Mutant Density: A Measure of Fault-Sensitive Complexity

04/25/2021
by   Ali Parsai, et al.
0

Software code complexity is a well-studied property to determine software component health. However, the existing code complexity metrics do not directly take into account the fault-proneness aspect of the code. We propose a metric called mutant density where we use mutation as a method to introduce artificial faults in code, and count the number of possible mutations per line. We show how this metric can be used to perform helpful analysis of real-life software projects.

READ FULL TEXT
research
04/08/2020

C++11/14 Mutation Operators Based on Common Fault Patterns

The C++11/14 standard offers a wealth of features aimed at helping progr...
research
03/21/2021

Fault Prediction based on Software Metrics and SonarQube Rules. Machine or Deep Learning?

Background. Developers spend more time fixing bugs and refactoring the c...
research
07/23/2018

Fault Localization for Declarative Models in Alloy

Fault localization is a popular research topic and many techniques have ...
research
02/23/2020

Deriving a Usage-Independent Software Quality Metric

Context:The extent of post-release use of software affects the number of...
research
10/01/2018

Doric: Foundations for Statistical Fault Localisation

To fix a software bug, you must first find it. As software grows in size...
research
11/24/2017

Interactive Complexity: Software Metrics from an Ecosystem Perspective

With even the most trivial of applications now being written on top of m...
research
03/01/2020

The cross cyclomatic complexity: a bi-dimensional measure for program complexity on graphs

Reduce and control complexity is an essential practice in software desig...

Please sign up or login with your details

Forgot password? Click here to reset