The Knowledge Engineering Review

Article

Effective use of ontologies in software measurement

Félix Garcíaa1, Francisco Ruiza1, Coral Caleroa1, Manuel F. Bertoaa2, Antonio Vallecilloa2, Beatriz Moraa1 and Mario Piattinia1

a1 Alarcos Research Group—Institute of Information Technologies & Systems, Department of Information Technologies & Systems—Escuela Superior de Informática, University of Castilla-La Mancha, Spain. e-mail: Felix.Garcia@uclm.es, Francisco.RuizG@uclm.es, Coral.Calero@uclm.es, Beatriz.Mora@uclm.es, Mario.Piattini@uclm.es

a2 Departamento de Lenguajes y Ciencias de la Computación, Universidad de Málaga. 29071 Málaga, España, Spain. e-mail: bertoa@lcc.uma.es, av@lcc.uma.es

Abstract

Ontologies are frequently used in the context of software and technology engineering. These can be grouped into two main categories, depending on whether they are used to describe the knowledge of a domain (domain ontologies) or whether they are used as software artifacts in software development processes. This paper presents some experiences and lessons learnt from the effective use of an ontology for Software Measurement, called software measurement ontology (SMO). The SMO was developed some years ago as a result of a thorough analysis of the software measurement domain. Its use as a domain ontology is presented first, a description of how the SMO can serve as a conceptual basis for comparing international standards related to software measurement. Second, the paper describes several examples of the applications of SMO as a software artifact. In particular, we show how the SMO can be instantiated to define a data quality model for Web portals, and also how it can be used to define a Domain-Specific Language (DSL) for measuring software entities. These examples show the significant role that ontologies can play as software artifacts in the realm of model-driven engineering and domain-specific modeling.