Prediction of software reliability

Willem D. van Driel, J.W. Bikker, M. Tijink

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
17 Downloads (Pure)

Abstract

It is known that quantitative measures for the reliability of software systems can be derived from software reliability models. And, as such, support the product development process. Over the past four decades, research activities in this area have been performed. As a result, many software reliability models have been proposed. It was shown that, once these models reach a certain level of convergence, it can enable the developer to release the software. And stop software testing accordingly. Criteria to determine the optimal testing time include the number of remaining errors, failure rate, reliability requirements, or total system cost. In this paper we will present our results in predicting the reliability of software for agile testing environments. We seek to model this way of working by extending the Jelinski-Moranda model to a ‘stack’ of feature-specific models, assuming that the bugs are labelled with the feature they belong to. In order to demonstrate the extended model, several prediction results of actual cases will be presented. The questions to be answered in these cases are: how many software bugs remain in the software and should one decide to stop testing the software?

Original languageEnglish
Article number114074
Pages (from-to)1-6
Number of pages6
JournalMicroelectronics Reliability
Volume119
DOIs
Publication statusPublished - 2021

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Bayesian statistics
  • Maturity growth
  • Reliability
  • Software

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