{"title":"Robust Wavelet Shrinkage Estimation without Data Transform for Software Reliability Assessment","authors":"Xiao Xiao, T. Dohi","doi":"10.1109/SERE.2012.34","DOIUrl":null,"url":null,"abstract":"Since software failure occurrence process is well-modeled by a non-homogeneous Poisson process, it is of great interest to estimate accurately the software intensity function from observed software-fault count data. In the existing work the same authors introduced the wavelet-based techniques for this problem and found that the Haar wavelet transform provided a very powerful performance in estimating software intensity function. In this paper, we also study the Haar-wavelet-transform-based approach, but without using approximate transformations. In numerical study with real software-fault count data, we compare the proposed robust estimation with the existing wavelet-based estimation as well as the conventional maximum likelihood estimation and least squares estimation methods.","PeriodicalId":191716,"journal":{"name":"2012 IEEE Sixth International Conference on Software Security and Reliability","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Sixth International Conference on Software Security and Reliability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SERE.2012.34","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
Since software failure occurrence process is well-modeled by a non-homogeneous Poisson process, it is of great interest to estimate accurately the software intensity function from observed software-fault count data. In the existing work the same authors introduced the wavelet-based techniques for this problem and found that the Haar wavelet transform provided a very powerful performance in estimating software intensity function. In this paper, we also study the Haar-wavelet-transform-based approach, but without using approximate transformations. In numerical study with real software-fault count data, we compare the proposed robust estimation with the existing wavelet-based estimation as well as the conventional maximum likelihood estimation and least squares estimation methods.