IMPERFECT DEBUGGING MODEL WITH RANDOM FAULT REMOVAL EFFICIENCY FOR SOFTWARE RELIABILITY EVALUATION

Many software reliability models often assume the perfect debugging environment, however, this assumption is a controversial issue in software reliability modeling, i. e., the actual debugging environment is considered to be under the imperfect debugging one. On the other hand, the establishment of reasonable methods for deciding the fault removal efficiency (FRE), which represents the probability that a fault is corrected and removed from the software system perfectly when a debugging activity is performed, remains an open question. This paper discusses the imperfect debugging modeling for software reliability measurement considering the randomness of the FRE, i. e., the FRE is treated as a random-distributed variable. We use the nonhomogeneous Poisson process to describe the software failure-occurrence phenomenon. We rederive the mean value function representing the expected cumulative number of faults detected up to time t, and several software reliability assessment measures. Finally, we show several numerical examples of the model and investigate the impact of the randomness of the FRE on software reliability evaluation.