CS3003 Software Engineering
Threshold Coursework 2020
Word Count: 1980
,Contents
Section 1: Metrics ................................................................................................................................... 2
Section 2: Analysis and Discussion of results .......................................................................................... 3
Section 3: References.............................................................................................................................. 7
1
, Section 1: Metrics
When designing software, there are several factors and measures that are put in place to ensure
high quality and standards are met. This is due to the benefits of developing quality software such as
the contributions made towards maintainability. Producing quality software will reduce the costs of
maintenance as well as reduce the likelihood of errors occurring. The implications of poorly designed
software may result in the functionality of the software not working as intended, due to code smells
and overly complex code resulting in errors or bugs. Software metrics are used to measure whether
software has met the target of being of high quality. With software metrics, we are able to establish
guidelines to understand what needs to be done and how - as well as encouraging improvements to
achieve quality targets.
The metrics that will be used to evaluate the Ant system will firstly be calculating the lines of code
(LOC). This metric measures the lines of source code, which is used to estimate the size of the
project. This is important for estimations such as costs of the project; as the lines of code increases,
as does the cost. Using LOC is an easy measure to calculate the size of the project and based on the
result of the metric, resources can be allocated to clean and improve the code. The larger a code
base gets the more difficult to maintain and therefore more bug prone. (Sathanandam, A et. al 2017)
Using more than one means of measurement to evaluate the complexity is integral during the
analysis of this software. The metric weighted methods per class (WMC) measures the number of
methods in a class, and as the number of methods increase within a class, the level of reusability of
the class decreases. (Virtual Machinery - Sidebar 3 - WMC, CBO, RFC, LCOM, DIT, NOC - 'The
Chidamber and Kemerer Metrics', 2000) This metric is important as this measurement will provide
an insight to existing code smells within the software such as large classes and therefore solutions
can be put in place to resolve this and improve the quality of the software, overall reducing the
likelihood of errors.
The cyclomatic complexity is used to measure the complexity of a module through the calculation of
decisions or independent paths taken in the software. The average cyclomatic complexity (AVGCC) is
the average of this direct measure of the independent paths. This is important as the more decisions
made within a program, the more complex it becomes and therefore become more prone to bugs.
Additionally, the larger the AVGCC measurement, the more difficult testing becomes for the system.
Lastly, the fan-out metric will be used throughout the analysis of the Ant system. This is due to the
fan-out metric presenting the number of classes, that each class in the system calls. This is important
as it is a direct measure of the number of classes each class depends on. Therefore, numerically
showcasing the coupling and potential volume of errors being caused from any changes made within
these used classes - due to the dependencies. The larger the fan-out figure the bigger the impact on
the system, if any changes occur, and therefore the increased likelihood of bugs in the system.
2
Threshold Coursework 2020
Word Count: 1980
,Contents
Section 1: Metrics ................................................................................................................................... 2
Section 2: Analysis and Discussion of results .......................................................................................... 3
Section 3: References.............................................................................................................................. 7
1
, Section 1: Metrics
When designing software, there are several factors and measures that are put in place to ensure
high quality and standards are met. This is due to the benefits of developing quality software such as
the contributions made towards maintainability. Producing quality software will reduce the costs of
maintenance as well as reduce the likelihood of errors occurring. The implications of poorly designed
software may result in the functionality of the software not working as intended, due to code smells
and overly complex code resulting in errors or bugs. Software metrics are used to measure whether
software has met the target of being of high quality. With software metrics, we are able to establish
guidelines to understand what needs to be done and how - as well as encouraging improvements to
achieve quality targets.
The metrics that will be used to evaluate the Ant system will firstly be calculating the lines of code
(LOC). This metric measures the lines of source code, which is used to estimate the size of the
project. This is important for estimations such as costs of the project; as the lines of code increases,
as does the cost. Using LOC is an easy measure to calculate the size of the project and based on the
result of the metric, resources can be allocated to clean and improve the code. The larger a code
base gets the more difficult to maintain and therefore more bug prone. (Sathanandam, A et. al 2017)
Using more than one means of measurement to evaluate the complexity is integral during the
analysis of this software. The metric weighted methods per class (WMC) measures the number of
methods in a class, and as the number of methods increase within a class, the level of reusability of
the class decreases. (Virtual Machinery - Sidebar 3 - WMC, CBO, RFC, LCOM, DIT, NOC - 'The
Chidamber and Kemerer Metrics', 2000) This metric is important as this measurement will provide
an insight to existing code smells within the software such as large classes and therefore solutions
can be put in place to resolve this and improve the quality of the software, overall reducing the
likelihood of errors.
The cyclomatic complexity is used to measure the complexity of a module through the calculation of
decisions or independent paths taken in the software. The average cyclomatic complexity (AVGCC) is
the average of this direct measure of the independent paths. This is important as the more decisions
made within a program, the more complex it becomes and therefore become more prone to bugs.
Additionally, the larger the AVGCC measurement, the more difficult testing becomes for the system.
Lastly, the fan-out metric will be used throughout the analysis of the Ant system. This is due to the
fan-out metric presenting the number of classes, that each class in the system calls. This is important
as it is a direct measure of the number of classes each class depends on. Therefore, numerically
showcasing the coupling and potential volume of errors being caused from any changes made within
these used classes - due to the dependencies. The larger the fan-out figure the bigger the impact on
the system, if any changes occur, and therefore the increased likelihood of bugs in the system.
2
