Modelling is one of the most frequent tasks in the area of information systems (ISs), with models such as schemata, ontologies, patterns and architectures forming the bases for their creation. Very often, however, the difference between these types of models is not clear and causes confusion and erratic use of the terms. The aim of this paper is to clarify the concept of model through a study of some of the more common ones used in ISs. This proposal is presented through an ontology, where we show how we conceptualize models according to their role in the development of an IS: the model understood as the representation of a domain or as a reality serving as an example.

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.

This paper develops an ontological basis for evaluating software design methods, based on the situated function–behaviour–structure framework. This framework accounts for the situatedness of designing, viewing it as a dynamic activity driven by interactions between designers and the artefacts being designed. On the basis of this framework, we derive a general evaluation schema that we apply to five software design methods. The ideas presented in this work contribute to a better understanding of design methods, and uncover opportunities for method integration and development.

Component-based development (CBD) has become an important emerging topic in the software engineering field. It promises long-sought-after benefits such as increased software reuse, reduced development time to market and, hence, reduced software production cost. Despite the huge potential, the lack of reasoning support and development environment of component modeling and verification may hinder its development. Methods and tools that can support component model analysis are highly appreciated by industry. Such a tool support should be fully automated as well as efficient. At the same time, the reasoning tool should scale up well as it may need to handle hundreds or even thousands of components that a modern software system may have. Furthermore, a distributed environment that can effectively manage and compose components is also desirable. In this paper, we present an approach to the modeling and verification of a newly proposed component model using Semantic Web languages and their reasoning tools. We use the Web Ontology Language and the Semantic Web Rule Language to precisely capture the inter-relationships and constraints among the entities in a component model. Semantic Web reasoning tools are deployed to perform automated analysis support of the component models. Moreover, we also proposed a service-oriented architecture (SOA)-based semantic web environment for CBD. The adoption of Semantic Web services and SOA make our component environment more reusable, scalable, dynamic and adaptive.

The success of a software system strongly depends on the ability of turning a precise domain analysis into a concrete architecture. Even if the domain model relies on sound ontological bases, there is often a wide semantic gap between the conceptual model and the concrete components that should reify it. To fill the semantic gap, relevant domain concepts should be engineered by identifying the corresponding architectural abstractions, which can be realized by concrete software components. Space plays a crucial role in many application domains, but surprisingly, related architectural abstractions have not emerged yet. This paper proposes space-related abstractions derived from the application of classical software engineering principles; in particular, the information hiding principle that leads to an operational definition of space. Basic abstractions are refined to deal with architectural aspects. As the underlying software engineering principles are close to principles that underlie the definition of space ontologies, the conjecture is that the proposed space architectural abstractions might be the basis for a formalization in ontological terms.