Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/348739
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dc.date.accessioned2021-11-23T12:17:14Z-
dc.date.available2021-11-23T12:17:14Z-
dc.identifier.urihttp://hdl.handle.net/10603/348739-
dc.description.abstractIn recent years, importance of software has increased due to development of softwarebased newlineautomated systems for multitudinous applications. The volume and complexity newlineof software with demand has increased day by day to provide reliability, quality, and newlinesecurity with integration of latest technologies and to enhance cross platform newlinecommunication capability. Therefore, it is challenging and difficult work to produce newlinefault free reliable software with constraints of finance and allocated time. This fault newlinecauses the failure of software dependent system and shows the significant impact on newlinereliability and productivity of system. Thus software fault classification (SFC) is newlineimportant to maintain the quality of software system and elimination of faults makes newlinethe software reliable after each version. The SFC system operates on various metrics newlinefor diagnosis of faults. The SFC uses the data generated from previous versions of newlinesoftware. newline
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleSoft Computing Techniques for Software Fault Prediction
dc.title.alternative
dc.creator.researcherPandey, Anil Kumar
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Software Engineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordSoft computing
dc.description.note
dc.contributor.guideGupta, Manjari
dc.publisher.placeVaranasi
dc.publisher.universityBanaras Hindu University
dc.publisher.institutionDepartment of Computer Science
dc.date.registered2015
dc.date.completed2018
dc.date.awarded
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science

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01_title.pdfAttached File566.25 kBAdobe PDFView/Open
02_certificate.pdf117.49 kBAdobe PDFView/Open
03_content.pdf94.05 kBAdobe PDFView/Open
04_abstract.pdf105.69 kBAdobe PDFView/Open
05_acknowledgement.pdf128.88 kBAdobe PDFView/Open
06_abbreviation.pdf103.51 kBAdobe PDFView/Open
07_notation.pdf108.66 kBAdobe PDFView/Open
08_list of tables and figures.pdf83.83 kBAdobe PDFView/Open
09_list of glossary.pdf106.06 kBAdobe PDFView/Open
10_list of algorithm.pdf100.86 kBAdobe PDFView/Open
11_preface.pdf92.36 kBAdobe PDFView/Open
12_chapter1.pdf412.64 kBAdobe PDFView/Open
13_chapter2.pdf211.74 kBAdobe PDFView/Open
14_chapter3.pdf814.61 kBAdobe PDFView/Open
15_chapter4.pdf279.03 kBAdobe PDFView/Open
16_chapter5.pdf850.83 kBAdobe PDFView/Open
17_chapter6.pdf100.43 kBAdobe PDFView/Open
18_bibliograhy.pdf197.93 kBAdobe PDFView/Open
19_appendix.pdf2.24 MBAdobe PDFView/Open
80_recommendation.pdf665.97 kBAdobe PDFView/Open


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