Cambridge (CIE) International AS Computer Science specification (9618)
Understanding the exam specification is key to doing well in your Cambridge (CIE) International AS 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 Cambridge (CIE) International AS 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 Cambridge (CIE) International AS Computer Science (9618) 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 Cambridge (CIE) specification PDF.
Specification overview
Cambridge International AS Level Computer Science aims to develop learners' computational thinking skills and their ability to solve problems using computers. The course fosters a deep understanding of the components of computer systems and their interrelationships, covering software, data, hardware, communication, and people. Students learn methods of communication, networking, and the internet's functionality, alongside the practical application of this knowledge to design computer-based solutions. The syllabus encourages learners to be confident in using various technologies, responsible in ethical considerations, reflective in programming practice, innovative in creating efficient solutions, and engaged in understanding technology, its construction, and software development.Subject content breakdown
1 Information representation
- Binary magnitudes, prefixes (kibi, kilo, mebi, mega, gibi, giga, tebi, tera)
- Number systems: binary, denary, hexadecimal, BCD, one’s and two’s complement
- Binary arithmetic, overflow, applications of BCD and Hexadecimal
- Character data representation: ASCII, extended ASCII, Unicode
- Bitmap and vector graphic encoding, file size estimation, resolution and colour depth
- Sound data representation: sampling, rate, resolution, analogue/digital
- Compression: lossy, lossless, RLE, application to various file types
2 Communication
- Network devices and benefits, LAN/WAN, client-server and peer-to-peer models
- Thin/thick clients, network topologies, packet transmission
- Cloud computing, wireless vs wired networks, network hardware
- Router functions, Ethernet and CSMA/CD, bit streaming (real-time/on-demand)
- Internet vs WWW, IP addressing (IPv4, IPv6, subnetting), static/dynamic, DNS
3 Hardware
- Input/output, memory types, embedded systems
- Hardware operations and devices, buffering, RAM vs ROM, SRAM vs DRAM
- PROM, EPROM, EEPROM, monitoring/control systems, sensors, actuators, feedback
4 Processor Fundamentals
- Von Neumann model, registers, ALU, CU, buses, performance factors, ports
- Fetch-execute cycle, interrupts and ISR handling
5 System Software
- OS roles: memory, file, security, hardware, process management
- Utility software, program libraries, language translators (assembler, compiler, interpreter)
- IDE features: coding, error detection, debugging tools
6 Security, privacy and data integrity
- Data security, privacy, integrity, threats, security measures, validation, verification
7 Ethics and Ownership
- Professional ethics, ethical bodies, copyright, licensing types, AI implications
8 Databases
- File-based vs relational, database terminology, E-R diagrams, normalisation (1NF–3NF)
- DBMS features, tools, DDL and DML with SQL (CREATE, ALTER, SELECT, JOIN, INSERT, DELETE, UPDATE)
9 Algorithm Design and Problem-solving
- Abstraction, decomposition, algorithm definition, pseudocode, flowcharts, stepwise refinement
10 Data Types and Structures
- Data types, record structures, arrays (1D, 2D), file handling, ADTs (stack, queue, linked list)
11 Programming
- Pseudocode implementation, variable handling, built-in functions
- Constructs: IF, CASE, loops, structured programming, procedures, functions, parameters
12 Software Development
- Life cycle models, stages of development, structure charts, state-transition diagrams
- Testing types, test strategies and data, program maintenance
Assessment structure
Paper 1 Theory Fundamentals
- 1 hour 30 minutes, 75 marks
- Assesses sections 1–8 of the syllabus
- Written paper with all questions compulsory
- 50% of AS Level, 25% of A Level
Paper 2 Fundamental Problem-solving and Programming Skills
- 2 hours, 75 marks
- Assesses sections 9–12 of the syllabus
- Written paper requiring pseudocode answers
- All questions compulsory
- 50% of AS Level, 25% of A Level
Paper 3 Advanced Theory
- 1 hour 30 minutes, 75 marks
- Assesses sections 13–20 of the syllabus
- Written paper with all questions compulsory
- 25% of A Level
Paper 4 Practical
- 2 hours 30 minutes, 75 marks
- Assesses sections 19–20 (except low-level and declarative programming)
- Candidates submit complete program code and testing evidence
- Programming in Java (console), Visual Basic (console), or Python (console)
- Computer-based assessment without internet/email access
- 25% of A Level
Assessment Routes
- AS Level: Papers 1 & 2 in same series
- A Level (staged): AS Level in Year 1 (Papers 1 & 2), Papers 3 & 4 in Year 2
- A Level (linear): Papers 1, 2, 3 & 4 in same series
Assessment Objectives Weighting
- AO1 (Knowledge): 30% AS, 30% A Level
- AO2 (Application): 40% AS, 30% A Level
- AO3 (Design/Programming/Evaluation): 30% AS, 40% A Level
Key tips for success
Doing well in your Cambridge (CIE) International AS 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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