期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2013
卷号：4
期号：2
页码：438-441
语种：English
出版社：Ayushmaan Technologies
摘要：In this paper, we have developed software analyzers tool for deriving several software reliability growth models based on Enhanced nonhomogeneous Poisson process (ENHPP) in the presence of imperfect debugging and error generation. The offered models are initially formulated for the case when there is no differentiation between failure observation and fault removal testing processes, and then continued for the case when there is a clear differentiation between failure observation and fault removal testing processes. Many software reliability growth models (SRGM) have been developed to describe software failures as a random process, and can be used to classify development status during testing. With software reliability growth, software engineers can easily measure (or forecast) the software reliability (or quality), and design software reliability growth charts. It is not easy to select the best tool for improving software quality. There are few SRGM in the literature of software engineering that differentiates between failure observation and fault removal processes. In real software development background, the number of failures checked need not be the same as the number of faults removed. Due to the elaboration of software systems, and an defective understanding of software, the testing team may not be able to discard the fault perfectly on observation of a failure, and the authentic fault may remain, resulting in a phenomenon known as defective debugging, or get replaced by another fault causing error generation. In the case of defective debugging, the error content of the software remains the same; while in the case of error generation, the error content increases as the testing progresses. Replacement of observed faults may result in the introduction of new faults.
关键词：Software Reliability Growth Models (SRGM);ENHPP (Enhanced Non Homogeneous Poisson Process);SDLC(Software Development Life Cycle);FDR (Fault Detection Rate).
