Presentation Title

Analyzing Bug Reports by Topic Mining in Software Evolution

Presenter Information

Uy NguyenFollow

Advisor Information

Myoungkyu Song

Presentation Type

Poster

Start Date

26-3-2021 12:00 AM

End Date

26-3-2021 12:00 AM

Abstract

Reporting bugs is one of the vital activities for evolving software systems. Given such reports, developers cope with unanticipated behaviours during software development, maintenance, and operations. The description of bug reports typically includes (1) what errors occurred previously and (2) how a failure can be reproduced through specific steps, test inputs, and original configurations when a failure was created. However, analyzing bug reports is a tedious and error-prone process due to overflowing, complex terminologies. For example, diverse terms are used to represent similar or divergent elucidations by surrounding contexts during software development and maintenance. To address this problem, we present an approach that applies a topic mining technique to bug reports for finding an adequate code reviewer, who can potentially cope with reported failures, by inferring some hidden topics of a textual document.

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Mar 26th, 12:00 AM Mar 26th, 12:00 AM

Analyzing Bug Reports by Topic Mining in Software Evolution

Reporting bugs is one of the vital activities for evolving software systems. Given such reports, developers cope with unanticipated behaviours during software development, maintenance, and operations. The description of bug reports typically includes (1) what errors occurred previously and (2) how a failure can be reproduced through specific steps, test inputs, and original configurations when a failure was created. However, analyzing bug reports is a tedious and error-prone process due to overflowing, complex terminologies. For example, diverse terms are used to represent similar or divergent elucidations by surrounding contexts during software development and maintenance. To address this problem, we present an approach that applies a topic mining technique to bug reports for finding an adequate code reviewer, who can potentially cope with reported failures, by inferring some hidden topics of a textual document.