GTAC 2013: Empirical Investigation of Software Product Line Quality

http://g.co/gtac2013 Slides: http://goo.gl/pPQ1u Katerina Goseva-Popstojanova, West Virginia University Software product lines exhibit high degree of commonality among the systems in the product line and a well specified number of possible variations. Based on data extracted from two case studies - a medium size industrial product line and a large, evolving open source product line - we explored empirically if the systematic reuse improves the quality and supports successful prediction of potential future faults from previously experienced faults, source code metrics, and change metrics. Our research results confirmed, in a software product line setting, the findings of others that faults are more highly correlated to change metrics than to static code metrics. The quality assessment results showed that although older packages (including commonalities) continually changed, they retained low fault densities. Furthermore, the open source product line improved in quality as it evolved through releases. The prediction based on generalized linear regression models accurately ranked the packages according to their post-release faults using the models built on the previous release. The results also revealed that post-release fault predictions benefit from additional product line information.