Current model-driven development approaches allow for a more productive way of developing software systems. However, building tools and languages for software development still suffer a neglect of semantics in modeling and metamodeling.
An interest to strengthen semantics in modeling and metamodeling that gained scientific and commercial attention is the integration of ontology technology and software development. Ontology formalisms for consistency validation and dynamic classification as well as semantic web technologies for enabling shared terminologies and automated reasoning provide means for leveraging metamodeling and language engineering.
This tutorial on Bridging Software Languages and Ontology Technologies at SPLASH 2010 enlightens the potential of ontology and semantic web technology for modeling and metamodeling in software development, positioning it among modeling standards like UML, and MOF; and (2) illustrates ontology-enabled software development with real application scenarios in areas like software design patterns, domain-specific languages and variability management.
Showing posts with label metamodel. Show all posts
Showing posts with label metamodel. Show all posts
Bridging Software Languages and Ontology Technologies: Tutorial at SPLASH 2010
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Wednesday, August 4, 2010
OWLizer: Software Languages -> OWL ontologies Part I
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Monday, March 29, 2010
Software development consists of multiple phases, from inception to production. During each software development phase, developers and other actors generate many artifacts, eg. documents, models, diagrams, code, tests and bug reports. Although some of these artifacts are integrated, they are usually handled as islands inside the software development process.
Many of these artifacts (graphical or textual) are written using a structured language, which has a defined grammar. In a model-driven environment, concepts of software languages are represented by metamodels, whereas the artifacts written in those software languages are represented by models, which are described by the language metamodel. Thus, by transforming software metamodels and models into OWL and by aligning the OWL ontologies corresponding to software languages, we are able to link multiple data sources of a software development process, creating a linked-data repository for software development.
Let us consider an example of integrating two data sources: UML diagrams and Java Code. Regardless of generating Java code from UML diagrams, developers would like to have a consistent view of corresponding classes and methods in UML and Java, i.e., developers might want to consult UML diagrams looking for a corresponding Java class. In this scenario, OWL and ontology technologies play an important role.
Fig. 1 depicts the usage of M3 transformations together with ontology technologies [1]. UML metamodel and model as well as Java grammar (metamodel) and java code (model) are transformed into OWL ontologies. Ontology alignment techniques [] might identify some concepts in common between the two ontologies (UML and Java), e.g., package, class, method. Moreover, individuals with the same name in these two ontologies are likely the same.
Once the two ontologies are aligned, queries against the Java ontology also retrieve elements defined in UML diagrams. Now it is possible to retrieve sequence diagrams including a given Java class, since the two artifacts (UML diagrams and Java code) are now linked. This is only one example of the great potential provided by linking software engineering artifacts using OWL technologies.
[1] Gröner, G., Silva Parreiras, F., Staab, S., Walter, T.: Software Modeling Using Ontology Technologies. In: Rudi Studer - A Review on Semantic Web Research. Springer Verlag (2011)
Many of these artifacts (graphical or textual) are written using a structured language, which has a defined grammar. In a model-driven environment, concepts of software languages are represented by metamodels, whereas the artifacts written in those software languages are represented by models, which are described by the language metamodel. Thus, by transforming software metamodels and models into OWL and by aligning the OWL ontologies corresponding to software languages, we are able to link multiple data sources of a software development process, creating a linked-data repository for software development.
Let us consider an example of integrating two data sources: UML diagrams and Java Code. Regardless of generating Java code from UML diagrams, developers would like to have a consistent view of corresponding classes and methods in UML and Java, i.e., developers might want to consult UML diagrams looking for a corresponding Java class. In this scenario, OWL and ontology technologies play an important role.
Fig. 1 depicts the usage of M3 transformations together with ontology technologies [1]. UML metamodel and model as well as Java grammar (metamodel) and java code (model) are transformed into OWL ontologies. Ontology alignment techniques [] might identify some concepts in common between the two ontologies (UML and Java), e.g., package, class, method. Moreover, individuals with the same name in these two ontologies are likely the same.
Once the two ontologies are aligned, queries against the Java ontology also retrieve elements defined in UML diagrams. Now it is possible to retrieve sequence diagrams including a given Java class, since the two artifacts (UML diagrams and Java code) are now linked. This is only one example of the great potential provided by linking software engineering artifacts using OWL technologies.
[1] Gröner, G., Silva Parreiras, F., Staab, S., Walter, T.: Software Modeling Using Ontology Technologies. In: Rudi Studer - A Review on Semantic Web Research. Springer Verlag (2011)
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