Bug Prediction Metrics Based Decision Support for Preventive Software Maintenance

There exist a number of large legacy systems that still undergo continuous maintenance and enhancement. Due to the sheer size and complexity of the software systems and limited resources, managers are confronted with crucial decisions regarding allocation and training of new engineers, intelligent allocation of testing personnel, assessment of release readiness of the software and so on. While the area of bug prediction by mining software repositories holds promise, and is a worthwhile endeavor, the current state of the art techniques are not accurate enough in predicting bugs and hence are of limited usefulness to managers. So instead of predicting files as buggy or not we take a different viewpoint and focus on providing decision support for managers. In this paper we present a set of metrics to guide the managers in taking these decisions. These metrics are evaluated using 4 open source systems and 2 proprietary systems.