The design of a software fault prone application using evolutionary algorithm

Most of the current project management software's are utilizing resources on developing areas in software projects. This is considerably essential in view of the meaningful impact towards time and cost-effective development. One of the major areas is the fault proneness prediction, which is use...

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Bibliographic Details
Published in:2011 IEEE Conference on Open Systems, ICOS 2011
Main Author: Rosli M.M.; Teo N.H.I.; Yusop N.S.M.; Mohammad N.S.
Format: Conference paper
Language:English
Published: IEEE Computer Society 2011
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-83155185458&doi=10.1109%2fICOS.2011.6079246&partnerID=40&md5=263f0ff20b1136561f5f1e6eff070af1
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Summary:Most of the current project management software's are utilizing resources on developing areas in software projects. This is considerably essential in view of the meaningful impact towards time and cost-effective development. One of the major areas is the fault proneness prediction, which is used to find out the impact areas by using several approaches, techniques and applications. Software fault proneness application is an application based on computer aided approach to predict the probability that the software contains faults. The application will uses object oriented metrics and count metrics values from open source software as input values to the genetic algorithm for generation of the rules to classify the software modules in the categories of Faulty and Non Faulty modules. At the end of the process, the result will be visualized using genetic algorithm applet, bar and pie chart. This paper will discussed the detail design of software fault proneness application by using genetic algorithm based on the object oriented approach and will be presented using the Unified Modeling Language (UML). The aim of the proposed design is to develop an automated tool for software development group to discover the most likely software modules to be high problematic in the future. © 2011 IEEE.
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DOI:10.1109/ICOS.2011.6079246