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ASE 2014

Combining rule-based and information retrieval techniques to assign software change requests

Yguaratã Cerqueira Cavalcanti, Ivan do Carmo Machado, Paulo Anselmo da Mota Silveira Neto, Eduardo Santana de Almeida, Silvio Romero de Lemos Meira

PDFDOI 10.1145/2642937.2642964dblp

Abstract

Change Requests (CRs) are key elements to software maintenance and evolution. Finding the appropriate developer to a CR is crucial for obtaining the lowest, economically feasible, fixing time. Nevertheless, assigning CRs is a labor-intensive and time consuming task. In this paper, we present a semi-automated CR assignment approach which combine rule-based and information retrieval techniques. The approach emphasizes the use of contextual information, essential to effective assignments, and puts the development team in control of the assignment rules, toward making its adoption easier. Results of an empirical evaluation showed that the approach is up to 46,5% more accurate than approaches which rely solely on machine learning techniques.

BibTeX
@inproceedings{Cavalcanti-al:ASE14,
  author    = {Yguarat{\~{a}} Cerqueira Cavalcanti and
               Ivan do Carmo Machado and
               Paulo Anselmo da Mota Silveira Neto and
               Eduardo Santana de Almeida and
               Silvio Romero de Lemos Meira},
  title     = {Combining rule-based and information retrieval techniques to assign software change requests},
  booktitle = {ASE},
  pages     = {325--330},
  publisher = {{ACM}},
  year      = {2014},
}

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