Bayesian optimum stopping rule for software release

Ashis Kumar Chakraborty (), Gopal Krishna Basak () and Suchismita Das ()
Additional contact information
Ashis Kumar Chakraborty: Indian Statistical Institute, Kolkata
Gopal Krishna Basak: Indian Statistical Institute, Kolkata
Suchismita Das: S P Jain School of Global Management

OPSEARCH, 2019, vol. 56, issue 1, No 11, 242-260

Abstract: Abstract 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.

Keywords: Bayesian approach; Optimal release time; Prior distribution; Software reliability; Stopping rule; Primary: 62N05; Secondary: 90B25 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s12597-018-00353-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:opsear:v:56:y:2019:i:1:d:10.1007_s12597-018-00353-0

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/12597

DOI: 10.1007/s12597-018-00353-0

Access Statistics for this article

OPSEARCH is currently edited by Birendra Mandal

More articles in OPSEARCH from Springer, Operational Research Society of India
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().