Measuring and Evaluating Maintenance Process Using Reliability, Risk, and Test Metrics
IEEE Transactions on Software Engineering
Software quality control and prediction model for maintenance
Annals of Software Engineering
A Classification Scheme for Studies on Fault-Prone Components
PROFES '01 Proceedings of the Third International Conference on Product Focused Software Process Improvement
Investigation of the Risk to Software Reliability and Maintainability of Requirements Changes
ICSM '01 Proceedings of the IEEE International Conference on Software Maintenance (ICSM'01)
A Queue Theory-Based Approach to Staff Software Maintenance Centers
ICSM '01 Proceedings of the IEEE International Conference on Software Maintenance (ICSM'01)
Software Metrics Model For Integrating Quality Control And Prediction
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
Predicting Deviations in Software Quality by Using Relative Critical Value Deviation Metrics
ISSRE '99 Proceedings of the 10th International Symposium on Software Reliability Engineering
On the Repeatability of Metric Models and Metrics across Software Builds
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Modeling Fault-Prone Modules of Subsystems
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Assessing Staffing Needs for a Software Maintenance Project through Queuing Simulation
IEEE Transactions on Software Engineering
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This is an experience report on identifying fault-prone modules in a subsystem of the Joint Surveillance Target Attack Radar System, jstars, a large tactical military system. The project followed the spiral life cycle model. The iterations of the system were developed in fortran about one year apart. We developed a discriminant analysis model using software metrics from one iteration to predict whether or not each module in the next would be considered fault-prone. Tactical military software is required to have high reliability. Each software function is often considered mission-critical, and the lives of military personnel often depend on mission success. In our project, each iteration of a spiral life cycle development produced a system that was suitable for operational testing. A risk analysis based on operational testing guided development of the next iteration. Identifying fault-prone modules early in the development of an iteration can lead to better reliability. The results confirm previously published studies that discriminant analysis can be a useful tool in identification of fault-prone software modules. This study used consecutive iterations, first, to build, and then, to evaluate the model. This model validation approach is more realistic than earlier studies which split data from one project to simulate two iterations. Model results could be used to identify those modules that would probably benefit from extra reviews and testing, and thus, reduce the risk of unexpected problems with those modules.