BigraphER: rewriting and analysis engine for bigraphs

BigraphER is a suite of open-source tools providing an effi- cient implementation of rewriting, simulation, and visualisation for bigraphs, a universal formalism for modelling interacting systems that evolve in time and space and first introduced by Milner. BigraphER consists of an OCaml library that provides programming interfaces for the manipulation of bigraphs, their constituents and reaction rules, and a command-line tool capable of simulating Bigraphical Reactive Systems (BRSs) and computing their transition systems. Other features are native support for both bigraphs and bigraphs with sharing, stochastic reaction rules, rule priorities, instantiation maps, parameterised controls, predicate checking, graphical output and integration with the probabilistic model checker PRISM

Constructing runtime models with bigraphs to address ubiquitous computing service composition volatility

In this thesis, we explore the appropriateness of the language abstractions provided by Bigraphs to construct a model at runtime to tackle the problem of volatility in a service composition running on a mobile device. Our contributions to knowledge are as follows: 1) We have shown that Bigraphs (Milner, 2009) are suitable for expressing models at runtime. 2) We have offered Bigraph language abstractions as an appropriate solution to some of the research problems posed by the models at runtime community (Aßmann et al., 2012). 3) We have discussed the general lessons learnt from using Bigraphs for a practical application such as a model at runtime. 4) We have discussed the general lessons learnt from our experiences of designing models at runtime. 5) We have implemented the model at runtime using the BPL Tool (ITU, 2011) and have experimentally studied the response times of our Bigraphical model. We have suggested appropriate enhancements for the tool based on our experiences. We present techniques to parameterize the reaction rules so that the matching algorithm of the BPL Tool returns a single match giving us the ability to dynamically program the model at runtime. We also show how to query the Bigraph structure

Formal verification of the extension of iStar to support Big data projects

Identifying all the right requirements is indispensable for the success of anysystem. These requirements need to be engineered with precision in the earlyphases. Principally, late corrections costs are estimated to be more than 200times as much as corrections during requirements engineering (RE). EspeciallyBig data area, it becomes more and more crucial due to its importance andcharacteristics. In fact, and after literature analyzing, we note that currentsRE methods do not support the elicitation of Big data projects requirements. Inthis study, we propose the BiStar novel method as extension of iStar to under-take some Big data characteristics such as (volume, variety ...etc). As a firststep, we identify some missing concepts that currents requirements engineeringmethods do not support. Next, BiStar, an extension of iStar is developed totake into account Big data specifics characteristics while dealing with require-ments. In order to ensure the integrity property of BiStar, formal proofs weremade, we perform a bigraph based description on iStar and BiStar. Finally, anapplication is conducted on iStar and BiStar for the same illustrative scenario.The BiStar shows important results to be more suitable for eliciting Big dataprojects requirements

Computing (optimal) embeddings of directed bigraphs

Bigraphs and bigraphical reactive systems are a well-known meta-model successfully used for formalizing a wide range of models and situations, such as process calculi, service oriented architectures, multi-agent systems, biological systems, etc. A key problem in the theory and the implementations of bigraphs is how to compute embeddings, i.e., structure-preserving mappings of a given bigraph (the pattern or guest) inside another (the target or host). In this paper, we present an algorithm for computing embeddings for directed bigraphs, an extension of Milner's bigraphs which take into account the request directions between controls and names. This algorithm solves the embedding problem by means of a reduction to a constraint satisfaction problem. We first prove soundness and completeness of this algorithm; then we present an implementation in jLibBig, a general Java library for manipulating bigraphical reactive systems. The effectiveness of this implementation is shown by several experimental results. Finally, we show that this algorithm can be readily adapted to find the optimal embeddings in a weighted variant of the embedding problem

Matching of Bigraphs

We analyze the matching problem for bigraphs. In particular, we present a sound and complete inductive characterization of matching of binding bigraphs. Our results pave the way for a provably correct matching algorithm, as needed for an implementation of bigraphical reactive systems

Un Framework Basé Bigraphes pour la Conception et l'Analyse des Systèmes Sensibles au Contexte

Today, modern technologies have become a part of our daily life. Whether to be informed, entertained, or even to communicate with friends, ubiquitous computing offers numerous opportunities. For this to become reality, computer systems must be able to observe the environment and to adapt their behaviour according to the users expectations and needs. This is called context-awareness. Indeed, the literature shows that context-awareness is the focal point of ubiquitous computing. However, due to heterogeneity and dynamicity of context information, taking it into account requires establishing a model to represent these information at a high-level of abstraction.In this thesis, we propose a model called BigCAS (Bigraphical Context-Aware System) that supports the design of context-aware systems. To achieve this goal, BigCAS is based on formal specifications, derived from bigraphical reactive systems, for modelling structural and behavioural aspects of context aware systems. It provides a clear separation between the context-aware part and the context-unaware part of these systems. Each part is modelled separately as a distinct bigraph, where the composition of these bigraphs models the general structure of the system, particularly, its components interactions and their side effects. Moreover, BigCAS considers not only structural aspects, but also the different reconfigurations involved in the behaviour of context aware systems.We also propose an extension to BigCAS, named BigCAS-FA (Bigraphical Context-Aware System - Formal Analysis), that provides formal verification of safety and liveness properties of context aware systems. Furthermore, BigCAS-FA provides contract-based strategies to guide the dynamic reconfiguration according to the context.To validate our proposals, we develop a prototype, BigCAS-Tool (Bigraphical Context Aware System - Tool), devoted to the specification and verification of context-aware systems. The proposed prototype is illustrated with a case study of a smart lighting system.Aujourd'hui, les nouvelles technologies font partie de notre vie quotidienne. Qu'il s'agisse de s'informer, de se divertir, ou même de communiquer avec ses amis, les possibilités qu'offre l'informatique ubiquitaire sont innombrables.Pour que ces possibilités puissent devenir une réalité, les systèmes informatiques doivent alors se doter d'une capacité d'observation de leur environnement et de s'adapter en fonction des attentes et des besoins des utilisateurs. C'est ce qu'on appelle la sensibilité au contexte. En effet, la littérature montre que la sensibilité au contexte est le point central de l'informatique ubiquitaire. Cependant, face à l'hétérogénéité et la dynamicité des informations de contexte, sa prise en compte nécessite la mise en place d'un modèle pour décrire ces informations à un haut niveau d'abstraction.Dans ce travail de thèse nous proposons, dans un premier temps, un modèle appelé BigCAS (Bigraphical Contexte-Aware System) qui permet la conception formelle des systèmes sensibles au contexte. Pour accomplir cet objectif, BigCAS repose sur des modèles formelles à base des systèmes réactifs bigraphiques permettant la modélisation des aspects structurels et comportementaux des systèmes sensibles au contexte. Il offre une séparation claire entre la partie sensible au contexte et la partie non-sensible au contexte de ces systèmes. Chacune de ces parties est modélisée séparément par un bigraphe distinct, où la composition de ceux-ci modélise la structure générale du système ainsi que les interactions et les effets de bord entre ses différents composants. Par ailleurs, BigCAS tient compte non seulement des aspects structurels, mais aussi des différentes reconfigurations intervenant dans le comportement des systèmes sensibles au contexte.Nous proposons également une extension du modèle BigCAS, appelée BigCAS-FA (Bigraphical Context-Aware System - Formal Analysis), qui permet la vérification formelle de propriétés de sûreté et de vivacité des systèmes sensibles au contexte. En outre, BigCAS-FA possède des stratégies à base de contrats qui consistent à guider la reconfiguration dynamique en fonction du contexte.Afin de valider nos propositions, nous développons le prototype BigCAS-Tool (Bigraphical Context Aware System - Tool) dédié à la spécification et la vérification des systèmes sensibles au contexte, et nous l'illustrons à travers une étude de cas d'un système d'éclairage intelligent