AQA GCSE Computer Science, Second Edition

267 Pages·2020·19.9 MB·English

by  George Rouse, Lorne Pearcey, Gavin Craddock

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FOR THE
8525
SPECIFICATION
AQA
GCSE
(9–1)
Computer
Science
Second Edition
George Rouse
Lorne Pearcey
Gavin Craddock
9781510484306_AQA_GCSE_Computer_Science_FM.indd 1 19/08/20 10:56 PM
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ISBN: 978 1 5104 8430 6
© George Rouse, Lorne Pearcey and Gavin Craddock 2020
First published in 2020 by
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Printed in Italy
A catalogue record for this title is available from the British Library.
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CONTENTS
How to use this book v
1 FUNDAMENTALS OF ALGORITHMS 1
1.1 Representing algorithms 1
1.2 Efficiency of simple algorithms 8
1.3 Sorting and searching algorithms 9
2 PROGRAMMING 25
2.1 Data types 26
2.2 Programming concepts 28
2.3 Arithmetic operations 37
2.4 Relational operations 38
2.5 Boolean operations 40
2.6 Data structures 42
2.7 Input and output 46
2.8 String-handling operations 46
2.9 Random number generation 49
2.10 Structured programming and subroutines 50
2.11 Robust and secure programming 55
3 FUNDAMENTALS OF DATA REPRESENTATION 80
3.1 Number bases 81
3.2 Converting between number bases 83
3.3 Units of information 90
3.4 Binary arithmetic 91
3.5 Character encoding 95
3.6 Representing images 97
3.7 Representing sound 100
3.8 Data compression 103
4 COMPUTER SYSTEMS 123
4.1 Hardware and software 124
4.2 Boolean logic 124
4.3 Software classification 134
4.4 Classification of programming languages and translators 138
4.5 Systems architecture 143
iii
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5 FUNDAMENTALS OF COMPUTER NETWORKS 169
5.1 Computer networks 169
6 CYBER SECURITY 188
6.1 Fundamentals of cyber security 188
6.2 Cyber security threats 188
6.3 Methods to detect and prevent cyber security threats 194
7 RELATIONAL DATABASES AND STRUCTURED QUERY LANGUAGE (SQL) 200
7.1 Relational databases 200
7.2 Structured Query Language (SQL) 203
8 ETHICAL, LEGAL AND ENVIRONMENTAL IMPACTS OF DIGITAL TECHNOLOGY
ON WIDER SOCIETY 211
8.1 Ethical, legal and environmental impacts and risks of digital technology 211
GLOSSARY 221
KNOWLEDGE CHECK ANSWERS 226
QUESTION PRACTICE ANSWERS 234
INDEX 252
ACKNOWLEDGEMENTS 257
iv
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HOW TO USE THIS BOOK
To help you get the most out of it, this textbook uses the following learning features:
Important words
Highlighted in green, these are terms that you will be expected to know and understand in
your exams.
Important words
You will need to know and understand the following terms:
algorithm
decomposition
abstraction
Tech terms
Jargon or technical definitions in blue that you may find useful.
Tech terms
Inverter An alternative name for a NOT gate, because the output inverts the input.
Key point
An important idea or concept.
Key point
A computer program is an implementation of an algorithm – an algorithm is not a computer program!
Worked examples
Used to illustrate an idea or a concept, these will guide you through the reasoning behind
each step of a calculation or process.
Worked example
←
FOR a 1 to 4
←
FOR b 1 to 3
OUTPUT a * b
ENDFOR
ENDFOR
v
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Beyond the spec
Information that you will not be expected to know or state in an exam but will aid
understanding or add some useful context..
Beyond the spec
Computer Scientists use ‘Big O notation’ to measure mathematically how
efficient algorithms are. Big O attempts to measure the change in efficiency
as the size of the data input increases. This is covered fully in the A-level
Computer Science specification.
Knowledge check
Quick check-ins that help you to recap and consolidate your understanding of the
previous section.
Knowledge check
1 Define the following terms:
(a) Decomposition
(b) Abstraction
2 A programmer is creating software to send and receive encrypted messages
via email. Describe how decomposition can be used to allow this problem to
be solved.
Recap and review
A targeted summary of everything you have learned in the chapter. Use this to
help you recap as you work through your course.
Question practice
More formal questions to help you to prepare for both examination papers.
Answers
Answers to all of the Knowledge check and Question practice questions
are at the back of the book and also at www.hoddereducation.co.uk/
AQAGCSEComputerScience.
vi
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1
FUNDAMENTALS
OF ALGORITHMS
CHAPTER INTRODUCTION 1.1 Representing
In this chapter you will learn about:
algorithms
1.1 Representing algorithms
➤ Understand and explain the term algorithm
Computers are simply electronic machines that carry out
➤ Understand and explain the terms decomposition
instructions given by human programmers; although a
and abstraction
computer can solve many complex problems, it can only do
➤ Explain algorithms in terms of their inputs, outputs so if it is given instructions to tell it how to do so. Writing
and processing these instructions in a form that is suitable for a computer to
➤ Use a systematic approach to problem solving carry out can be a challenging task!
including pseudo-code, program code and flowcharts An algorithm is a step-by-step sequence of instructions
➤ Determine the purpose of simple algorithms using that are used to solve a problem or complete a task. Each
trace tables and visual inspection instruction in an algorithm must be precise enough to be
understood independently. An algorithm must also clearly
1.2 Efficiency of simple algorithms
show the order in which instructions are carried out and
➤ Understand that more than one algorithm can be
where decisions are made or sections repeated.
used to solve the same problem
➤ Compare the efficiency of algorithms Key point
1.3 Sorting and searching algorithms
A computer program is an implementation of an algorithm – an
➤ Understand and explain how linear search and
algorithm is not a computer program!
binary search algorithms work
➤ Understand and explain how merge sort and bubble
sort algorithms work
1
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1 Fundamentals of algorithms
Decomposition and abstraction
In order to define algorithms effectively, decomposition and abstraction are often used.
● Decomposition is breaking a problem down into smaller sub-problems that each
accomplish an identifiable task, which might itself be further subdivided.
● Abstraction is removing or hiding unnecessary details from a problem so that the important
details can be focused on or more easily understood.
For example, imagine a programmer wishes to create a system to sell T-shirts. This could be a
relatively large problem. Where would they start? By using decomposition and abstraction, the
programmer can begin to work out how to tackle the problem.
Decomposition Abstraction
How can the T-shirt sales system be split up? What can we focus on and what can we ignore?
It perhaps involves: Let’s consider the login and search functions:
● A login system for users ● The login system could focus on a
● A search function to find particular T-shirt customer’s email address and password but
● A system to allow users to buy a T-shirt. ignore everything else.
● A reordering system ● The search function could focus only on
certain T-shirt details (for example colour,
size, material, price, how many in stock).
A particularly powerful example of abstraction is Harry Beck’s well-known London
underground map. The map focuses on the connections between stations and how lines
intersect. It is a useful tool for anyone who wants to plan a journey in London. However, it
ignores details such as tunnels, distances between stations and which streets pass overhead.
These details are not important for underground travellers and would make the map more
confusing if included. To see Harry Beck's original design, go to the Transport for London
website, at https://tfl.gov.uk/corporate/about-tfl/culture-and-heritage/art-and-design/harry-
becks-tube-map.
Figure 1.1 A modern interpretation of a transport system map
2
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