Process measures for predicting software quality

Software reliability is essential for tactical military systems, such as the Joint Surveillance Target Attack Radar System (JSTARS). It is an embedded, real-time military application, which performs real-time detection, location, classification and tracking of moving and fixed objects on the ground. A software quality model can make timely predictions of reliability indicators. These enable one to improve software development processes by targeting reliability improvement techniques more effectively and efficiently. This paper presents a case study of a large subsystem of JSTARS to improve integration and testing. The dependent variable of a logistic regression model was the class of a module: either fault-prone or not. Measures of the process history of each module were the independent variables. The case study supports our hypothesis that the likelihood of discovering additional faults during integration and testing can be usefully modeled as a function of the module history prior to integration. This history is readily available by combining data from the project's configuration management system and problem-reporting system.