Detection of fault-prone software modules during a spiral life cycle

The article 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 earlier reviews and testing, and thus, reduce the risk of unexpected problems with those modules.