Predicting Software Reliability Using Particle SWARM Optimization Technique
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shin, Su Min | - |
dc.contributor.author | Uroosa, Sk. | - |
dc.date.accessioned | 2023-03-08T19:43:26Z | - |
dc.date.available | 2023-03-08T19:43:26Z | - |
dc.date.issued | 2015 | - |
dc.identifier.issn | 2508-9080 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/64721 | - |
dc.description.abstract | Building programming unwavering quality development models means software reliability growth models (SRGM) for evaluating in the feeling of foreseeing the product dependability speaks to an incredible test for programming testing designers in the product commercial ventures. Being able to foresee or gauge the quantity of flaws in the product amid improvement and testing procedure helps altogether in indicating/registering the product discharge day into the business sector and in overseeing venture assets (i.e. individuals and money).There are different routines to appraise the parameters of programming unwavering quality development models, for example, Subterranean insect state enhancement and Molecule swarm improvement means particle swarm optimization (PSO). We to investigate the upsides of utilizing PSO to better model the product dependability expectation process. | - |
dc.format.extent | 14 | - |
dc.publisher | 사단법인 아태인문사회융합기술교류학회 | - |
dc.title | Predicting Software Reliability Using Particle SWARM Optimization Technique | - |
dc.type | Article | - |
dc.identifier.doi | 10.21742/APJCRI.2015.09.02 | - |
dc.identifier.bibliographicCitation | 아시아태평양융합연구교류논문지, v.1, no.3, pp 17 - 30 | - |
dc.identifier.kciid | ART002264594 | - |
dc.description.isOpenAccess | N | - |
dc.citation.endPage | 30 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 17 | - |
dc.citation.title | 아시아태평양융합연구교류논문지 | - |
dc.citation.volume | 1 | - |
dc.publisher.location | 대한민국 | - |
dc.subject.keywordAuthor | Software Reliability | - |
dc.subject.keywordAuthor | SWARM | - |
dc.subject.keywordAuthor | SRGM | - |
dc.subject.keywordAuthor | PSO | - |
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