부산대학교 도서관

Predicting Reliability of Software using SRGMs are a big challenge for Software Engineers. Software Reliability is a way to find the probability of software to operate in a given time limit and in a specified environment without causing any failure; hence it is reviewed as Quantifiable Metric. System faults can be the result of software or hardware errors. Software fault is comparatively more difficult to predict than hardware faults. Even the Reliability of a web application is also hard to determine due to its highly distributed nature. Predicting the reliability of application helps the Engineers to compute the software's release date/time and to manage various resources of software such as people, money, time etc. In this paper SRGM Models are considered namely Goel Okumoto Model (GO Model), Yamada S-shaped Model and Kapur & Garg Model (KG Model) to estimate and predict Software Reliability by detecting the cumulative number of faults in software application within specified time. Additional number of days are also calculated to remove them and release the software on time. By implementing the test cases of actual defects per day, Rate of Change or Test Case Efficiency can be measured.