Assessment of Change Request Artifacts Impact towards Fault Proneness
Exploring the impact of change requests applied on a software maintenance project helps to forecasts the fault-proneness of the change request to be handled further, which is either a bug fix or a new feature request. In practice the major development community stores change requests and related data using bug tracking systems such as bugzilla. These data, together with the data stored in a versioning system, such as Concurrent Versioning Systems, are a valuable source of information to create descriptions and also can perform useful analyses. In this paper we propose a novel knowledge based approach to assess the impact of the change request by the Change Request artifacts derived in our earlier work. The proposed model can be labeled as Assessment of Change Request Impact towards Fault Proneness (CRAI2FP). The method CRAI2FP exploits information retrieval algorithms to identify the influenced part of the code, architecture, modules and structure against the devised change request. And further evaluates the change impact value of the Change Request Artifacts towards fault proneness. The proposed method is evaluated by applying on known open source projects concurrent versioning and Change request logs.
Keywords: Defect forecasting, product metrics, change request, artifacts, concurrent versioning system, fault proneness, SDLC, risk prediction
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ABOUT THE AUTHORS
M.Rudra Kumar
Associate Professor, Annamacharya Institute of Technology and Sciences, Rajampet AP, India
Dr.A.Ananda Rao
Professor,Director of IR&P,SCDE JNTU Anantapur AP, India
M.Rudra Kumar
Associate Professor, Annamacharya Institute of Technology and Sciences, Rajampet AP, India
Dr.A.Ananda Rao
Professor,Director of IR&P,SCDE JNTU Anantapur AP, India
