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

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

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 rep...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Su, Emily Ronshien, Chang, Sha, Chien, Hanlin Daniel, Bagal, Prasad V, Joshi, Sameer Arun, Diez, Ricardo Rey, Woo, David Cavazos
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Beschreibung
Zusammenfassung: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.