The International Arab Journal of Information Technology (IAJIT)


Discrete Time NHPP Models for Software Reliability Growth Phenomenon

 Nonhomogeneous poisson process based software reli ability growth models are generally classified into two groups. The first group contains models, which use the machine execution time or calendar time as a un it of fault detection/removal period. Such models are called co ntinuous time models. The second group contains mod els, which use the number of test occasions/cases asaunitoffaultd etectionperiod.Suchmodelsarecalleddiscreteti memodels,sincetheunit of software fault detection period is countable. A large number of models have been developed in the f irst group while there are fewer in the second group. Discrete time models  in software reliability are important and a little effort has been made in this direction. In this paper, we develop two discr ete time SRGMs using probability generating functio n for the software failure occurrence / fault detection phenomenon bas ed on a NHPP namely, basic and extended models. The  basic model exploitsthefaultdetection/removalrateduringth einitialandfinaltestcases.Whereas,theextendedmodelincorporatesfault generation and imperfect debugging with learning. A ctual software reliability data have been used to demonstrate the proposed models. The results are fairly encouraging  in terms of goodness-of-fit and predictive validity criteria due to applicabilityandflexibilityoftheproposedmodel sastheycancaptureawideclassofreliabilitygrowthcurvesrangingfrom purelyexponentialtohighlyS-shaped. 

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[18] Xie M., Software Reliability Modelling , World Scientific, New York, 1991. Omar Shatnawi received his PhD, in computer science and his MSc in operational research from University of delhi in 2004 and 1999, respectively. Currently, he is head of Department of Information Systems at al!Bayt University. His research interests are in software engineering, wit h an emphasis on improving software reliability and dependability.