Reactive Model Transformation with ATL

International audienceModel-driven applications may maintain large networks of structured data models and transformations among them. The development of such applications is complicated by the need to reflect on the whole network any runtime update performed on models or transformation logic. If not carefully designed, the execution of such updates may be computationally expensive. In this paper we propose a reactive paradigm for programming model transformations, and we implement a reactive model-transformation engine. We argue that this paradigm facilitates the development of autonomous model-driven systems that react to update and request events from the host application by identifying and performing only the needed computation. We implement such approach by providing a reactive engine for the ATL transformation language. We evaluate the usage scenarios that this paradigm supports and we experimentally measure its ability to reduce computation time in transformation-based applications

Modularity and Openness in Modeling Multi-Agent Systems

We revisit the formalism of modular interpreted systems (MIS) which encourages modular and open modeling of synchronous multi-agent systems. The original formulation of MIS did not live entirely up to its promise. In this paper, we propose how to improve modularity and openness of MIS by changing the structure of interference functions. These relatively small changes allow for surprisingly high flexibility when modeling actual multi-agent systems. We demonstrate this on two well-known examples, namely the trains, tunnel and controller, and the dining cryptographers. Perhaps more importantly, we propose how the notions of multi-agency and openness, crucial for multi-agent systems, can be precisely defined based on their MIS representations.Comment: In Proceedings GandALF 2013, arXiv:1307.416

Weaving Rules into [email protected] for Embedded Smart Systems

Smart systems are characterised by their ability to analyse measured data in live and to react to changes according to expert rules. Therefore, such systems exploit appropriate data models together with actions, triggered by domain-related conditions. The challenge at hand is that smart systems usually need to process thousands of updates to detect which rules need to be triggered, often even on restricted hardware like a Raspberry Pi. Despite various approaches have been investigated to efficiently check conditions on data models, they either assume to fit into main memory or rely on high latency persistence storage systems that severely damage the reactivity of smart systems. To tackle this challenge, we propose a novel composition process, which weaves executable rules into a data model with lazy loading abilities. We quantitatively show, on a smart building case study, that our approach can handle, at low latency, big sets of rules on top of large-scale data models on restricted hardware.Comment: pre-print version, published in the proceedings of MOMO-17 Worksho

Role-based Runtime Model Synchronization

Model-driven Software Development (MDSD) promotes the use of multiple related models to realize a software system systematically. These models usually contain redundant information but are independently edited. This easily leads to inconsistencies among them. To ensure consistency among multiple models, model synchronizations have to be employed, e.g., by means of model transformations, trace links, or triple graph grammars. Model synchronization poses three main problems for MDSD. First, classical model synchronization approaches have to be manually triggered to perform the synchronization. However, to support the consistent evolution of multiple models, it is necessary to immediately and continuously update all of them. Second, synchronization rules are specified at design time and, in classic approaches, cannot be extended at runtime, which is necessary if metamodels evolve at runtime. Finally, most classical synchronization approaches focus on bilateral model synchronization, i.e., the synchronization between two models. Consequently, for more than two models, they require the definition of pairwise model synchronizations leading to a combinatorial explosion of synchronization rules. To remedy these issues, we propose a role-based approach for runtime model synchronization. In particular, we propose role-based synchronization rules that enable the immediate and continuous propagation of changes to multiple interrelated models (and back again). Additionally, our approach permits adding new and customized synchronization rules at runtime. We illustrate the benefits of role-based runtime model synchronization using the Families to Persons case study from the Transformation Tool Contest 2017

Feature-Oriented Modelling Using Event-B

Event-B is a formal method for specification and verification of reactive systems. Its Rodin toolkit provides comprehensive support for modelling, refinement and analysis using theorem proving, animation and model checking. There has always been a need to reuse existing models and their associated proofs when modelling related systems to save time and effort. Software product lines (SPLs) focus on the problem of reuse by providing ways to build software products having commonalities and managing variations within products of the same family. Feature modelling is a well know technique to manage variability and configure products within the SPLs. We have combined the two approaches to formally specify SPLs using Event-B. This will contribute the concept of formalism to SPLs and re-usability to Event-B. Existing feature modelling notations were adapted and extended to include refinement mechanism of Event-B. An Eclipse-based graphical feature modelling tool has been developed as a plug-in to the Rodin platform. We have modelled the "production cell" case-study in Event-B, an industrial metal processing plant, which has previously been specified in a number of formalisms. We have also highlighted future directions based on our experience with this framework so far

Allen Linear (Interval) Temporal Logic --Translation to LTL and Monitor Synthesis--

The relationship between two well established formalisms for temporal reasoning is first investigated, namely between Allen's interval algebra (or Allen's temporal logic, abbreviated \ATL) and linear temporal logic (\LTL). A discrete variant of \ATL is defined, called Allen linear temporal logic (\ALTL), whose models are \omega-sequences of timepoints, like in \LTL. It is shown that any \ALTL formula can be linearly translated into an equivalent \LTL formula, thus enabling the use of \LTL techniques and tools when requirements are expressed in \ALTL. %This translation also implies the NP-completeness of \ATL satisfiability. Then the monitoring problem for \ALTL is discussed, showing that it is NP-complete despite the fact that the similar problem for \LTL is EXPSPACE-complete. An effective monitoring algorithm for \ALTL is given, which has been implemented and experimented with in the context of planning applications

Timing diagrams add Requirements Engineering capability to Event-B Formal Development

Event-B is a language for the formal development of reactive systems. At present the RODIN toolkit [15] for Event-B is used for modeling requirements, specifying refinements and doing verification. In order to extend graphical requirements modeling capability into the real-time domain, where timing constraints are essential, we propose a Timing diagram (TD) [13] notation for Event-B. The UML 2.0 based notation provides an intuitive graphical specification capability for timing constraints and causal dependencies between system events. A translation scheme to Event-B is proposed and presented. Support for model refinement is provided. A partial case study is used to demonstrate the translation in practice

MONDO : Scalable modelling and model management on the Cloud

Achieving scalability in modelling and MDE involves being able to construct large models and domain-specific languages in a systematic manner, enabling teams of modellers to construct and refine large models in collaboration, advancing the state of the art in model querying and transformations tools so that they can cope with large models (of the scale of millions of model elements), and providing an infrastructure for efficient storage, indexing and retrieval of large models. This paper outlines how MONDO, a collaborative EC-funded project, has contributed to tackling some of these scalability-related challenges

Our digital children

The power relationship between adults and children in the West is shifting. Factors of age and life experience are becoming counterbalanced by children’s affinity for burgeoning developments in digital technology, where skills developed in online gaming and social media provide a strong foundation for knowledge economy occupations. The implications for parenting, schooling and society are immense. This paper summarises the current debate on issues around children’s use of digital devices and social media. It argues that for many parents a lack of familiarity and understanding creates anxieties and impairs them from helping their children realise the opportunities for social, moral and economic development afforded by the new technologies. Schools have a leading role to play but are hampered by teachers’ technical skills and confidence to innovate. The paper concludes with recommendations for a proactive approach to yield benefits for both children and adults