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Article type: Research Article
Authors: Souza, Érica Ferreira dea; * | Falbo, Ricardo de Almeidab | Vijaykumar, Nandamudi Lankalapalic
Affiliations: [a] Department of Computer, Federal Technological University of Paraná, UTFPR, Cornélio Procópio/PR, Brazil | [b] Department of Computer Science, Federal University of Espírito Santo, UFES, Vitória/ES, Brazil | [c] Laboratory of Computing and Applied Mathematics, National Institute for Space Research, INPE, São José dos Campos/SP, Brazil
Correspondence: [*] Corresponding author: Érica Ferreira de Souza, Department of Computer, Federal Technological University of Paraná, UTFPR. Av. Alberto Carazzai, 1640, 86300-000, Cornélio Procópio/PR, Brazil. E-mail: ericasouza@utfpr.edu.br.
Note: [] Accepted by: Oscar Pastor
Abstract: Software testing is a complex and critical process for achieving product quality. Its importance has been increasing and well recognized, and there is a growing concern in improving the accomplishment of this process. In this context, Knowledge Management (KM) emerged as an important supporting approach to improve the software testing process. However, managing relevant testing knowledge requires effective means to represent and to associate semantics to a large volume of testing information. To address this concern, we have developed a Reference Ontology on Software Testing (ROoST). ROoST establishes a common conceptualization about the software testing domain, which can serve several KM-related purposes, such as defining a common vocabulary for knowledge workers with respect to the testing domain, structuring testing knowledge repositories, annotating testing knowledge items, and for making search for relevant information easier. In this paper, we present ROoST, and we discuss how it was developed using two ontology pattern languages. Moreover, we discuss how we evaluated ROoST following four complementary approaches: assessment by humans, data-driven evaluation, ontology testing, and application-based evaluation.
Keywords: Software testing, ontology, reference ontology, ontology evaluation, knowledge management
DOI: 10.3233/AO-170177
Journal: Applied Ontology, vol. 12, no. 1, pp. 59-90, 2017
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