Defect Prediction Models in Software Engineering: A Comprehensive Review on Methodologies

Authors

  • Prof. William Turner Director of Software Engineering at Harvard University, Massachusetts, USA Author

Keywords:

Software Engineering, Defect Prediction Models

Abstract

Defect prediction models play a crucial role in software engineering by aiding in the identification and prevention of defects before they impact the software's reliability and performance. This research article provides a comprehensive review of defect prediction models, examining their evolution, methodologies, challenges, and future directions. These metrics provide quantitative insights into code quality and defect proneness. Defective software modules cause software failures, increase development and maintenance costs, and decrease customer satisfaction [1]. The aim is to offer researchers and practitioners insights into the current state of defect prediction models and guide future advancements in this critical area of software quality assurance.

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References

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Published

29-12-2021

How to Cite

“Defect Prediction Models in Software Engineering: A Comprehensive Review on Methodologies”. Journal of Science & Technology, vol. 2, no. 5, Dec. 2021, pp. 93-104, https://www.thesciencebrigade.com/jst/article/view/57.

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