Analyzing Bug Reports by Topic Mining in Software Evolution
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.
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.