Using Process Enactment Data Analysis to Support Orthogonal Defect Classification for Software Process Improvement

Defects occur in many software development projects. It is important to extract semantic information from defects to investigate their root causes and improve the process. In this study, enactment data of a software development process in which defects originated was used to support Orthogonal Defect Classification (ODC). In a sample project of a CMMI ML3 organization ODC was applied to the defects and the utilization of the process enactment data was found to be effective and efficient in providing information about the root causes of the defects and deriving improvement actions. The defect attributes were analyzed and compared before and after applying suggested improvement actions. The comparison between the initial and the improved defect trigger and origin distributions showed that there was a positive change in the software development process of the project.