Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3145
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dc.contributor.authorKumar, Kulamala Vinod-
dc.contributor.authorTeja, A. Sarath Chandra-
dc.contributor.authorMaru, Abha-
dc.contributor.authorSingla, Yogesh-
dc.contributor.authorMohapatra, Durga Prasad-
dc.date.accessioned2019-01-01T13:04:31Z-
dc.date.available2019-01-01T13:04:31Z-
dc.date.issued2018-12-
dc.identifier.citation17th International Conference on Industrial Technology (ICIT 2018), Bhubaneswar , India, 20-22 December 2018en_US
dc.identifier.urihttp://hdl.handle.net/2080/3145-
dc.descriptionCopyright of this document belongs to proceedings publisher.en_US
dc.description.abstractSoftware measurement is yet in an infant stage. There is hardly any efficient quantitative method to represent software reliability. The existing methods are not generic and have many limitations. Various techniques could be used to enhance software reliability. However, one has to not only balance time but also cater to budget constraints. Computational Intelligence (CI) techniques that have been explored for software reliability prediction have shown remarkable results. In this paper, the applications of CI techniques for software reliability prediction are surveyed and an evaluation based on some selected performance criteria is presented.en_US
dc.subjectSoftware reliabilityen_US
dc.subjectAssessmenten_US
dc.subjectFault predictionen_US
dc.subjectComputational intelligence techniquesen_US
dc.titlePredicting Software Reliability using Computational Intelligence Techniques: A Reviewen_US
dc.typeArticleen_US
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