A general modeling and analysis framework for software fault detection and correction process. (7th March 2016)

• Record Type: Journal Article
• Authors: Liu, Yu; Li, Duo; Wang, Lujia; Hu, Qingpei
• Is Part Of: Software testing, verification & reliability. Volume 26:Number 5(2016)
• Page Start: 351
• Page End: 365
• Publication Date: 2016-03-07
• Subjects: fault detection process -- fault correction process -- software reliability -- weighted least‐square estimation; Computer software -- Testing -- Periodicals; Computer software -- Verification -- Periodicals; Computer software -- Reliability -- Periodicals; 005.14
• DOI: 10.1002/stvr.1600
• Languages: English
• ISSNs: 0960-0833

Abstract

Summary: Software reliability growth modeling plays an important role in software reliability evaluation. To incorporate more information and provide more accurate analysis, modeling software fault detection and correction processes has attracted widespread research attention recently. In modeling software correction processes, the assumption of fault correction time is relaxed from constant delay to random delay. However, stochastic distribution of fault correction time brings more difficulties in modeling and corresponding parameter estimation. In this paper, a framework of software reliability models containing both information from software fault detection process and correction process is studied. Different from previous extensions on software reliability growth modeling, the proposed approach is based on Markov model other than a nonhomogeneous Poisson process model. Also, parameter estimation is carried out with weighted least‐square estimation method, which emphasizes the influence of later data on the prediction. Two data sets from practical software development projects are applied with the proposed framework, which shows satisfactory performance with the results. Copyright © 2016 John Wiley & Sons, Ltd. Abstract : In this paper, a framework of software reliability models containing both information from software fault detection process and correction process is studied. The proposed approach is based on Markov model other than a nonhomogeneous Poisson process model. Also, parameter estimation is carried out with weighted least‐square estimation method, which emphasizes the influence of later data on the prediction. Two data sets from practical software development projects are applied with the proposed framework, which shows satisfactory performance with the results.