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Duplicate bug report detection using machine learning algorithms and automated feedback incorporation

机译:使用机器学习算法和自动反馈功能进行重复的错误报告检测

摘要

Duplicate bug report detection using machine learning algorithms and automated feedback incorporation is disclosed. For each set of bug reports, a user-classification of the set of bug reports as including duplicate bug reports or non-duplicate bug reports is identified. Also for each set of bug reports, correlation values corresponding to a respective feature, of a plurality of features, between bug reports in the set of bug reports is identified. Based on the user-classifications and the correlation values, a model is generated to identify any set of bug reports as including duplicate bug reports or non-duplicate bug reports. The model is applied to classify a particular bug report and a candidate bug report as duplicate bug reports or non-duplicate bug reports.
机译:公开了使用机器学习算法和自动反馈合并的重复错误报告检测。对于每组错误报告,标识出一组错误报告的用户分类,包括重复错误报告或非重复错误报告。同样对于每组错误报告,识别出与错误报告集合中的错误报告之间的多个特征中的相应特征相对应的相关值。基于用户分类和相关值,生成模型以将任何错误报告集识别为包括重复错误报告或非重复错误报告。该模型用于将特定错误报告和候选错误报告分类为重复错误报告或非重复错误报告。

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