A metamodelling approach for i* model translations

The i* (i-star) framework has been widely adopted by the information systems community. Since the time it was proposed, different variations have arisen. Some of them just propose slight changes in the language definition, whilst others introduce constructs for particular usages. This flexibility is one of the reasons that makes i* attractive, but it has as counterpart the impossibility of automatically porting i* models from one context of use to another. This lack of interoperability makes difficult to build a repository of models, to adopt directly techniques defined for one variation, or to use i* tools in a feature-oriented instead of a variant-oriented way. In this paper, we explore in more detail the interoperability problem from a metamodel perspective. We analyse the state of the art concerning variations of the i* language, from these variations and following a proposal from Wachsmuth, we define a supermetamodel hosting identified variations, general enough so as to embrace others yet to exist. We present a translation algorithm oriented to semantic preservation and we use the XML-based iStarML interchange format to illustrate the interconnection of two tools.Peer ReviewedPostprint (author's final draft

An institution theory of formal meta-modelling in graphically extended BNF

Meta-modelling plays an important role in model driven software development. In this paper, a graphic extension of BNF (GEBNF) is proposed to define the abstract syntax of graphic modelling languages. From a GEBNF syntax definition, a formal predicate logic language can be induced so that meta-modelling can be performed formally by specifying a predicate on the domain of syntactically valid models. In this paper, we investigate the theoretical foundation of this metamodelling approach. We formally define the semantics of GEBNF and its induced predicate logic languages, then apply Goguen and Burstall’s institution theory to prove that they form a sound and valid formal specification language for meta-modelling

Tool interoperability using iStarML

iStarML is an XML-based format for enabling interoperability among i* tools. Its main design focus was to support data interchange even when involved tools implement different i* variants. In this paper, we present a summary of the format, we briefly describe the ccistarml Java library, and we show an application of it. We finally summarize the requirements for representing new i* concepts in order to generate a revised version of iStarML.Postprint (published version

Advanced Information Systems Engineering: 23rd International Conference, CAiSE 2011, London, UK, June 20-24, 2011. Proceedings

International audienc

Using a foundational ontology to investigate the semantics behind the concepts of the i* language

In the past few years, the community that develops i* has become aware of the problem of having so many variants, since it makes it difficult for newcomers to learn how to use the language and even to experts to efficiently exchange knowledge and disseminate their proposals. Moreover, this problem also delays the transfer of the i* framework to industrial settings. Our work is one of the current attempts to promote interoperability among the existing variants, and it does that by investigating the semantics behind the i* core concepts. For that, we apply a foundational ontology named UFO, which is used as a semantically coherent reference model to which the language should be isomorphic. In this paper, we report on the steps we have pursued, what we have accomplished so far, also setting the context for the work ahead.Peer ReviewedPostprint (author’s final draft

On Ontologology

The study of models, and related concepts such as metamodels, is largely situated within the software engineering community under the banner of model-driven development. Yet these concepts have some obvious parallels with concepts developed within the artificial intelligence community under the banners of ontologies and the semantic web. Although a considerable amount of work has been done that aims to relate the development of ontologies to the model-driven development of software, the place of bidirectional transformations within these connected worlds is (almost) unstudied. Yet, experts in the study of ontologies have experienced the need to check and restore consistency, and have developed techniques, terminology and tools that relate to these tasks. In this paper we provide a high-level introduction to the work that has been done, aiming to promote further study and perhaps collaboration between these communities

The Meaning of UML Models

The Unified Modelling Language (UML) is intended to express complex ideas in an intuitive and easily understood way. It is important because it is widely used in software engineering and other disciplines. Although an official definition document exists, there is much debate over the precise meaning of UML models. ¶ In response, the academic community have put forward many different proposals for formalising UML, but it is not at all obvious how to decide between them. Indeed, given that UML practitioners are inclined to reject formalisms as non-intuitive, it is not even obvious that the definition should be “formal” at all. Rather than searching for yet another formalisation of UML, our main aim is to determine what would constitute a good definition of UML. ¶ The first chapter sets the UML definition problem in a broad context, relating it to work in logic and the philosophy of science. ..

Metamodel based high-fidelity stochastic analysis of composite laminates: A concise review with critical comparative assessment

This paper presents a concise state-of-the-art review along with an exhaustive comparative investigation on surrogate models for critical comparative assessment of uncertainty in natural frequencies of composite plates on the basis of computational efficiency and accuracy. Both individual and combined variations of input parameters have been considered to account for the effect of low and high dimensional input parameter spaces in the surrogate based uncertainty quantification algorithms including the rate of convergence. Probabilistic characterization of the first three stochastic natural frequencies is carried out by using a finite element model that includes the effects of transverse shear deformation based on Mindlin’s theory in conjunction with a layer-wise random variable approach. The results obtained by different metamodels have been compared with the results of traditional Monte Carlo simulation (MCS) method for high fidelity uncertainty quantification. The crucial issue regarding influence of sampling techniques on the performance of metamodel based uncertainty quantification has been addressed as an integral part of this article