Bayesian optimum stopping rule for software release
OPSEARCH, ISSN: 0975-0320, Vol: 56, Issue: 1, Page: 242-260
2019
- 6Citations
- 1Usage
- 2Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations6
- Citation Indexes4
- Policy Citations2
- Policy Citation2
- Usage1
- Abstract Views1
- Captures2
- Readers2
Article Description
This Paper proposes a Bayesian approach to find out the optimum stopping rule of software testing. We consider a discrete periodic debugging framework so that software can be released for market once the criteria are fulfilled. Simplification of stopping rules were obtained by using some specific prior distributions of the number of remaining bugs. We also develop necessary and sufficient conditions for stopping the software testing. Some illustrative examples are presented.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85063152006&origin=inward; http://dx.doi.org/10.1007/s12597-018-00353-0; http://link.springer.com/10.1007/s12597-018-00353-0; http://link.springer.com/content/pdf/10.1007/s12597-018-00353-0.pdf; http://link.springer.com/article/10.1007/s12597-018-00353-0/fulltext.html; https://digitalcommons.isical.ac.in/journal-articles/920; https://digitalcommons.isical.ac.in/cgi/viewcontent.cgi?article=2674&context=journal-articles; https://dx.doi.org/10.1007/s12597-018-00353-0; https://link.springer.com/article/10.1007/s12597-018-00353-0
Springer Science and Business Media LLC
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