Parvinder S. Sandhu and Satish Kumar Dhiman and Anmol Goyal
A Genetic Algorithm Based Classification Approach for Finding Fault Prone Classes
2882 - 2885
2009
3
12
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/14456
https://publications.waset.org/vol/36
World Academy of Science, Engineering and Technology
Faultproneness of a software module is the
probability that the module contains faults. A correlation exists
between the faultproneness of the software and the measurable
attributes of the code (i.e. the static metrics) and of the testing (i.e.
the dynamic metrics). Early detection of faultprone software
components enables verification experts to concentrate their time and
resources on the problem areas of the software system under
development. This paper introduces Genetic Algorithm based
software fault prediction models with ObjectOriented metrics. The
contribution of this paper is that it has used Metric values of JEdit
open source software for generation of the rules for the classification
of software modules in the categories of Faulty and non faulty
modules and thereafter empirically validation is performed. The
results shows that Genetic algorithm approach can be used for
finding the fault proneness in object oriented software components.
Open Science Index 36, 2009