Mining software repositories using topic models

Author

Thomas, Stephen W.

Author_Institution

Software Anal. & Intell. Lab. (SAIL), Queen´´s Univ., Kingston, ON, Canada

fYear

2011

fDate

21-28 May 2011

Firstpage

1138

Lastpage

1139

Abstract

Software repositories, such as source code, email archives, and bug databases, contain unstructured and unlabeled text that is difficult to analyze with traditional techniques. We propose the use of statistical topic models to automatically discover structure in these textual repositories. This discovered structure has the potential to be used in software engineering tasks, such as bug prediction and traceability link recovery. Our research goal is to address the challenges of applying topic models to software repositories.

Keywords

data mining; program debugging; program diagnostics; software engineering; statistical analysis; bug databases; bug prediction; email archives; software engineering; software repository mining; source code; statistical topic model; textual repository; topic models; traceability link recovery; Adaptation models; Computational modeling; Data mining; Object oriented modeling; Resource management; Software; Software engineering; lda; mining software repositories; topic models;

fLanguage

English

Publisher

ieee

Conference_Titel

Software Engineering (ICSE), 2011 33rd International Conference on

Conference_Location

Honolulu, HI

ISSN

0270-5257

Print_ISBN

978-1-4503-0445-0

Electronic_ISBN

0270-5257

Type

conf

DOI

10.1145/1985793.1986020

Filename

6032613