{"title":"Comparison of Non-Homogeneous Poisson Process Software Reliability Models in Web Applications","authors":"Rabia Burcu Karaömer","doi":"10.5824/1309-1581.2016.3.001.X","DOIUrl":null,"url":null,"abstract":"Software reliability is an important quality factor that effects project success. By modelling software reliability, it can be estimated when and with how much effort a project can be deployed. Consequently, this can contribute to the resource and schedule planning of a project. Therefore, software reliability models (SRM) are frequently used for measuring the maturity of a software. A number of studies exist in the literature that compare SRMs in terms of their modelling performance. However, there is a need of evaluating these SRMs by taking into account the software project domain. This study aims to compare the performance of SRMs in the context of Web applications. In accordance to this purpose, six different software reliability models, namely Goel-Okumoto, Musa Exponential, Inflected S-shaped, Delayed S-shaped, Yamada and Pham Nordmann Zhang Imperfect Fault Detection (PNZ), are evaluated by using the defect records of four Web application projects developed by a Turkish software organization. 100%, 70% and 50% of the recorded data is used as input to the maximum likelihood parameter estimation (MLPE) method and the results of these three cases are investigated and commented separately in the research. The goodness of fit and the predictive validity of the models to the project data are tested by calculating Mean Square Error (MSE), Mean Magnitude Relative Error (MMRE), Percentage Relative Error Deviation (PRED) and Average Balanced Predicted Relative Error (A.BPRE) measures. For each NHPP model 48 separate cases which are combinations of the three defect inflow data cases (100%, 70% and 50%), four projects and four measures, are investigated and ranked. It is shown that the NHPP models can be applied to Web applications and Delayed S-shaped model displays the best results among the alternatives. However, it is understood that the Goel-Okumoto and Yamada models give identical results and that these two models converge to each other with respect to the project defect data that has been used. Combined, these two models obtain the highest ranking scores and it is concluded that these two models perform better than the other models with respect to Web based software.","PeriodicalId":244910,"journal":{"name":"AJIT‐e: Online Academic Journal of Information Technology","volume":"40 33","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AJIT‐e: Online Academic Journal of Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5824/1309-1581.2016.3.001.X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Software reliability is an important quality factor that effects project success. By modelling software reliability, it can be estimated when and with how much effort a project can be deployed. Consequently, this can contribute to the resource and schedule planning of a project. Therefore, software reliability models (SRM) are frequently used for measuring the maturity of a software. A number of studies exist in the literature that compare SRMs in terms of their modelling performance. However, there is a need of evaluating these SRMs by taking into account the software project domain. This study aims to compare the performance of SRMs in the context of Web applications. In accordance to this purpose, six different software reliability models, namely Goel-Okumoto, Musa Exponential, Inflected S-shaped, Delayed S-shaped, Yamada and Pham Nordmann Zhang Imperfect Fault Detection (PNZ), are evaluated by using the defect records of four Web application projects developed by a Turkish software organization. 100%, 70% and 50% of the recorded data is used as input to the maximum likelihood parameter estimation (MLPE) method and the results of these three cases are investigated and commented separately in the research. The goodness of fit and the predictive validity of the models to the project data are tested by calculating Mean Square Error (MSE), Mean Magnitude Relative Error (MMRE), Percentage Relative Error Deviation (PRED) and Average Balanced Predicted Relative Error (A.BPRE) measures. For each NHPP model 48 separate cases which are combinations of the three defect inflow data cases (100%, 70% and 50%), four projects and four measures, are investigated and ranked. It is shown that the NHPP models can be applied to Web applications and Delayed S-shaped model displays the best results among the alternatives. However, it is understood that the Goel-Okumoto and Yamada models give identical results and that these two models converge to each other with respect to the project defect data that has been used. Combined, these two models obtain the highest ranking scores and it is concluded that these two models perform better than the other models with respect to Web based software.