Engineering model transformations with transML

The final publication is available at Springer via http://dx.doi.org/10.1007%2Fs10270-011-0211-2Model transformation is one of the pillars of model-driven engineering (MDE). The increasing complexity of systems and modelling languages has dramatically raised the complexity and size of model transformations as well. Even though many transformation languages and tools have been proposed in the last few years, most of them are directed to the implementation phase of transformation development. In this way, even though transformations should be built using sound engineering principles—just like any other kind of software—there is currently a lack of cohesive support for the other phases of the transformation development, like requirements, analysis, design and testing. In this paper, we propose a unified family of languages to cover the life cycle of transformation development enabling the engineering of transformations. Moreover, following an MDE approach, we provide tools to partially automate the progressive refinement of models between the different phases and the generation of code for several transformation implementation languages.This work has been sponsored by the Spanish Ministry of Science and Innovation with project METEORIC (TIN2008-02081), and by the R&D program of the Community of Madrid with projects “e-Madrid" (S2009/TIC-1650). Parts of this work were done during the research stays of Esther and Juan at the University of York, with financial support from the Spanish Ministry of Science and Innovation (grant refs. JC2009-00015, PR2009-0019 and PR2008-0185)

Student engagement in the educational interface: understanding the mechanisms of student success

This is an Accepted Manuscript of an article published by Taylor & Francis in Higher Education Research & Development on 2016, available online: https://www.tandfonline.com/doi/full/10.1080/07294360.2017.1344197Publishe

Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose

An evaluation of the role of the Admiral Nurse : a systematic evidence synthesis to inform service delivery and research

Two thirds of people with dementia live in the community and receive support from family members. There is a great deal of evidence to suggest that caring for a person with dementia impacts on the health and wellbeing of family carers. Despite this the provision of funded support for family carers is often limited or inadequate. Admiral Nurses, developed in the 1990s, were specifically designed by the charity for dementia (now Dementia UK) to support the family carers of people with dementia. Admiral Nurses are mental health nurses specialising in the care of people with dementia. They are mainly employed by local providers of care for people with dementia but dementia UK is involved in setting up new posts and providing ongoing practice development. There are currently around 100 Admiral Nurses employed in England. In addition the charity has a national helpline provided by experienced Admiral Nurses. The evidence synthesis presented here was commissioned by Dementia UK in order to establish what is currently known about the scope, nature and effectiveness of Admiral Nurse

Formal Dependability Engineering with MIOA

In this paper, we introduce MIOA, a stochastic process algebra-like specification language with datatypes, as well as a logic intSPDL, and its model checking algorithms. MIOA, which stands for Markovian input/output automata language, is an extension of Lynch's input/automata with Markovian timed transitions.MIOA can serve both as a fully fledged ``stand-alone'' specification language and the semantic model for the architectural dependability modelling and evaluation language Arcade. The logic intSPDL is an extension of the stochastic logic SPDL, to deal with the specialties of MIOA. intSPDL in the context of Arcade can be seen as the semantic model of abstract and complex dependability measures that can be defined in the Arcade framework. We define syntax and semantics of both MIOA and intSPDL, and show examples of applying MIOA and intSPDL in the realm of dependability modelling with Arcade

Rate-Based Transition Systems for Stochastic Process Calculi

A variant of Rate Transition Systems (RTS), proposed by Klin and Sassone, is introduced and used as the basic model for defining stochastic behaviour of processes. The transition relation used in our variant associates to each process, for each action, the set of possible futures paired with a measure indicating their rates. We show how RTS can be used for providing the operational semantics of stochastic extensions of classical formalisms, namely CSP and CCS. We also show that our semantics for stochastic CCS guarantees associativity of parallel composition. Similarly, in contrast with the original definition by Priami, we argue that a semantics for stochastic π-calculus can be provided that guarantees associativity of parallel composition

Efficient and Modular Coalgebraic Partition Refinement

We present a generic partition refinement algorithm that quotients coalgebraic systems by behavioural equivalence, an important task in system analysis and verification. Coalgebraic generality allows us to cover not only classical relational systems but also, e.g. various forms of weighted systems and furthermore to flexibly combine existing system types. Under assumptions on the type functor that allow representing its finite coalgebras in terms of nodes and edges, our algorithm runs in time $\mathcal{O}(m\cdot \log n)$ where $n$ and $m$ are the numbers of nodes and edges, respectively. The generic complexity result and the possibility of combining system types yields a toolbox for efficient partition refinement algorithms. Instances of our generic algorithm match the run-time of the best known algorithms for unlabelled transition systems, Markov chains, deterministic automata (with fixed alphabets), Segala systems, and for color refinement.Comment: Extended journal version of the conference paper arXiv:1705.08362. Beside reorganization of the material, the introductory section 3 is entirely new and the other new section 7 contains new mathematical result

Design thinking and innovation: synthesising concepts of knowledge co-creation in spaces of professional development

This paper explores how design thinking connects to concepts of knowledge creation and innovation. A case study of a knowledge sharing network in the social services sector is used to illustrate how design thinking supports Ba, the spaces for knowledge creation. Further exploration of the four enabling conditions for Ba resulted in delineation of two distinct types: relational and structural. Relational enablers support three groups of enabling conditions: interaction, shared values and communication. It is proposed that design thinking aligns well with relational enabling conditions for Ba to create the ideal spaces for knowledge creation. The group of structural enablers can assist or obstruct change and relate to the culture and management approaches of an organization, which may or may not be assisted by design thinking. However, to ensure that design thinking is not undermined, and innovation is achieved, the presence of an appropriate structural enabler is critical for success