Abstract
Over the past 30 years, many software reliability growth models (SRGMs) have been proposed for estimation of reliability growth of products during software development processes. In fact, effective debugging will not be easy because the fault may not be immediately obvious. Engineers need some time to read and analyze the software failure data. Thus the time delayed by the fault detection and correction processes should not be negligible. Besides, from our studies, software debugging process is very similar to a queuing system: if test engineers or programmers found errors, they have to isolate the bugs and determine the factors which produce the bugs. Thus the time delayed by the fault detection and correction processes should not be negligible. In this thesis, we will show how to incorporate the concept of queuing theory into software reliability modeling. Based on the concepts, we derive some new software reliability models considering various software debugging processes. Numerical examples are presented and the evaluation results show that the proposed framework to incorporate both fault detection and removal processes for SRGM has a fairly accurate prediction capability. Besides SRGMs, software process simulation is beginning to be used in the software reliability. Thus, we develop simulation procedures to analyze various debugging scenarios. According to the results of simulation procedures, it is found that the results are very close to the proposed models and they also indicate the simulation procedures have good performance.