Experience Report on Developing an Ontology-based Approach for Knowledge Management in Software Testing

  • Érica Ferreira de Souza UTFPR
  • Ricardo de Almeida Falbo UFES
  • Marcos S. Specimille UFES
  • Alexandre G. N. Coelho UFES
  • Nandamudi L. Vijaykumar INPE
  • Katia Romero Felizardo UTFPR
  • Giovani Volnei Meinerz UTFPR


Software testing is a knowledge intensive process. Thus, Knowledge Management (KM) emerges as a means to manage testing knowledge, and, consequently, to improve software quality. However, there are only a few KM solutions supporting software testing. This paper reports experiences from the development of an approach, Ontology-based Testing Knowledge Management (OntoT-KM), to assist in launching KM initiatives in the software testing domain with the support of Knowledge Management Systems (KMSs). OntoT-KM provides a process guiding how to start applying KM in software testing. OntoT-KM is based on the findings of a systematic mapping on KM in software testing and the results of a survey with testing practitioners. Moreover, OntoT-KM considers the conceptualization established by a Reference Ontology on Software Testing (ROoST). As a proof of concept, OntoT-KM was applied to develop a KMS called Testing KM Portal (TKMP), which was evaluated in terms of usefulness, usability and functional correctness. Results show that the developed KMS from OntoT-KM is a potential system for managing knowledge in software testing, so, the approach is able to guide KM initiatives in software testing.
Palavras-chave: Knowledge Management, Knowledge Management System, Software Testing, Testing Ontology
SOUZA, Érica Ferreira de; FALBO, Ricardo de Almeida; SPECIMILLE, Marcos S.; COELHO, Alexandre G. N.; VIJAYKUMAR, Nandamudi L.; FELIZARDO, Katia Romero; MEINERZ, Giovani Volnei. Experience Report on Developing an Ontology-based Approach for Knowledge Management in Software Testing. In: SIMPÓSIO BRASILEIRO DE QUALIDADE DE SOFTWARE (SBQS), 19. , 2020, São Luiz do Maranhão. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 314-323.