Validation of a Methodology for Assessing Software Reliability

Lil, M.; Wei, Yuan; Desovski, D.; Nejad, Hamed S.; Ghose, S.; Čukić, Bojan; Smidts, Carol

doi:10.1109/issre.2004.47

Cited by 15 publications

(14 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The expected system failure rate has decreased from 0.0819 to 0.0604, an improvement of 26.25%. This result matches closely the measured reliability of our implementation [16]. Predictive performance can be explained by the error propagation, since there is a substantial probability (0.425 in Table 3) that an error in Driver component (C1) can affect the PACS component C2.…”

Section: The Sensitivity Analysis Assuming Failure Independencesupporting

confidence: 83%

“…More important for the subject of this paper, in a related project [16] we implemented PACS and empirically evaluated its reliability through extensive testing. To our dismay the observed system reliability was much lower than predicted by this model, even though component reliabilities were those indicated in Table 1.…”

Section: System Reliability Under Failure Independence Assumptionmentioning

confidence: 99%

See 1 more Smart Citation

Error Propagation in the Reliability Analysis of Component Based Systems

Popic

Desovski

Abdelmoez

et al.

16th IEEE International Symposium on Software Reliability Engineering (ISSRE'05)

Self Cite

View full text Add to dashboard Cite

Component based development is gaining popularity in the software engineering community. The reliability of components affects the reliability of the system. Different models and theories have been developed to estimate system reliability given the information about system architecture and the quality of the components. Almost always in these models a key attribute of component-based systems, the error propagation between the components, is overlooked and not taken into account in the reliability prediction.We extend our previous work on Bayesian reliability prediction of component based systems by introducing the error propagation probability into the model. We demonstrate the impact of the error propagation in a case study of an automated Personnel Access Control System. We conclude that error propagation may have a significant impact on the system reliability prediction and, therefore, future architecture-based models should not ignore it.

show abstract

Section: The Sensitivity Analysis Assuming Failure Independencesupporting

confidence: 83%

Section: System Reliability Under Failure Independence Assumptionmentioning

confidence: 99%

Error Propagation in the Reliability Analysis of Component Based Systems

Popic

Desovski

Abdelmoez

et al.

16th IEEE International Symposium on Software Reliability Engineering (ISSRE'05)

Self Cite

View full text Add to dashboard Cite

show abstract

“…Several studies have been conducted to investigate the relationship between code coverage and software reliability (Adams 1980;Ramsey and Basili 1985;Garg 1994;Veevers and Marshall 1994;Malaiya et al 1994;Jalote and Muralidhara 1994;Varadan 1995;Horgan et al 1995;Malaiya et al 1996;Chen et al 1996;Gokhale et al 1996;Krishnamurthy and Mathur 1996;Chen et al 1997;Chen et al 2001;Ye and Malaiya 2002;Malaiya et al 2002;Grottke 2002;Pham and Zhang 2003;Li et al 2004). An early experiment using control flow and data flow based testing was conducted by Frate et al (1995a).…”

Section: Motivationmentioning

confidence: 99%

A binomial software reliability model based on coverage of structural testing criteria

et al. 2007

View full text Add to dashboard Cite

A new approach to software reliability modeling is discussed where variables indirectly related with software reliability are used to provide additional information for the modeling process. Previous studies, empirical and theoretical evidences, and results from experiments indicate that there is a strong relationship between software reliability and coverage of program elements required to be exercised by structural testing criteria. This paper develops a binomial type coverage-based software reliability model through the definition of a coverage-based failure rate function. The Binomial software reliability Model Based on Coverage-BMBC-is proposed and discussed. In the BMBC test data between failures is used instead of time as independent variable; the model was assessed with test data from a real application, making use of the following structural testing criteria: all-nodes, all-edges, and potential-uses-a data-flow based family of testing criteria. The results from our experiments have shown that our modeling approach has some advantages over some traditional reliability models and points to a very promising research direction in software reliability.

show abstract

“…To predict software reliability at the end of requirements stage with limited information about a system at hand, appropriate measures (or metrics) need to be selected and methods should be developed to bridge the gap between measures and reliability. In our previous research [5], we found that CEGA is a promising candidate for this purpose.…”

Section: Introductionmentioning

confidence: 95%