Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/538877
Title: Enhancing the Performance of Software Defect Prediction Model by Alleviating the Class Imbalance Problem
Researcher: Arun, C
Guide(s): Lakshmi, C
Keywords: Computer Science
Computer Science Interdisciplinary Applications
Engineering and Technology
University: SRM Institute of Science and Technology
Completed Date: 2023
Abstract: Software and its applications have been a prominent component in every aspect and field of engineering, either it be manufacturing, finance, medicine, automobile, and so on. Delivering high-quality software components has been the cornerstone of the Software engineering domain, which is enhanced by the use of early prediction techniques. Detecting the defect before testing activities improves the testing process and enhances the quality of the Software. newlineSoftware Defect Prediction (SDP) is the process of tracing defective or faulty software artifacts, i.e., classes, functions, or modules, before the testing process, which aids the testing activity by effectively allocating the resources toward defective components. SDP identifies the defect proneness of the software components using its underlying properties, i.e., various metrics components used to assess the component quality during different stages of software development newline
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URI: http://hdl.handle.net/10603/538877
Appears in Departments:Department of Computer Science Engineering

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01_title.pdfAttached File32.59 kBAdobe PDFView/Open
02_preliminary page.pdf123.19 kBAdobe PDFView/Open
03_content.pdf91.4 kBAdobe PDFView/Open
04_abstract.pdf84.09 kBAdobe PDFView/Open
05_chapter 1.pdf577.8 kBAdobe PDFView/Open
06_chapter 2.pdf211.02 kBAdobe PDFView/Open
07_chapter 3.pdf493.88 kBAdobe PDFView/Open
08_chapter 4.pdf990.48 kBAdobe PDFView/Open
09_chapter 5.pdf626.7 kBAdobe PDFView/Open
10_chapter 6.pdf171.52 kBAdobe PDFView/Open
11_annexures.pdf240.47 kBAdobe PDFView/Open
80_recommendation.pdf201.5 kBAdobe PDFView/Open
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