2011 ExtSructKnowFromROMTexDataInSoftRepos

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Abstract

Software team members, as they communicate and coordinate their work with others throughout the life-cycle of their projects, generate different kinds of textual artifacts. Despite the variety of works for mining software artifacts, relatively little research has focused on communication artifacts. Software communication artifacts contain useful semantic information that is not fully explored by existing approaches. This thesis, presents the development of a text analysis method and tool to extract and represent valuable information from a wide range of textual data sources from software projects. The developed system integrates Natural Language Processing techniques and statistical text analysis methods, with software domain knowledge. The extracted information is represented as RDF-style triples which constitute interesting relations between developers and software products. We applied our system to analyze five different textual sources, i.e., source code commits, bug reports, email messages, chat logs, and wiki pages. In the evaluation of the system, we found its precision to be 82%, its recall 58%, and its F-measure 68%.

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2011 ExtSructKnowFromROMTexDataInSoftReposMaryam HasanExtracting Structured Knowledge From ROM Textual Data In Software Repositorieshttp://repository.library.ualberta.ca/dspace/bitstream/10048/1776/1/Hasan Maryam Spring+2011.pdf2011