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Showing 1 to 3 of 3 for “"Software defect prediction"”.
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k-Label Dependent Evolutionary Distance Weighting for Software Defect Prediction
Software Defect Prediction is a field of study that uses machine learning algorithms to identify software that is susceptible to defects. Software defects and bugs can potentially cause errors that have significant consequences ranging from minor inconveniences to system failures. Identification of …
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Enhancing Software Defect Prediction: Investigating Diverse Representations of Source Code as Feature Values in Classical and Quantum Machine Learning Approaches
Software defect prediction is one of the prominent topics within the software engineering research domain. Studies have been delved into predicting and addressing software bugs (also known as defects/ issues). Yet, the landscape remains marked by a steady influx of new reports filling bug …
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Empirical Evaluation of Graph-Anonymized Metrics for JIT Defect Prediction
Software analytics data, housed in version control and issue report repositories, serves pivotal roles in organizational tasks like predicting code bugs and selecting code reviewers. Yet, individual organizations often lack the breadth of data needed for these analytics, making data sharing …