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YOUR NOTES
IGCSE Computer Science CIE 

7. Algorithm design and problem-solving

CONTENTS
7.1 Development Life Cycle
Program Development Life Cycle - Analysis
Program Development Life Cycle - Design
Program Development Life Cycle - Coding
Program Development Life Cycle - Testing
7.2 Algorithms
Explaining Algorithms
7.3 Standard Methods
Standard Methods
7.4 Validation and Testing
Validation
Test Data
Trace Tables
7.5 Identifying Errors
Identifying Errors
Writing & Amending Algorithms

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7.2 Algorithms YOUR NOTES


Explaining Algorithms

Explaining Algorithms
Algorithms can be written using flowcharts, pseudocode or high-level programming
language code such as Python
The purpose of an algorithm is to achieve some goal. It isn’t always initially clear what the
goal may be. By following the algorithm instructions, the purpose can become clear

 Exam Tip
Comments in an algorithm or program usually describe why something has
been done or provide useful information to the reader. Each line of code should
otherwise be self-explanatory

The purpose of the algorithm below is to add ten user-entered numbers together and
output the total. The processes are:
initializing three variables (Count, Number, Total)
inputting a user number
adding to two variables (Total, Count)
repeating nine more times
outputting the final Total value
Count ← 1

Number ← 0

Total ← 0

REPEAT

INPUT Number

Total ← Total + Number

Count ← Count + 1

UNTIL Count > 10

OUTPUT Total

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YOUR NOTES
 Worked Example

The Pseudocode Algorithm shown has been written by a teacher to enter marks for
the students in her class and then to apply some simple processing.
Count ← 0

REPEAT

INPUT Score[Count]

IF Score[Count] >= 70

THEN

Grade[Count] ← "A"

ELSE

IF Score[Count] >= 60

THEN

Grade[Count] ← "B"

ELSE

IF Score[Count] >= 50

THEN

Grade[Count] ← "C"

ELSE

IF Score[Count] >= 40

THEN

Grade[Count] ← "D"

ELSE

IF Score[Count] >= 30

THEN

Grade[Count] ← "E"

ELSE

Grade[Count] ← "F"

ENDIF

ENDIF

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ENDIF YOUR NOTES

ENDIF 

ENDIF

Count ← Count + 1

UNTIL Count = 30

Describe what happens in this algorithm.

[3]
Any 3 of:
Inputted marks are stored in the array Score[] [1]
Marks are then checked against a range of boundaries [1]
A matching grade is assigned to each mark that has been input [1]
The grade is then stored in the array Grade[] [1]
At the same index as the inputted mark [1]
The algorithm finishes after 30 marks have been input [1]

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7.3 Standard Methods YOUR NOTES


Standard Methods

Linear Search
The linear search is a standard algorithm used to find elements in an unordered list. The list
is searched sequentially and systematically from the start to the end one element at a time,
comparing each element to the value being searched for
If the value is found the algorithm outputs where it was found in the list
If the value is not found it outputs a message stating it is not in the list
An example of using a linear search would be looking for a specific student name in a list or
searching for a supermarket item in a shopping list

OUTPUT “Enter a value to find”

INPUT Number

Found ← FALSE

Index ←1

REPEAT

IF Number = Mylist[Index]

THEN

Found ← TRUE

ELSE

Counter ← Counter + 1

ENDIF

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UNTIL Found =TRUE OR Counter > LENGTH(Mylist) YOUR NOTES



IF Found = TRUE

THEN

OUTPUT Number, “ found at position “, Counter

ELSE

OUTPUT Number, “ not found”

ENDIF

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Bubble Sort YOUR NOTES

Bubble sort sorts items into order, smallest to largest, by comparing pairs of elements and 
swapping them if they are out of order
The first element is compared to the second, the second to the third, the third to the fourth
and so on, until the second to last is compared to the last. Swaps occur if each comparison
is out of order. This overall process is called a pass
Once the end of the list has been reached, the value at the top of the list is now in order and
the sort resets back to the start of the list. The next largest value is then sorted to the top of
the list
More passes are completed until all elements are in the correct order
A final pass checks all elements and if no swaps are made then the sort is complete
An example of using a bubble sort would be sorting into alphabetical order an array of
names, or sorting an array of student marks from a test

Mylist ← [5, 9, 4, 2, 6, 7, 1, 2, 4, 3]

FirstElement ← 1

LastElement ← LENGTH(Mylist)

REPEAT

Swap ← FALSE

For Index ← FirstElement TO LastElement - 1

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IF Mylist[Index] > Mylist[Index + 1] YOUR NOTES

THEN 

Temp ← Mylist[Index]

Mylist[Index] ← Mylist[Index + 1]

Mylist[Index + 1] ← Temp

Swap ← TRUE

ENDIF

NEXT Index

LastElement ← LastElement - 1

UNTIL Swap = FALSE OR LastElement = 1

OUTPUT “Your sorted list is:”, Mylist

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Totalling & Counting YOUR NOTES

Totalling 
Totalling involves keeping a running total of values entered into the algorithm. An example
may be totalling a receipt for purchases made at a shop
The Total below starts at 0 and adds up the user inputted value for each item in the list. For
example, if the user has a receipt for four items: an apple (£0.50), a drink (£1), a sandwich
(£2) and a bar of chocolate (£1). The algorithm will total the cost for each item one at a time.
The output Total will be 4.50
Total ← 0

FOR Count ← 1 TO ReceiptLength

INPUT ItemValue

Total ← Total + itemValue

NEXT Count

OUTPUT Total

Counting
Counting works similarly to totalling except the count is incremented or decremented by a
fixed value, usually 1, each time it iterates. Counting keeps track of the number of times an
action has been performed. Many algorithms use counting, including the linear search and
binary search to track which element is currently being considered
The count is incremented and each pass number is output until fifty outputs have been
produced
Count ← 0

DO

OUTPUT “Pass number”, Count

Count ← Count + 1

UNTIL Count >= 50

The count is decremented from fifty until the count reaches zero. An output is produced for
each pass
Count ← 50

DO

OUTPUT “Pass number”, Count

Count ← Count - 1

UNTIL Count <= 0

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Maximum, Minimum & Average YOUR NOTES

Finding the largest and smallest values in a list is a frequently used method in algorithms. 
Examples could include the maximum and minimum student grades or scores in a game
Max ← Score[1]

Min ← Score[1]

FOR Count ← 2 TO ScoreSize

IF ScoreSize[Count] > Max

THEN

Max ← ScoreSize[Count]

ENDIF

IF ScoreSize[Count] < Min

THEN

Min ← ScoreSize[Count]

ENDIF

Next Count

In the above algorithm, the initial max and min are set to the first value in the list and the for
loop starts at the second element instead of the first as the first value is the benchmark to
compare all other items to
If no value is larger than the initial max, then Max doesn’t change. If no value is smaller than
the initial min, then Min doesn’t change
The algorithm loops over each element asking whether the current value is larger than Max
and whether it is smaller than Min. Max and Min adjust their values throughout the program
depending on these conditions
The program will eventually output the smallest and largest value in Min and Max
respectively
Average values (also known as the mean) involve totalling all the list values and then
dividing by the number of values in the list
Total ← 0

FOR Count ← 1 TO ScoreSize

Total ← Total + ScoreSize[Count]

NEXT Count

Average ← Total / ScoreSize

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7.5 Identifying Errors YOUR NOTES


Identifying Errors

Identifying Errors
Errors can be identified in algorithms using trace tables as well as scanning and debugging code
manually
Two types of errors are as follows:
Syntax error
Syntax refers to the grammar of language, that is, are the words in the right order
and is everything spelled correctly
Unlike programs written on computers, syntax errors in flowcharts and
pseudocode do not cause the algorithm to fail however they do make the code
more difficult to read and understand
Transcribing flowcharts and pseudocode to real programming code may cause
problems if it is difficult to read and understand said flowcharts and pseudocode
Logical error
Logical errors occur when the program finishes but produces the wrong output during
or after
Flowcharts and pseudocode, unlike real programs, do not crash when dry run,
however may still produce logic errors by producing incorrect output
Logical errors are the most difficult error to fix as developers must reconsider their
logic and processes. If they do not understand the problem they cannot produce an
accurate solution
Below is an algorithm that asks the user to enter their age to determine what rated movie
they could watch at the cinema
There are syntax and logical errors with this pseudocode
OUTPUT Age

INPUT “Enter an age”

IF Age > 18

THEN

OUTPUT “You can watch an 18 movie”

ELSE

IF Age > 15

THEN

OUTPUT “You can watch a 15 movie

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ELSE YOUR NOTES

IF Age > 12 

THEN

OUTPUT “You can watch a 12 movie”

ELSE

IF Age < 9

THEN

OUTPUT “You can watch a PG movie”

ELSE

OUTPUT “You can watch a U movie”

END IF

ENDIF

ENDIF

ENDIF

Syntax and logic: OUTPUT Age and INPUT “Enter an age” are both syntax and logical errors
Syntax: Age does not yet have a value so OUTPUT cannot display it while INPUT does
not have a variable to store the data as strings cannot store data
Logical: Both are the wrong way around. OUTPUT Age should be OUTPUT “Enter an
age” and INPUT “Enter an age” should be INPUT Age
Syntax: THEN is missing from the first IF statement
Syntax: A quote is missing from the OUTPUT “You can watch a 15 movie”
Logic: Age < 9 should be Age > 9 so that it follows the other IF statement logic
Syntax: ENDIF is missing from the first IF statement

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YOUR NOTES
 Worked Example

1. An algorithm has been written in pseudocode to input some numbers. It only
outputs any numbers that are greater than or equal to 100. The number 999 is
not output and stops the algorithm.
INPUT Number
WHILE Numbers <> 999 DO
IF Number > 100
THEN
OUTPUT Number
ENDIF
ENDWHILE
OUTPUT Number
(a) Identify the four errors in the pseudocode and suggest corrections.
[4]
Numbers should be Number [1]
IF Number > 100 should be IF Number >= 100 [1]
INPUT Number is missing from inside the loop, insert INPUT Number after the ENDIF
statement [1]
The final OUTPUT Number is not needed, remove it [1]
(b) Write a pseudocode statement to change the corrected algorithm to output all
numbers between 100 and 200 inclusive. You do not need to rewrite the whole
algorithm
[2]
[1] for both ends of the range and correct inequality symbols
[1] for the AND

IF Number >= 100 AND Number <= 200

THEN
OUTPUT Number
ENDIF

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7.1 Development Life Cycle YOUR NOTES


Program Development Life Cycle - Analysis

Abstraction
This is the act of removing unimportant details of the problem to focus on important elements.
An example of abstraction would be the London underground train route map; travellers do not
need to know the geographical layout of the routes, only that getting on at stop A will eventually
transport you to stop B

Figure 1: London Underground train route map

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YOUR NOTES


Figure 2: The geographical London underground train map

Requirements
Identification of the problem: Before tackling a problem, it needs to be clearly understood
by everyone working on it. The overall goal of the solution needs to be agreed as well as any
constraints such as limited resources or requiring a platform specific solution
Requirements: To create a solution, a requirements document is created to define the
problem and break it down into clear, manageable, understandable parts by using
abstraction and decomposition. A requirements document labels each requirement, gives
it a description as well as success criteria which state how we know when the requirement
has been achieved

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7.4 Validation and Testing YOUR NOTES


Validation

Validation
Validation and verification are used to ensure input data is correct, reasonable and
accurate
Validation generally is about making sure data follows a set of specified rules created by
the programmer. Verification is about double-checking input data to make sure it's what
the user intended to enter

Validation
Validation is the method of checking input data so that it is of an expected value and
therefore accepted by the system
Programmers create rules using code that automatically checks user input data to make
sure the data is reasonable. If it is not reasonable then the data is rejected, usually with a
message explaining why it was rejected and allowing the user to reenter the data
The different types of validation rules or checks are as follows:
Range checks
Length checks
Type checks
Presence checks
Format checks
Check digits
Each piece of data may require multiple different checks to be fully valid

Range check
Range checks make sure the input data is a value between a user-defined minimum and
maximum value, for example, a percentage being between 0 and 100 inclusive or a date in
April is between 1 and 30 inclusive
OUTPUT “Enter a number between 0 and 100”

REPEAT

INPUT Number

IF Number < 0 OR Number > 100

THEN

OUTPUT “Number is not between 0 and 100, please try again”

ENDIF

UNTIL Number >= 0 AND Number <= 100

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Length check YOUR NOTES

Length checks check either that the input data is of an exact number of characters or in a 
user specified number range of characters
A bank 4-digit PIN number may be an example of an exact number of characters. If it is not
4 digits in length it should be rejected
OUTPUT “Please enter your 4 digit bank PIN number”

REPEAT

INPUT Pin

IF LENGTH(Pin) <> 4

THEN

OUTPUT “Your pin number must be four characters in length, please try again”

ENDIF

UNTIL LENGTH(Pin) = 4

Passwords usually have a specified range, for example, eight to twenty characters in
length. If it does not fall within this range, it should be rejected
OUTPUT “Please enter a password between 8 and 20 characters”

REPEAT

INPUT Password

IF LENGTH(Password) < 8 OR LENGTH(Password) > 20

THEN

OUTPUT “Your password must be between 8 and 20 characters in length, please try again”

ENDIF

UNTIL LENGTH(Password) >= 8 AND LENGTH(Password) <= 20

Type checks
Type checks make sure the input data is of the correct data type. For example, someone's
age should be an integer (a whole number) whereas their name should be a string (a bunch
of characters)
OUTPUT “Enter an integer number”

REPEAT

INPUT Number

IF Number <> DIV(Number, 1)

THEN

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OUTPUT “Not a whole number, please try again” YOUR NOTES

ENDIF 

UNTIL Number = DIV(Number , 1)

Presence check
Presence checks make sure that input data has been entered and that the input box has
not been left empty
A login system requires presence checks as both a username and password are required
for authentication
OUTPUT “Enter your username”

REPEAT

INPUT Username

IF Username = “”

THEN

OUTPUT “No username entered, please try again”

ENDIF

UNTIL Username <> “”

Format check
Format checks make sure that input data is of a predefined pattern
Identification codes e.g. AP1234 and dates are examples of patterns
Format checks are done using pattern matching and string handling
The algorithm below checks a six digit identification number against the format “XX9999”
where X is an uppercase alphabetical letter and 9999 is a four digit number
The first two characters are checked against a list of approved characters. The first
character is compared one at a time to each valid character in the ValidChars array. If it finds
a match it stops looping and sets ValidChar to True. The second character is then
compared one at a time to each valid character in the ValidChars array. If it finds a match
then it also stops looping and sets ValidChar to True
Casting is used on the digits to turn the digit characters into numbers. Once the digits are
considered a proper integer they can be checked to see if they are in the appropriate range
of 0-9999
If any of these checks fail then an appropriate message is output
INPUT IDNumber

IF LENGTH(IDNumber) <> 6

THEN

OUTPUT “ID number must be 6 characters long”

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END IF YOUR NOTES

ValidChars ← “ABCDEFGHIJKLMNOPQRSTUVWXYZ” 

FirstChar ← SUBSTRING(IDNumber, 1, 1)

ValidChar ← False

Index ← 1

WHILE Index <= LENGTH(ValidChars) AND ValidChar = False DO

IF FirstChar = ValidChars[Index]

THEN

ValidChar ← True

ENDIF

Index ← Index + 1

ENDWHILE

IF ValidChar = False

THEN

OUTPUT “First character is not a valid uppercase alphabetical character”

ENDIF

SecondChar ← SUBSTRING(IDNumber, 2, 2)

ValidChar ← False

Index ← 1

WHILE Index <= LENGTH(ValidChars) AND ValidChar = False DO

IF SecondChar = ValidChars[Index]

THEN

ValidChar ← True

ENDIF

Index ← Index + 1

ENDWHILE

IF ValidChar = False

THEN

OUTPUT “Second character is not a valid uppercase alphabetical character”

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ENDIF YOUR NOTES

Digits ← INT(SUBSTRING(IDNumber, 3, 6)) 

IF Digits < 0000 OR Digits > 9999

THEN

OUTPUT “Digits invalid. Enter four valid digits in the range 0000-9999”

ENDIF

Check digits
Check digits are numerical values that are the final digit of a larger code such as a barcode
or an International Standard Book Number (ISBN). They are calculated by applying an
algorithm to the code and are then attached to the overall code
Check digits help to identify errors in data entry such as mistyping, miscanning or
misspeaking
Such errors include missing or additional digits, swapped digits, mispronunciation of
digits or simply an incorrect digit
Barcode ← “9780201379624”

Total ← 0

FOR Index = 1 to LENGTH(Barcode) - 1

IF Index MOD 2 = 0

THEN

Total ← Total + CAST_TO_INT(Barcode[Index])*3

ELSE

Total ← Total + CAST_TO_INT(Barcode[Index])*1

ENDIF

NEXT Index

CheckDigit ← 10 - Total MOD 10

IF CheckDigit = Barcode[LENGTH(Barcode)]

THEN

OUTPUT “Valid check digit”

ELSE

OUTPUT “Invalid check digit”

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ENDIF YOUR NOTES



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Verification YOUR NOTES

Verification is the act of checking data is accurate when entered into a system 
Mistakes such as creating a new account and entering a password incorrectly mean being
locked out of the account immediately
Verification methods include: double entry checking and visual checks

Double entry checking

Double entry checking involves entering the data twice in separate input boxes and then
comparing the data to ensure they both match. If they do not, an error message is shown
REPEAT

OUTPUT “Enter your password”

INPUT Password

OUTPUT “Please confirm your password”

INPUT ConfirmPassword

IF Password <> ConfirmPassword

THEN

OUTPUT “Passwords do not match, please try again”

ENDIF

UNTIL Password = ConfirmPassword

Visual check
Visual checks involve the user visually checking the data on the screen. A popup or
message then asks if the data is correct before proceeding. If it isn’t the user then enters
the data again
REPEAT

OUTPUT “Enter your name”

INPUT Name

OUTPUT “Your name is: “, Name, “. Is this correct? (y/n)”

INPUT Answer

UNTIL Answer = “y”

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YOUR NOTES
 Worked Example

Describe the purpose of validation and verification checks during data entry.
Include an example for each.
[4]
Validation check
[1] for description:
To test if the data entered is possible / reasonable / sensible
A range check tests that data entered fits within specified values
[1] for example:
Range / length / type / presence / format
Verification check
[1] for description:
To test if the data input is the same as the data that was intended to be input
A double entry check expects each item of data to be entered twice and
compares both entries to check they are the same
[1] for example:
Visual / double entry

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7.1 Development Life Cycle YOUR NOTES


Program Development Life Cycle - Design

Decomposition
This is the act of breaking down a large problem into smaller, clear, manageable and
understandable sub-parts. Sub-parts can be divided until they are easily solvable and
cannot be broken down any further. An example of decomposition could be getting ready
in the morning to go to school
Step 1: Wake up
Step 2: Get breakfast
Step 3: Brush teeth
Step 4: Put clothes on
Step 5: Make sure the bag and school supplies are ready
Step 6: Find transport to school e.g. walk, bus, car, bike, etc

These steps could be further subdivided, for example, “Step 2: Get breakfast” would entail:
Step 2.1 Get a bowl
Step 2.2 Get cereal
Step 2.3 Get milk
Step 2.4 Get a spoon
Step 2.5 Put cereal in a bowl
And so on…

Once the requirements document has been created, developers need to design the
structure and algorithms to solve the problem:
Structure charts are created to show the breakdown of tasks in a hierarchy
Flowcharts may be created to visually show how tasks should be carried out
Pseudocode is created, sometimes from flowcharts, to allow programmers to easily
translate task instructions into programming code

The design of a solution identifies what tasks need completing, how to complete the tasks
and how each task works together with other tasks

A computer system includes several components that work together: software, hardware,
data, networking and people
Systems can be broken down into sub-systems that can be further broken down into more
sub-systems, until each sub-system has a single purpose. This decomposition is known as
top-down design

Decomposing a system
To create an overall system and solve a problem, it must first be broken down into
subsystems that are easier to solve and create. The act of breaking down the problem is
known as stepwise refinement

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Decomposing the problem this way creates smaller, more manageable and more easily YOUR NOTES
understandable sub-parts 
Each sub-system can be assigned to a developer or group of developers who create
subroutines from these sub-systems. Each sub-system can then be created at the same
time, reducing development and testing time, especially on large projects
Decomposing the system using stepwise refinement requires developers to think about
four key areas:
Inputs: data entered into the system
Processes: subroutines and algorithms that turn inputs and stored data into outputs
Outputs: data that is produced by the system, such as information on a screen or
printed information
Storage: data that is stored on a physical device, such as on a hard drive
To solve a problem all aspects must be thoroughly understood by the developers
There are many methods used to design and construct solutions. Three such methods are
illustrated below:

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Structure Diagrams YOUR NOTES

Structure diagrams show hierarchical top-down design in a visual form. Each problem is 
divided into sub-problems and each sub-problem divided into further sub-problems. At
each level the problem is broken down into more detailed tasks that can be implemented
using a single subroutine

Figure 1: A structure diagram

Figure 2: A structure diagram for a mobile application

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YOUR NOTES
 Worked Example

A satellite navigation system is an example of a computer system that is made up
of subsystems. Part of a satellite navigation system: allows the user to enter details
for a new destination or select a previously saved destination and displays
directions in the form of a visual map or as a list. Draw a structure diagram for this
part of the satellite navigation system.
[4]
[1] for a hierarchical structure
[1] for suitable names for the sub-systems
[1] for identifiable inputs
[1] for identifiable outputs

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Flowcharts YOUR NOTES

Flowcharts show how algorithms can be represented visually in a diagrammatic format 
Each flowchart has a start and an end with arrows showing the order each task or
instruction needs to be carried out in
Flowcharts are made of several symbols:
Terminator symbols: Also known as Begin/End symbols. These indicate where a
flowchart starts and stops
Process symbols: These show simple actions being performed such as assigning
values or performing arithmetic operations on values
Processes can also represent other flowcharts or summarised actions. For
example, searching or sorting a list is a complex process which would require its
own flowchart. A process symbol could be used to represent sorting or searching
in a separate flowchart. This is represented by a process with an additional bar on
either side of the symbol
Input/Output symbols: These show the input of data and output of data
Decision symbols: These symbols are used to decide whether to take one of two
routes by answering a true/false or yes/no question. They can be used for selection
and iteration
Flow lines: Flow lines use arrows to show the direction of flow and what task to perform
next. Usually these are top to bottom and left to right

Figure 3: Flowchart symbols: terminator, input/output, process, decision (left to right)

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YOUR NOTES


Figure 4: Flowchart for finding the largest of ten numbers

Pseudocode
Pseudocode is a programming-like language that does not have syntax. It can be
considered “fake” code.
It uses english words and phrases to represent instructions and is very similar to
programming code but does not and cannot run on any computer
The purpose of pseudocode is to allow developers to understand how to create a program
regardless of the programming language used to implement the solution
While pseudocode has no specific syntax, it is important to stick to a consistent style. This
will make it easier and quicker for programmers to read and create programs from the
pseudocode
Examples of a consistent style can include:
Keywords are written in capital letters e.g. INPUT, OUTPUT, IF, THEN, ELSE
Variable and subroutine names start with capital letters e.g. Age, Name, Date,
CalculateArea, Sortlist
Indentation can be used for iteration and selection

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7.4 Validation and Testing YOUR NOTES


Test Data

Test Data
Suggesting and applying suitable test data
Before a system is used, each sub-system must be tested to ensure it works correctly and
interacts correctly with other sub-systems
Programs are tested by running them on a computing device while pseudocode and
flowcharts must be dry run manually. Both require suitably chosen and different sets of test
data. The outputs are then compared to the expected output to check if the algorithm
works as intended
Test data comes in several generic types:
Normal
Normal test data is data that a system would be expected to handle on a day-to-
day basis, be accepted by the algorithm and produce expected results
Examples could include entering people's names and addresses, phone
numbers, student grades as a percentage, etc
Student percentage grades could involve test data such as: 34, 41, 56, 78, 12, 92
Abnormal
Also known as erroneous data, abnormal data is data that is expected to fail and
should be rejected by the system. This is used to prove that the system works
correctly by rejecting incorrect data
Examples of abnormal data would be entering numbers instead of someone's
name, or entering text instead of numbers
Student percentage grades abnormal data could involve test data such as: abc,
7&n, Harry, £300, <!%, etc
Extreme
Extreme test data is the maximum and minimum values of normal data that are
accepted by the system
Examples could include percentages (0 and 100), days in April (1 and 30) or the
number of characters in a passwords range
For an 8-20 character range password, a password of 8 characters and
another of 20 characters would be tested
Boundary
Boundary test data is similar to extreme data except that the values on either side
of the maximum and minimum values are tested
The largest and smallest acceptable value is tested as well as the largest and
smallest unacceptable value
For example, a percentage boundary test would be 0 and -1 (for 0) and 100 and
101 (for 100). For the days in April, 1 and 0 (for day 1) and 30 and 31 (for day 30)
would be tested. For an 8-20 length password, an 8 and 7 character password
would be tested as well as a 20 and 21 character password

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YOUR NOTES
 Worked Example

A programmer has written an algorithm to check that prices are less than $10.00
These values are used as test data: 10.00 9.99 ten
State why each value was chosen as test data.
[3]
10.00 is boundary or abnormal data and should be rejected as it is out of range [1]
9.99 is boundary, extreme and normal data and should be accepted as it is within
the normal range [1]
Ten is abnormal data and should be rejected as it is the wrong value type [1]

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7.5 Identifying Errors YOUR NOTES


Writing & Amending Algorithms

Writing & Amending Algorithms

To create algorithms for a given problem several stages must be followed:
1. The problem must be sufficiently analysed and understood. The requirements and purpose
of the algorithm must be clearly stated
2. The problem must be sufficiently decomposed into sub-problems. A complex problem
may require many sub-problems with each sub-problem requiring their sub-problems and
algorithms. When determining an algorithm for a sub-problem developers need to consider
inputs, outputs, processes and long term data storage (if necessary)
3. Consideration must be given to how data is going to be gathered, stored and processed as
well as how output is going to be displayed to the user
For example, will data be entered via input boxes or file upload/opening? Is data to be
stored in a file? What overall processes will be performed on the data? Will the data be
displayed on a form, a web page or output into a file?
4. The structure of the problem and subproblems should be illustrated by creating a structure
diagram which details the breakdown and hierarchy of sub-problems
5. Once each sub-problem is specified, an algorithm can be created using flowcharts or
pseudocode. The algorithm should be clear, easy to read and as simple as possible
Meaningful variable names help readers understand what data is being stored and
their purpose
Mathematical symbols such as “=” or “<=” are quicker and simpler to read than “equal
to “ or “less than or equal to”. “Percentage < 0 OR Percentage > 100” is clearer than
“Percentage under zero or Percentage over one-hundred”. Be concise
6. Sets of predetermined test data should be dry run on the algorithm, including normal,
abnormal, extreme and boundary data. The results should be displayed in a trace table, with
clear outputs to allow errors to be detected
7. Encountered errors should be fixed and the algorithm retested to make sure it functions as
intended

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Exam Tip YOUR NOTES

 Writing algorithms in an exam can be challenging and time consuming. It's

important to allocate your time carefully to not spend too little or too long
writing an algorithm
You will likely make mistakes and rewrite your algorithm a few times. Use scrap
paper or the back of your exam paper if possible to sketch out your ideas before
committing to your answer. This will make your answer clearer, neater and easier
to read, follow and understand
You may wish to chunk your algorithm into parts initially, for example, “This part
will enter the grades”, “this part will calculate the total”, and “This part will
allocate grades”. You can then put the whole algorithm together in order later
Make a plan before you start answering the question and writing your algorithm.
A plan can be simple but allows you to order your thoughts, for example:
Part 1: Declare and initialise variables
Part 2: Allocate marks for each subject
Part 3: Allocate grades for each student's subject
Part 4: Include a loop
Part 5: Output all necessary data
Pseudocode does not have a syntax, therefore you can write an algorithm in
any way which is easily understandable. Caution is advised to stick to iGCSE
specification standards to ensure your answer is consistent and easy for
examiners to follow
Be sure to use variable names and data provided in the question as given.
Failure to do so will lose you marks
Remember to comment on your code. It helps both you and the examiner
understand your answer and also awards marks in the mark scheme!

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7.1 Development Life Cycle YOUR NOTES


Program Development Life Cycle - Coding

Writing Code
Developers begin programming modules in a suitable programming language that works
together to provide an overall solution to the problem
As each developer programs, they perform iterative testing. Iterative testing is where each
module is tested and debugged thoroughly to make sure it interacts correctly with other
modules and accepts data without crashing or causing any errors. Developers may need to
retest modules as new modules are created and changed to make sure they continue to
interact correctly and do not cause errors

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7.4 Validation and Testing YOUR NOTES


Trace Tables

Trace Tables
Trace tables are used to follow algorithms and make sure they perform the required task
correctly. Test data is usually used in conjunction with a trace table to ensure the
correctness of the algorithm. Manually tracing an algorithm with test data in this way is
known as a dry run
Trace tables can be used with flowcharts or pseudocode or even real code if necessary
Trace tables can also be used to discover the purpose of an algorithm by showing output
data and intermediary steps
Trace tables record the state of the algorithm at each step or iteration. The state includes all
variables that impact the algorithms output as well as the output itself
A trace table is composed of columns where each variable and the output is a column
Whenever a value changes or an output is produced the relevant column and row is
updated to reflect the change

Trace Table Walkthrough

Below is a flowchart to determine the highest number of ten user entered numbers
The algorithm prompts the user to enter the first number which automatically becomes the
highest number entered
The user is then prompted to enter nine more numbers. If a new number is higher than an
older number then it is replaced
Once all ten numbers are entered, the algorithm outputs which number was the highest
Example test data to be used is: 4, 3, 7, 1, 8, 3, 6, 9, 12, 10

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YOUR NOTES


Figure 1: A flowchart to determine the highest of ten user entered numbers

Trace table for Figure 1: Highest number

Count Highest Number Output
1 Enter ten numbers
4 Enter your first number
2 3 Enter your next number
3 7 7
4 1
5 8 8
6 3
7 6

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8 9 9 YOUR NOTES
9 12 12 

10 10 12 is your highest number

 Exam Tip
When asked to identify the purpose of an algorithm in the exam, the variables
listed will often be a single letter rather than a meaningful identifier

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YOUR NOTES
 Worked Example

The flowchart represents an algorithm. The algorithm will terminate if –1 is entered.

Complete the trace table for the input data: 50, 75, 99, 28, 82, 150, –1, 672, 80
[4]
Value Diff1 Diff2 Output

[1] for each correct column

Value Diff1 Diff2 Output
50 50 0 Accept: Extreme
75 25 25 Accept: Normal
99 1 49 Accept: Normal
28 Reject: Abnormal
82 18 32 Accept: Normal
150 Reject: Abnormal
-1

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7.1 Development Life Cycle YOUR NOTES


Program Development Life Cycle - Testing

Testing
Once the overall program or set of programs is created, they are run many times using
varying sets of test data. This ensures the program or programs work as intended as
outlined in the initial requirements specification and design and rejects any invalid data that
is input
Examples of test data include alphanumeric sequences to test password validation
routines. Such validation routines could be:
A password must be between 8-20 characters
Test data would be passwords of less than 8 characters or greater than 20
characters
A password must include only alphanumeric characters
Test data would be passwords including non-alphanumeric symbols such as @, ?,
#, !, $ or %, etc

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