Software Testing Techniques Revisited for OWL Ontologies

Abstract

Abstract. Ontologies are an essential component of semantic knowledge bases and applications, and nowadays they are used in a plethora of domains. Despite the maturity of ontology languages, support tools and engineering techniques, the testing and validation of ontologies is a field which still lacks consolidated approaches and tools. This paper attempts at partly bridging that gap, taking a first step towards the extension of some traditional software testing techniques to ontologies expressed in a widely-used format. Mutation testing and coverage testing, revisited in the light of the peculiar features of the ontology language and structure, can can assist in designing better test suites to validate them, and overall help in the engineering and refinement of ontologies and software based on them.

GRADUATION: A GDPR-Based Mutation Methodology

“…On the contrary, considering the mutation testing in the context of the GDPR, to the best of our knowledge the only proposal currently available is represented by [2]. Indeed, this paper is the first attempts of extending mutation operators for validating ontologies expressing the GDPR's provisions.…”

“…In the context of the GDPR, and data privacy management in general, only few proposals are targeting the definition of mutation operators able to deal with the specific privacy characteristics and requirements of the privacy standards [2].…”

“…In the context of the GDPR, and data privacy management in general, only few proposals are targeting the definition of mutation operators able to deal with the specific privacy characteristics and requirements of the privacy standards [2]. In these cases, the proposed mutation operators do not exhaustively cover all the important criticalities of the GDPR.…”

Model-Driven Software Development Combined with Semantic Mutation of UML State Machines

“…In semantic mutation, graph structure of a model is not changed, as in a "standard" mutation testing. In this approach, different semantic interpretations of a model are analyzed [37,38].…”

The DAta Protection REgulation COmpliance Model

“…23 Further testing techniques for the ontology, borrowed from software engineering literature, include coverage testing and mutation testing. 12 The evaluation of the ontology's semantic soundness, i.e., how well the ontology describes the domain, is based on CQs. This kind of evaluation is currently ongoing, and some partial results (actual CQs with their SPARQL translation) are shown in previous works.…”