Bugs are inevitable in any software development life cycle. Most bugs are detected and removed in the testing phase. In software, we can classify bugs into two categories: (1) bugs of different severity (2) bugs of different complexity. Prior knowledge of bug distribution of different complexity in software can help project managers in allocating testing resources and tools. Various researchers...

Several studies have been undertaken in recent years to investigate the software failure phenomenon, with the objective of developing analytical models for quantitative assessment of software performance. Most of these studies assume that the times between software failures follow an exponential distribution with a failure rate that depends on the number of errors in the system (see, for exampl...

With the growing size and complexity of software applications, research in the area of component software reliability analysis has gained prominence. To ensure analytical tractability, traditional approaches usually ignore fault correction process of component software based on simplifying assumptions of instantaneous and perfect debugging. As a result, the estimates obtained from these models ...

Software Reliability is defined as the probability of failure free operation for a specified period of time in a specified environment. If the size of the software system is large, and the number of the faults which are detected and removed through debugging activities becomes sufficiently small compared with the initial faults content at the beginning of the testing phase, in such a situation,...

Considering testing effort and imperfect debugging in reliability modeling process may further improve the fitting and prediction results of software reliability growth models (SRGMs). For describing the S-shaped varying trend of the testing-effort increasing rate more accurately, this paper first proposes a inflected S-shaped testing effort function (IS-TEF). Then this new TEF is incorporated ...

In this paper, we propose a software reliability model that considers not only error generation but also fault removal efficiency combined with testing coverage information based on a nonhomogeneous Poisson process (NHPP). During the past four decades, many software reliability growth models (SRGMs) based on NHPP have been proposed to estimate the software reliability measures, most of which ha...