Title :
Studying the Impact of Social Structures on Software Quality
Author :
Bettenburg, Nicolas ; Hassan, Ahmed E.
Author_Institution :
Software Anal. & Intell. Lab. (SAIL), Queen´´s Univ., Kingston, ON, Canada
fDate :
June 30 2010-July 2 2010
Abstract :
Correcting software defects accounts for a significant amount of resources such as time, money and personnel. To be able to focus testing efforts where needed the most, researchers have studied statistical models to predict in which parts of a software future defects are likely to occur. By studying the mathematical relations between predictor variables used in these models, researchers can form an increased understanding of the important connections between development activities and software quality. Predictor variables used in past top-performing models are largely based on file-oriented measures, such as source code and churn metrics. However, source code is the end product of numerous interlaced and collaborative activities carried out by developers. Traces of such activities can be found in the repositories used to manage development efforts. In this paper, we investigate statistical models, to study the impact of social structures between developers and end-users on software quality. These models use predictor variables based on social information mined from the issue tracking and version control repositories of a large open-source software project. The results of our case study are promising and indicate that statistical models based on social information have a similar degree of explanatory power as traditional models. Furthermore, our findings suggest that social information does not substitute, but rather augments traditional product and process-based metrics used in defect prediction models.
Keywords :
data mining; software metrics; software quality; statistical analysis; churn metrics; explanatory power degree; predictor variables; social information mining; social structures impact; software future defects; software quality; source code; statistical models; Collaborative software; Intelligent structures; Mathematical model; Open source software; Power system modeling; Predictive models; Software debugging; Software engineering; Software measurement; Software quality; Human Factors; Metrics/Measurement; Software Evolution; Software Quality Assurance;
Conference_Titel :
Program Comprehension (ICPC), 2010 IEEE 18th International Conference on
Conference_Location :
Braga, Minho
Print_ISBN :
978-1-4244-7604-6
Electronic_ISBN :
1092-8138
DOI :
10.1109/ICPC.2010.46