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Evidence-Based Software Engineering: Systematic Literature Review Process based on Visual Text Mining

Grant number: 12/02524-4
Support Opportunities:Scholarships in Brazil - Post-Doctorate
Effective date (Start): June 01, 2012
Effective date (End): April 30, 2014
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:Jose Carlos Maldonado
Grantee:Katia Romero Felizardo Scannavino
Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

Systematic Literature Review (SLR) is a methodology used to aggregate and summarize all relevant evidence of a specific research question. One of the activities associated with the SLR process is the selection of primary studies, which can be arduous, particularly when the researcher faces large volumes of primary studies. Visual Text Mining (VTM) can be used to support different activities of SLR processes, e.g., the selection of primary studies. An extension to the SLR process based on VTM was proposed during the PhD of the candidate. A pilot case study was conducted and the findings showed that the application of VTM is promising in terms of providing positive support to the study selection activity and that VTM techniques can be successfully employed to assist the SLR process. These results motivate us to continue with the research, therefore, this post-doctoral aims to experimentally validate the VTM-process. Controlled experiments and replications of these studies will be conducted to generate empirical evidences on the use of VTM in the context of SLRs in Software Engineering.

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
OCTAVIANO, FABIO R.; FELIZARDO, KATIA R.; MALDONADO, JOSE C.; FABBRI, SANDRA C. P. F.. Semi-automatic selection of primary studies in systematic literature reviews: is it reasonable?. EMPIRICAL SOFTWARE ENGINEERING, v. 20, n. 6, p. 1898-1917, . (12/02524-4)
PINTO FERRAZ FABBRI, SANDRA CAMARGO; FELIZARDO, KATIA ROMERO; FERRARI, FABIANO CUTIGI; MONTORO HERNANDES, ELIS CRISTINA; OCTAVIANO, FABIO ROBERTO; NAKAGAWA, ELISA YUMI; MALDONADO, JOSE CARLOS. Externalising tacit knowledge of the systematic review process. IET Software, v. 7, n. 6, SI, p. 298-307, . (08/57870-9, 12/02524-4)

Please report errors in scientific publications list by writing to: cdi@fapesp.br.