Combining query reduction and expansion for text-retrieval-based bug localization

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dc.contributor.authorFlorez, J.M.
dc.contributor.authorChaparro, O.
dc.contributor.authorTreude, C.
dc.contributor.authorMarcus, A.
dc.contributor.conferenceIEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) (9 Mar 2021 - 12 Mar 2021 : virtual online)
dc.date.issued2021
dc.description.abstractAutomated text-retrieval-based bug localization (TRBL) techniques normally use the full text of a bug report to formulate a query and retrieve parts of the code that are buggy. Previous research has shown that reducing the size of the query increases the effectiveness of TRBL. On the other hand, researchers also found improvements when expanding the query (i.e., adding more terms). In this paper, we bring these two views together to reformulate queries for TRBL. Specifically, we improve discourse-based query reduction strategies, by adopting a combinatorial approach and using task phrases from bug reports, and combine them with a state-of-the-art query expansion technique, resulting in 970 query reformulation strategies. We investigate the benefits of these strategies for localizing buggy code elements and define a new approach, called QREX, based on the most effective strategy. We evaluated the reformulation strategies, including QREX, on 1,217 queries from different software systems to retrieve buggy code artifacts at three code granularities, using five state-of-the-art automated TRBL approaches. The results indicate that QREX increases TRBL effectiveness by 4% - 12.6%, compared to applying query reduction and expansion in isolation, and by 32.1%, compared to the no-reformulation baseline.
dc.description.statementofresponsibilityJuan Manuel Florez, Oscar Chaparro, Christoph Treude, Andrian Marcus
dc.identifier.citationProceedings of the Euromicro Conference on Software Maintenance and Reengineering, CSMR, 2021, pp.166-176
dc.identifier.doi10.1109/SANER50967.2021.00024
dc.identifier.isbn9781728196305
dc.identifier.issn1534-5351
dc.identifier.orcidTreude, C. [0000-0002-6919-2149]
dc.identifier.urihttp://hdl.handle.net/2440/131348
dc.language.isoen
dc.publisherIEEE
dc.publisher.placeonline
dc.rights©2021 IEEE
dc.source.urihttps://ieeexplore.ieee.org/xpl/conhome/9425868/proceeding
dc.titleCombining query reduction and expansion for text-retrieval-based bug localization
dc.typeConference paper
pubs.publication-statusPublished

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