Software engineering sub-ontology for specific software development

In this paper we propose software engineering sub ontology. We called it application-specific ontology, for specific software development. It enables remote team members browsing, searching, sharing, and authoring ontological data under the distributed software engineering projects environment. We transform explicit meaningful human knowledge into application-specific ontology, where knowledge structures and semantics are linked, and we go through a formal hand-shaking agreement establishing process before the semantic contents are updated in ontology repositories. The application-specific ontology is used for communication over project agreement to facilitate better, highly consistent communications and formalized domain knowledge sharing. We assume that object-oriented development is deployed in the distributed projects. The knowledge of object-oriented development formed in the application-specific ontology clarifies the object-oriented development concepts in a machine understandable form. Software agent, for example, can be utilised to extract information

A Bootstrap Theory: the SEMAT Kernel Itself as Runnable Software

The SEMAT kernel is a thoroughly thought generic framework for Software Engineering system development in practice. But one should be able to test its characteristics by means of a no less generic theory matching the SEMAT kernel. This paper claims that such a matching theory is attainable and describes its main principles. The conceptual starting point is the robustness of the Kernel alphas to variations in the nature of the software system, viz. to software automation, distribution and self-evolution. From these and from observed Kernel properties follows the proposed bootstrap principle: a software system theory should itself be a runnable software. Thus, the kernel alphas can be viewed as a top-level ontology, indeed the Essence of Software Engineering. Among the interesting consequences of this bootstrap theory, the observable system characteristics can now be formally tested. For instance, one can check the system completeness, viz. that software system modules fulfill each one of the system requirements.Comment: 8 pages; 2 figures; Preprint of paper accepted for GTSE'2014 Workshop, within ICSE'2014 Conferenc

Towards Knowledge-Intensive Software Engineering

Postprin

A Process Framework for Semantics-aware Tourism Information Systems

The growing sophistication of user requirements in tourism due to the advent of new technologies such as the Semantic Web and mobile computing has imposed new possibilities for improved intelligence in Tourism Information Systems (TIS). Traditional software engineering and web engineering approaches cannot suffice, hence the need to find new product development approaches that would sufficiently enable the next generation of TIS. The next generation of TIS are expected among other things to: enable semantics-based information processing, exhibit natural language capabilities, facilitate inter-organization exchange of information in a seamless way, and evolve proactively in tandem with dynamic user requirements. In this paper, a product development approach called Product Line for Ontology-based Semantics-Aware Tourism Information Systems (PLOSATIS) which is a novel hybridization of software product line engineering, and Semantic Web engineering concepts is proposed. PLOSATIS is presented as potentially effective, predictable and amenable to software process improvement initiatives

Enterprise application reuse: Semantic discovery of business grid services

Web services have emerged as a prominent paradigm for the development of distributed software systems as they provide the potential for software to be modularized in a way that functionality can be described, discovered and deployed in a platform independent manner over a network (e.g., intranets, extranets and the Internet). This paper examines an extension of this paradigm to encompass ‘Grid Services’, which enables software capabilities to be recast with an operational focus and support a heterogeneous mix of business software and data, termed a Business Grid - "the grid of semantic services". The current industrial representation of services is predominantly syntactic however, lacking the fundamental semantic underpinnings required to fulfill the goals of any semantically-oriented Grid. Consequently, the use of semantic technology in support of business software heterogeneity is investigated as a likely tool to support a diverse and distributed software inventory and user. Service discovery architecture is therefore developed that is (a) distributed in form, (2) supports distributed service knowledge and (3) automatically extends service knowledge (as greater descriptive precision is inferred from the operating application system). This discovery engine is used to execute several real-word scenarios in order to develop and test a framework for engineering such grid service knowledge. The examples presented comprise software components taken from a group of Investment Banking systems. Resulting from the research is a framework for engineering servic

Ontology-based modelling of architectural styles

The conceptual modelling of software architectures is of central importance for the quality of a software system. A rich modelling language is required to integrate the different aspects of architecture modelling, such as architectural styles, structural and behavioural modelling, into a coherent framework. Architectural styles are often neglected in software architectures. We propose an ontological approach for architectural style modelling based on description logic as an abstract, meta-level modelling instrument. We introduce a framework for style definition and style combination. The application of the ontological framework in the form of an integration into existing architectural description notations is illustrated

Ontology of core data mining entities

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend