Predicting the types and locations of faults introduced during an imperfect repair process and their impact on reliability

Imperfect debugging of software development faults (called primary faults) will lead to the creation of new software faults denoted secondary faults. Secondary faults are typically fewer in numbers than the initial primary faults and are introduced late in the testing phase. As such it is unlikely that they will be observed during testing and their failure characteristics are unlikely to be assessed accurately. This is an issue since they may possibly display different propagation characteristics than the primary faults that led to their creation. In particular their location will be distributed non-uniformly around the fault being fixed. This paper proposes a methodology to assess the impact of secondary faults on reliability-based on predicting their possible types and locations. The methodology combines a fault taxonomy, code mutation and Bayesian statistics. The methodology is applied to portions of the application software code of a nuclear reactor protection system. This paper concludes with a discussion on the integration of the results within existing Software Reliability Growth Models.