Imperfect Debugging-Based Generalized Exponential Testing Effort Estimation for Software Fault Detection and Removal

In the current technological era, the reliability growth model depicts the failure in software that is employed for estimating the reliability of software. Conventional software reliability growth model (SRGMs) usually presume that faults in software are immediately corrected once a software fault is found and no new faults are introduced. This consideration can be impractical. However, introduction of several new faults is possible throughout debugging, which is called imperfect debugging. During such a process of debugging and introduction of new faults, consumption of testing effort also plays an important role. Hence, in this paper, two models are proposed that incorporate testing effort along with imperfect debugging during fault correction. Additionally, the combined testing effort is the addition of two efforts, specifically detection effort as well as correction effort. The formulated models are validated for real data set and contrasted with additional famous SRGMs. These inferences indicate that Model 2 performs best in terms of fitting and prediction capability.