Abstracting modelling languages: A reutilization approach

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-31095-9_9Proceedings of 24th International Conference, CAiSE 2012, Gdansk, Poland, June 25-29, 2012Model-Driven Engineering automates the development of information systems. This approach is based on the use of Domain-Specific Modelling Languages (DSMLs) for the description of the relevant aspects of the systems to be built. The increasing complexity of the target systems has raised the need for abstraction techniques able to produce simpler versions of the models, but retaining certain properties of interest. However, developing such abstractions for each DSML from scratch is a time and resource consuming activity. Our solution to this situation is a number of techniques to build reusable abstractions that are defined once and can be reused over families of modelling languages sharing certain requirements. As a proof of concept, we present a catalogue of reusable abstractions, together with an implementation in the MetaDepth multi-level meta-modelling tool.Work funded by the Spanish Ministry of Economy and Competitivity (TIN2011-24139), and the R&D programme of Madrid Region (S2009/TIC-1650)

Many-objective test suite generation for software product lines

A Software Product Line (SPL) is a set of products built from a number of features, the set of valid products being defined by a feature model. Typically, it does not make sense to test all products defined by an SPL and one instead chooses a set of products to test (test selection) and, ideally, derives a good order in which to test them (test prioritisation). Since one cannot know in advance which products will reveal faults, test selection and prioritisation are normally based on objective functions that are known to relate to likely effectiveness or cost. This paper introduces a new technique, the grid-based evolution strategy (GrES), which considers several objective functions that assess a selection or prioritisation and aims to optimise on all of these. The problem is thus a many-objective optimisation problem. We use a new approach, in which all of the objective functions are considered but one (pairwise coverage) is seen as the most important. We also derive a novel evolution strategy based on domain knowledge. The results of the evaluation, on randomly generated and realistic feature models, were promising, with GrES outperforming previously proposed techniques and a range of many-objective optimisation algorithms

Investigating business process elements: a journey from the field of Business Process Management to ontological analysis, and back

Business process modelling languages (BPMLs) typically enable the representation of business processes via the creation of process models, which are constructed using the elements and graphical symbols of the BPML itself. Despite the wide literature on business process modelling languages, on the comparison between graphical components of different languages, on the development and enrichment of new and existing notations, and the numerous definitions of what a business process is, the BPM community still lacks a robust (ontological) characterisation of the elements involved in business process models and, even more importantly, of the very notion of business process. While some efforts have been done towards this direction, the majority of works in this area focuses on the analysis of the behavioural (control flow) aspects of process models only, thus neglecting other central modelling elements, such as those denoting process participants (e.g., data objects, actors), relationships among activities, goals, values, and so on. The overall purpose of this PhD thesis is to provide a systematic study of the elements that constitute a business process, based on ontological analysis, and to apply these results back to the Business Process Management field. The major contributions that were achieved in pursuing our overall purpose are: (i) a first comprehensive and systematic investigation of what constitutes a business process meta-model in literature, and a definition of what we call a literature-based business process meta-model starting from the different business process meta-models proposed in the literature; (ii) the ontological analysis of four business process elements (event, participant, relationship among activities, and goal), which were identified as missing or problematic in the literature and in the literature-based meta-model; (iii) the revision of the literature-based business process meta-model that incorporates the analysis of the four investigated business process elements - event, participant, relationship among activities and goal; and (iv) the definition and evaluation of a notation that enriches the relationships between activities by including the notions of occurrence dependences and rationales

Linguistic Refactoring of Business Process Models

In the past decades, organizations had to face numerous challenges due to intensifying globalization and internationalization, shorter innovation cycles and growing IT support for business. Business process management is seen as a comprehensive approach to align business strategy, organization, controlling, and business activities to react flexibly to market changes. For this purpose, business process models are increasingly utilized to document and redesign relevant parts of the organization's business operations. Since companies tend to have a growing number of business process models stored in a process model repository, analysis techniques are required that assess the quality of these process models in an automatic fashion. While available techniques can easily check the formal content of a process model, there are only a few techniques available that analyze the natural language content of a process model. Therefore, techniques are required that address linguistic issues caused by the actual use of natural language. In order to close this gap, this doctoral thesis explicitly targets inconsistencies caused by natural language and investigates the potential of automatically detecting and resolving them under a linguistic perspective. In particular, this doctoral thesis provides the following contributions. First, it defines a classification framework that structures existing work on process model analysis and refactoring. Second, it introduces the notion of atomicity, which implements a strict consistency condition between the formal content and the textual content of a process model. Based on an explorative investigation, we reveal several reoccurring violation patterns are not compliant with the notion of atomicity. Third, this thesis proposes an automatic refactoring technique that formalizes the identified patterns to transform a non-atomic process models into an atomic one. Fourth, this thesis defines an automatic technique for detecting and refactoring synonyms and homonyms in process models, which is eventually useful to unify the terminology used in an organization. Fifth and finally, this thesis proposes a recommendation-based refactoring approach that addresses process models suffering from incompleteness and leading to several possible interpretations. The efficiency and usefulness of the proposed techniques is further evaluated by real-world process model repositories from various industries. (author's abstract