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http://hdl.handle.net/2080/3145
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DC Field | Value | Language |
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dc.contributor.author | Kumar, Kulamala Vinod | - |
dc.contributor.author | Teja, A. Sarath Chandra | - |
dc.contributor.author | Maru, Abha | - |
dc.contributor.author | Singla, Yogesh | - |
dc.contributor.author | Mohapatra, Durga Prasad | - |
dc.date.accessioned | 2019-01-01T13:04:31Z | - |
dc.date.available | 2019-01-01T13:04:31Z | - |
dc.date.issued | 2018-12 | - |
dc.identifier.citation | 17th International Conference on Industrial Technology (ICIT 2018), Bhubaneswar , India, 20-22 December 2018 | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/3145 | - |
dc.description | Copyright of this document belongs to proceedings publisher. | en_US |
dc.description.abstract | Software 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.subject | Software reliability | en_US |
dc.subject | Assessment | en_US |
dc.subject | Fault prediction | en_US |
dc.subject | Computational intelligence techniques | en_US |
dc.title | Predicting Software Reliability using Computational Intelligence Techniques: A Review | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2018_ICIT_DPMohapatra_PredictingSoftware.pdf | Conference paper | 355.43 kB | Adobe PDF | View/Open |
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