Linkster: Enabling Efficient Manual Mining

TitleLinkster: Enabling Efficient Manual Mining
Publication TypeConference Paper
Year of Publication2010
AuthorsBird, C, Bachman, A, Rahman, F, Bernstein, A
Secondary TitleDemonstration Track, Proceedings of the 17th SIGSOFT Symposium on Foundations of Software Engineering
Keywordsartifacts, bug, bug tracking, data mining, email, mailing lists, open source, source code

While many uses of mined software engineering data are automatic in nature, some techniques and studies either require, or can be improved, by manual methods. Unfortunately, manually inspecting, analyzing, and annotating mined data can be difficult and tedious, especially when information from multiple sources must be integrated. Oddly, while there are numerous tools and frameworks for automatically mining and analyzing data, there is a dearth of tools which facilitate manual methods. To fill this void, we have developed LINKSTER, a tool which integrates data from bug databases, source code repositories, and mailing list archives to allow manual inspection and annotation. LINKSTER has already been used successfully by an OSS project lead to obtain data for one empirical study.


"LINKSTER efficiently displays, integrates, and allows inspection and annotation of information from three main sources of data: source code repositories, developer mailing lists archives, and bug tracking databases. LINKSTER requires access to a source code repository for file content and a database which contains the raw mined repository, mailing list, and bug tracking information. All notes and annotations made by the user are also recorded in the database."

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