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Effective use of ontologies in software measurement

  • Félix García (a1), Francisco Ruiz (a1), Coral Calero (a1), Manuel F. Bertoa (a2), Antonio Vallecillo (a2), Beatriz Mora (a1) and Mario Piattini (a1)
  • DOI: http://dx.doi.org/10.1017/S0269888909000125
  • Published online: 01 March 2009
Abstract
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.

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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

M. Bertoa , F. García A. Vallecillo 2006. An ontology for software measurement. In Ontologies for Software Engineering and Technologies, Calero, C., Ruiz, F. & Piattini, M. (eds). Springer-Verlag, 175196.

C. Caro , C. Calero , I. Caballero M. Piattini 2008. A proposal for a set of attributes relevant for Web portal data quality. Software Quality Journal 16(4), 513542.

F. García , M. Bertoa , C. Calero , A. Vallecillo , F. Ruiz , M. Piattini M. Genero 2006. Towards a consistent terminology for software measurement. Information and Software Technology 48(8), 631644.

F. García , M. Serrano , J. Cruz-Lemus , F. Ruiz M. Piattini 2007. Managing software process measurement: a metamodel-based approach. Information Sciences 177, 25702586.

T. R. Gruber 1993. A translation approach to portable ontologies. Knowledge Acquisition 5(2), 199220.

E. Guerra , J. de Lara P. Díaz 2008. Visual specification of measurements and redesigns for domain specific visual languages. Journal of Visual Languages and Computing 19(8), 399425.

M. Mernik , J. Heering A. M. Sloane 2005. When and how to develop domain-specific languages. ACM Computing Surveys 37(4), 316344.

F. Ruiz J. R. Hilera 2006. Using ontologies in software engineering and technology. In Ontologies in Software Engineering and Software Technology, Calero, C., Ruiz, F. & Piattini, M. (eds). Springer-Verlag, 49102.

S. Staab , H. Schnurr Y. Sure 2001. Knowledge processes and ontologies. IEEE Intelligent Systems 16(1), 2634.

R. Wang D. Strong 1996. Beyond accuracy: what data quality means to data consumers. Journal of Management Information Systems 12, 533.

Z. Yang , S. Cai , Z. Zhou N. Zhou 2004. Development and validation of an instrument to measure user perceived service quality of information presenting Web portals. Information and Management 42, 575589.

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The Knowledge Engineering Review
  • ISSN: 0269-8889
  • EISSN: 1469-8005
  • URL: /core/journals/knowledge-engineering-review
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