Research Article
Supporting evidence-based Software Engineering with collaborative information retrieval
@INPROCEEDINGS{10.4108/icst.collaboratecom.2010.9, author={Heri Ramampiaro and Daniela Cruzes and Reidar Conradi and Manoel Mendona}, title={Supporting evidence-based Software Engineering with collaborative information retrieval}, proceedings={6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing}, publisher={IEEE}, proceedings_a={COLLABORATECOM}, year={2011}, month={5}, keywords={Collaborative Information Retrieval Empirical Software Engineering Systematic Review}, doi={10.4108/icst.collaboratecom.2010.9} }- Heri Ramampiaro
Daniela Cruzes
Reidar Conradi
Manoel Mendona
Year: 2011
Supporting evidence-based Software Engineering with collaborative information retrieval
COLLABORATECOM
ICST
DOI: 10.4108/icst.collaboratecom.2010.9
Abstract
The number of scientific publications is constantly increasing, and the results published on Empirical Software Engineering are growing even faster. Some software engineering publishers have began to collaborate with research groups to make available repositories of software engineering empirical data. However, these initiatives are limited due to issues related to the available search tools. As a result, many researchers in the area have adopted a semi-automated approach for performing searches for systematic reviews as a mean to extract empirical evidence from published material. This makes this activity labor intensive and error prone. In this paper, we argue that the use of techniques from information retrieval, as well as text mining, can support systematic reviews and improve the creation of repositories of SE empirical evidence.
