Patent · US Active

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

US10379999B2 · kind B2 · utility

1Cited by

6References

20Claims

0Family size

Assignee

Oracle International Corporation · US

Inventors

Prasad V. Bagal · San Jose, US
Sameer Joshi · San Jose, US
Hanlin Daniel Chien · San Jose, US
Ricardo Rey Diez · Zapopan, MX
David Woo · Zapopan, MX
Emily Ronshien Su · Mountain View, US
Sha Chang · Mountain View, US

Key dates

Filing date	Jan 11, 2016
Grant date	Aug 13, 2019
Priority date	—
Expiry date	Jan 13, 2036

Classification

Technology area (CPC G)Physics
CPC primaryG06F11/3692
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

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.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.