AQAAS Level30 resources

AQA AS Computer Science Past Papers & Mark Schemes

Download free AQA AS Computer Science (7516) past papers, mark schemes & supplementary files. Paper 1: on-screen exam. Paper 2: written theory. 30 resources.

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30 of 30 resources — page 1 of 2

June 2023

9 files
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AS Computer Science – Question paper (Modified A4 18pt) (AS) : Paper 2 – June 2023

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AS Computer Science – Question paper (Modified A4 18pt) (AS) : Paper 1 – June 2023

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AS Computer Science – Question paper (Modified A3 36pt) (AS) : Paper 2 – June 2023

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AS Computer Science – Question paper (Modified A3 36pt) (AS) : Paper 1 – June 2023

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AS Computer Science – Question paper (AS) : Paper 2 – June 2023

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AS Computer Science – Question paper (AS) : Paper 1 – June 2023

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AS Computer Science – Mark scheme (AS) : Paper 2 – June 2023

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AS Computer Science – Mark scheme (AS) : Paper 1 – June 2023

Mark Scheme
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AS Computer Science – Insert (Modified A4 18pt) (AS) : Paper 2 – June 2023

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June 2022

9 files
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AS Computer Science – Question paper: Paper 1 – supplementary files – June 2022

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AS Computer Science – Question paper (Modified A4 18pt) (AS) : Paper 2 – June 2022

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AS Computer Science – Question paper (Modified A4 18pt) (AS) : Paper 1 – June 2022

Question Paper
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AS Computer Science – Question paper (Modified A3 36pt) (AS) : Paper 2 – June 2022

Question Paper
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AS Computer Science – Question paper (Modified A3 36pt) (AS) : Paper 1 – June 2022

Question Paper
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AS Computer Science – Question paper (AS) : Paper 2 – June 2022

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AS Computer Science – Question paper (AS) : Paper 1 – June 2022

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AS Computer Science – Mark scheme (AS) : Paper 2 – June 2022

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AS Computer Science – Mark scheme (AS) : Paper 1 – June 2022

Mark Scheme

November 2020

7 files
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AS Computer Science – Question paper: Paper 1 – supplementary files – November 2020

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AS Computer Science – Question paper (Modified A4 18pt) (AS) : Paper 2 – November 2020

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AS Computer Science – Question paper (AS) : Paper 2 – November 2020

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AS Computer Science – Question paper (AS) : Paper 1 – November 2020

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AS Computer Science – Mark scheme (AS) : Paper 2 – November 2020

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AS Computer Science – Mark scheme (AS) : Paper 1 – November 2020

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AS Computer Science – Insert (Modified A4 18pt) (AS) : Paper 2 – November 2020

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On-Screen Programming and Computational Theory: The Two Pillars of AS Computer Science

AQA AS Computer Science (specification 7516) combines practical programming skill with theoretical understanding of how computers represent, process, and communicate data. The 30 resources include past papers, mark schemes, and supplementary program files for the on-screen examination. Paper 1 (1 hour 30 minutes, 75 marks, 50%) is an on-screen examination where students write, test, and debug programs using their chosen programming language (Python, C#, or VB.NET). Questions progress from short program-reading tasks to substantial programming challenges requiring algorithm design, data structure selection, and systematic testing. The paper assesses ability to trace code, predict outputs, write functions and procedures, use selection and iteration structures, handle files, and implement standard algorithms. Supplementary program files (skeleton code) are provided for some questions. Paper 2 (1 hour 30 minutes, 75 marks, 50%) is a written theory paper covering the computational thinking and hardware/software concepts that underpin computer science. Topics include data representation (binary, hexadecimal, two's complement, floating point, character encoding, bitmapped graphics, sound sampling), computer architecture (von Neumann model, the fetch-decode-execute cycle, processor registers, buses, instruction sets), networking (topologies, protocols, TCP/IP stack, DNS, firewalls), fundamentals of algorithms (Big-O notation, searching and sorting algorithms), and the theory of computation (finite state machines, regular expressions, Mealy machines). The qualification values both practical competence and theoretical depth. Students who can write working programs but cannot analyse their time complexity, or who can describe network protocols but cannot implement a linked list, will find themselves limited. The strongest candidates integrate these two dimensions — understanding the theory behind the code they write.

Exam Paper Structure

Paper 1No calculator

On-Screen Programming Examination

ā± 1 hour 30 minutesšŸŽÆ 75 marksšŸ“Š 50% of grade
Code reading and output predictionWriting functions and proceduresFile handling and data structuresAlgorithm implementationTesting and debugging with skeleton code
Paper 2Calculator āœ“

Computational Thinking and Theory

ā± 1 hour 30 minutesšŸŽÆ 75 marksšŸ“Š 50% of grade
Data representation (binary, hex, floating point, encoding)Computer architecture (von Neumann, FDE cycle)Networking (protocols, TCP/IP, topologies)Algorithms (Big-O, searching, sorting)Theory of computation (finite state machines, regular expressions)

Key Information

Exam BoardAQA
Specification Code7516
QualificationAS Level
Grading ScaleA–E
Assessment Type1 on-screen + 1 written paper
Paper 1On-screen exam (1 hr 30 min, 75 marks, 50%)
Paper 2Written exam (1 hr 30 min, 75 marks, 50%)
Programming LanguagesPython, C#, or VB.NET
Supplementary FilesSkeleton code provided for Paper 1
CalculatorCalculator allowed (Paper 2)
Exam SessionsJune only
Total Resources30

Key Topics in Computer Science

Topics you need to know

Programming (functions, procedures, iteration, recursion)Data representation (binary, hexadecimal, floating point)Computer architecture (processor, memory, buses)Networking (protocols, TCP/IP, security)Algorithm analysis (Big-O notation, efficiency)Searching and sorting algorithmsFinite state machines and regular expressionsPractical coding and debugging skills

Exam Command Words

Command wordWhat the examiner expects
Write a program/functionProduce working code in your chosen language that correctly implements the specified behaviour
TraceStep through the code line by line, recording variable values at each stage in a trace table
ExplainDescribe a computing concept or process, using technical terminology and examples where appropriate
ConvertChange a value between number systems (binary, denary, hexadecimal) showing intermediate steps
StateGive a brief, factual answer — no explanation or working is required
Describe the purposeExplain what a piece of code or algorithm does and why — focus on function, not line-by-line narration

Typical Grade Boundaries

GradeApproximate mark needed
A60–70%
B49–59%
C39–48%
D29–38%
E19–28%

āš ļø AS Computer Science boundaries come from 150 raw marks total. The on-screen and written papers may have different difficulty profiles — check AQA's published data.

Reading Code Before Writing It, Binary Conversions, and Algorithm Analysis

The on-screen exam tests programming under pressure, and the most efficient preparation is practising with past paper skeleton code. Download the supplementary files, open them in your IDE, read through the existing code carefully, and then complete the tasks within the time allocation. The examiners design skeleton code with deliberate structure — understanding what the existing code does before you start modifying it is essential. Students who dive straight into writing without reading the context consistently introduce bugs or duplicate functionality. Code tracing questions carry significant marks and require systematic discipline. Create a trace table with one column per variable, step through each line of execution, and update values methodically. Pay particular attention to loop boundaries (off-by-one errors are deliberately tested), the scope of variables (local vs global), and recursive calls (track the call stack). Tracing is tedious but mechanical — if you follow the process systematically, you will get the correct answer. Binary arithmetic is examined every session. Practise converting between denary, binary, and hexadecimal until it is automatic. Two's complement representation requires careful attention to the sign bit — the range of an 8-bit two's complement number is āˆ’128 to +127, not āˆ’128 to +128. Floating-point representation divides the binary number into mantissa and exponent; normalisation requires the mantissa to start with either 0.1 (positive) or 1.0 (negative in two's complement). When analysing algorithms, Big-O notation describes how execution time grows as input size increases, not the actual execution time. Linear search is O(n) because in the worst case you check every element. Binary search is O(log n) because each comparison halves the remaining search space. Bubble sort is O(n²) because each pass through the list is O(n) and you may need n passes. The examiners want you to explain why an algorithm has its particular time complexity, not just state it.

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