data types: queue, stack, graph, tree, hash table
- Static vs dynamic structures; operations on queues, stacks, graphs, trees, hash tables
4.3 Fundamentals of algorithms
- Graph and tree traversal algorithms
- Sorting (bubble, merge), searching (linear, binary, tree)
- Dijkstra’s algorithm, Reverse Polish notation, algorithm complexity and Big-O
4.4 Theory of computation
- Abstraction types, decomposition, automation
- FSMs, regular expressions, context-free grammars (BNF)
- Algorithmic complexity, halting problem, Turing machines
4.5 Fundamentals of data representation
- Number systems (binary, hex, decimal), floating point, rounding, overflow
- Character encoding (ASCII, Unicode), error checking, image and sound representation
- Compression techniques, encryption (Caesar, Vernam)
4.6 Fundamentals of computer systems
- Hardware/software classification, operating systems, translators
- Logic gates and circuits, Boolean algebra, flip-flops
4.7 Fundamentals of computer organisation and architecture
- CPU architecture: buses, registers, fetch-execute cycle
- Assembly code, addressing modes, interrupts
- Input/output and storage devices (HDD, SSD, optical)
4.8 Consequences of uses of computing
- Ethical, legal, moral, social implications
- Responsibilities of software engineers, digital legislation challenges
4.9 Fundamentals of communication and networking
- Data transmission (serial, parallel, synchronous, asynchronous)
- Protocols (TCP/IP, HTTP, FTP, SMTP), IP addressing, NAT, DNS
- Network topologies, WiFi, internet structure, firewalls, encryption
4.10 Fundamentals of databases
- Entity-relationship modelling, relational schema
- Normalisation (up to 3NF), SQL queries, client-server databases
- Concurrency, record locks, serialisation
4.11 Big Data
- Characteristics: volume, velocity, variety
- Functional programming for distributed processing
- Graph schema, fact-based data models
4.12 Fundamentals of functional programming
- First-class functions, higher-order functions, recursion
- Functional constructs: map, filter, reduce
- Lists, head/tail processing, composition
4.13 Systematic approach to problem solving
- Software lifecycle: analysis, design, implementation, testing, evaluation
- Agile and prototyping methodologies
4.14 Non-exam assessment – computing practical project
- Independent investigation solving a real-world problem
- Includes analysis, design, implementation, testing, evaluation
- 75 marks allocated, majority for technical solution
Assessment structure
Paper 1
- On-screen exam: 2 hours 30 minutes
- 40% of A-level
- Assesses programming skills and topics from sections 10–13, 22
- Includes short questions and practical code tasks with provided skeleton code
Paper 2
- Written exam: 2 hours 30 minutes
- 40% of A-level
- Assesses theoretical knowledge from sections 14–21
- Includes compulsory short and extended response questions
Non-exam assessment
- Practical project based on a chosen real-world problem
- Assesses problem-solving, programming, documentation and evaluation
- 75 marks, 20% of A-level
Key tips for success
Doing well in your AQA A Level Computer Science isn't just about how much you study, but how you study. Here are a few proven tips to help you stay on track
- Start with a clear plan: Break the subject into topics and create a revision schedule that allows enough time for each. Start early to avoid last-minute stress.
- Focus on understanding, not memorising: Use our revision notes to build a strong foundation in each topic, making sure you actually understand the material.
- Practise regularly: Attempt past papers to familiarise yourself with the exam format and timing. Mark your answers to see how close you are to full marks.
- Be strategic with your revision: Use exam questions by topic to focus on weaker areas, and flashcards to reinforce important facts and terminology.
- Learn from mistakes: Whether it's from mock exams or practice questions, spend time reviewing what went wrong and why. This helps prevent repeat mistakes in the real exam.
- Stay balanced: Don't forget to take regular breaks, eat well, and get enough sleep, a healthy routine makes revision much more effective.
With the right approach and consistent practice, you'll build confidence and improve your chances of exam success.
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