9 research outputs found

    Prototyping the Semantics of a DSL using ASF+SDF: Link to Formal Verification of DSL Models

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    A formal definition of the semantics of a domain-specific language (DSL) is a key prerequisite for the verification of the correctness of models specified using such a DSL and of transformations applied to these models. For this reason, we implemented a prototype of the semantics of a DSL for the specification of systems consisting of concurrent, communicating objects. Using this prototype, models specified in the DSL can be transformed to labeled transition systems (LTS). This approach of transforming models to LTSs allows us to apply existing tools for visualization and verification to models with little or no further effort. The prototype is implemented using the ASF+SDF Meta-Environment, an IDE for the algebraic specification language ASF+SDF, which offers efficient execution of the transformation as well as the ability to read models and produce LTSs without any additional pre or post processing.Comment: In Proceedings AMMSE 2011, arXiv:1106.596

    Scenario-Based Development and Verification of Domain-Specific Languages

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    The use of domain-specific languages (DSLs) has increased manifold for problem solving in specific domain areas as they allow for a wider variety of expressions within their domain. Modeling using DSLs has shown high increases in productivity after accounting for the time and cost expended in developing them, making them a suitable target for improvement in order to reap higher rewards. The currently used approach for domain modeling involves the creation of an ontology which is then used to describe the domain model. This ontology encapsulates all domain knowledge and can be cumbersome to create, requiring external sources of information and assistance from a domain expert. This dissertation first discusses the use and importance of DSLs for scenario generation for a domain and presents an extension to the Aviation Scenario Definition Language (ASDL). The main contribution of this dissertation is a novel framework for scenario based development of DSLs, called the Domain-Specific Scenario (DoSS) framework. This framework proposes the use of scenarios in natural language, which are currently used in requirements engineering and testing, as the basis for developing the domain model iteratively. An example of the use of this approach is provided by developing a domain model for ASDL and comparing the published model with one obtained using DoSS. This approach is supplemented with a case study to validate the claim that DoSS is easier to use by non-experts in the domain by having a user create a model and comparing it to one obtained by the author. These models were found to be almost identical, showing a promising return for this approach. The time taken and effort required to create this model by the user were recorded and found to be quite low, although no similar results have been published so no comparison could be made. State charts are then used for verification of scenarios to ensure the conformity between scenarios and models. The dissertation also discusses applications of the ideas presented here, specifically, the use of ASDL for Air Traffic Control training scenarios and the use of DoSS for ontology generation

    Formal Verification Techniques for Model Transformations: A Tridimensional Classification .

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    Cascading Verification: An Integrated Method for Domain-Specific Model Checking

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    Model checking is an established formal method for verifying the desired behavioral properties of system models. But popular model checkers tend to support low-level modeling languages that require intricate models to represent even the simplest systems. Modeling complexity arises in part from the need to encode domain knowledge, including domain objects and concepts, and their relationships, at relatively low levels of abstraction. We will demonstrate that, once formalized, domain knowledge can be reused to enhance the abstraction level of model and property specifications, and the effectiveness of probabilistic model checking. This thesis describes a novel method for domain-specific model checking called cascading verification. The method uses composite reasoning over high-level system specifications and formalized domain knowledge to synthesize both low-level system models and the behavioral properties that need to be verified with respect to those models. In particular, model builders use a high-level domain-specific language (DSL) to encode system specifications that can be analyzed with model checking. Domain knowledge is encoded in the Web Ontology Language (OWL), the Semantic Web Rule Language (SWRL) and Prolog, which are combined to overcome their individual limitations. Synthesized models and properties are analyzed with the probabilistic model checker PRISM. Cascading verification is illustrated with a prototype system that verifies the correctness of uninhabited aerial vehicle (UAV) mission plans. An evaluation of this prototype reveals non-trivial reductions in the size and complexity of input system specifications compared to the artifacts synthesized for PRISM

    Des spécifications en langage naturel aux spécifications formelles via une ontologie comme modèle pivot

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    Le développement d'un système a pour objectif de répondre à des exigences. Aussi, le succès de sa réalisation repose en grande partie sur la phase de spécification des exigences qui a pour vocation de décrire de manière précise et non ambiguë toutes les caractéristiques du système à développer.Les spécifications d'exigences sont le résultat d'une analyse des besoins faisant intervenir différentes parties. Elles sont généralement rédigées en langage naturel (LN) pour une plus large compréhension, ce qui peut mener à diverses interprétations, car les textes en LN peuvent contenir des ambiguïtés sémantiques ou des informations implicites. Il n'est donc pas aisé de spécifier un ensemble complet et cohérent d'exigences. D'où la nécessité d'une vérification formelle des spécifications résultats.Les spécifications LN ne sont pas considérées comme formelles et ne permettent pas l'application directe de méthodes vérification formelles.Ce constat mène à la nécessité de transformer les spécifications LN en spécifications formelles.C'est dans ce contexte que s'inscrit cette thèse.La difficulté principale d'une telle transformation réside dans l'ampleur du fossé entre spécifications LN et spécifications formelles.L'objectif de mon travail de thèse est de proposer une approche permettant de vérifier automatiquement des spécifications d'exigences utilisateur, écrites en langage naturel et décrivant le comportement d'un système.Pour cela, nous avons exploré les possibilités offertes par un modèle de représentation fondé sur un formalisme logique.Nos contributions portent essentiellement sur trois propositions :1) une ontologie en OWL-DL fondée sur les logiques de description, comme modèle de représentation pivot permettant de faire le lien entre spécifications en langage naturel et spécifications formelles; 2) une approche d'instanciation du modèle de représentation pivot, fondée sur une analyse dirigée par la sémantique de l'ontologie, permettant de passer automatiquement des spécifications en langage naturel à leur représentation conceptuelle; et 3) une approche exploitant le formalisme logique de l'ontologie, pour permettre un passage automatique du modèle de représentation pivot vers un langage de spécifications formelles nommé Maude.The main objective of system development is to address requirements. As such, success in its realisation is highly dependent on a requirement specification phase which aims to describe precisely and unambiguously all the characteristics of the system that should be developed. In order to arrive at a set of requirements, a user needs analysis is carried out which involves different parties (stakeholders). The system requirements are generally written in natural language to garantuee a wider understanding. However, since NL texts can contain semantic ambiguities, implicit information, or other inconsistenties, this can lead to diverse interpretations. Hence, it is not easy to specify a set of complete and consistent requirements, and therefore, the specified requirements must be formally checked. Specifications written in NL are not considered to be formal and do not allow for a direct application of formal methods. We must therefore transform NL requirements into formal specifications. The work presented in this thesis was carried out in this framework. The main difficulty of such transformation is the gap between NL requirements and formal specifications. The objective of this work is to propose an approach for an automatic verification of user requirements which are written in natural language and describe a system's expected behaviour. Our approach uses the potential offered by a representation model based on a logical formalism. Our contribution has three main aspects: 1) an OWL-DL ontology based on description logic, used as a pivot representation model that serves as a link between NL requirements to formal specifications; 2) an approach for the instantiation of the pivot ontology, which allows an automatic transformation of NL requirements to their conceptual representations; and 3) an approach exploiting the logical formalism of the ontology in order to automatically translate the ontology into a formal specification language called Maude.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

    Towards the Formal Verification of Model Transformations: An Application to Kermeta

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    Model-Driven Engineering (MDE) is becoming a popular engineering methodology for developing large-scale software applications, using models and transformations as primary principles. MDE is now being successfully applied to domain-specific languages (DSLs), which target a narrow subject domain like process management, telecommunication, product lines, smartphone applications among others, providing experts high-level and intuitive notations very close to their problem domain. More recently, MDE has been applied to safety-critical applications, where failure may have dramatic consequences, either in terms of economic, ecologic or human losses. These recent application domains call for more robust and more practical approaches for ensuring the correctness of models and model transformations. Testing is the most common technique used in MDE for ensuring the correctness of model transformations, a recurrent, yet unsolved problem in MDE. But testing suffers from the so-called coverage problem, which is unacceptable when safety is at stake. Rather, exhaustive coverage is required in this application domain, which means that transformation designers need to use formal analysis methods and tools to meet this requirement. Unfortunately, two factors seem to limit the use of such methods in an engineer’s daily life. First, a methodological factor, because MDE engineers rarely possess the effective knowledge for deploying formal analysis techniques in their daily life developments. Second, a practical factor, because DSLs do not necessarily have a formal explicit semantics, which is a necessary enabler for exhaustive analysis. In this thesis, we contribute to the problem of formal analysis of model transformations regarding each perspective. On the conceptual side, we propose a methodological framework for engineering verified model transformations based on current best practices. For that purpose, we identify three important dimensions: (i) the transformation being built; (ii) the properties of interest ensuring the transformation’s correctness; and finally, (iii) the verification technique that allows proving these properties with minimal effort. Finding which techniques are better suited for which kind of properties is the concern of the Computer-Aided Verification community. Consequently in this thesis, we focus on studying the relationship between transformations and properties. Our methodological framework introduces two novel notions. A transformation intent gathers all transformations sharing the same purpose, abstracting from the way the transformation is expressed. A property class captures under the same denomination all properties sharing the same form, abstracting away from their underlying property languages. The framework consists of mapping each intent with its characteristic set of property classes, meaning that for proving the correctness of a particular transformation obeying this intent, one has to prove properties of these specific classes. We illustrate the use and utility of our framework through the detailed description of five common intents in MDE, and their application to a case study drawn from the automative software domain, consisting of a chain of more than thirty transformations. On a more practical side, we study the problem of verifying DSLs whose behaviour is expressed with Kermeta. Kermeta is an object-oriented transformation framework aligned with Object Management Group standard specification MOF (Meta-Object Facility). It can be used for defining metamodels and models, as well as their behaviour. Kermeta lacks a formal semantics: we first specify such a semantics, and then choose an appropriate verification domain for handling the analysis one is interested in. Since the semantics is defined at the level of Kermeta’s transformation language itself, our work presents two interesting features: first, any DSL whose behaviour is defined using Kermeta (more precisely, any transformation defined with Kermeta) enjoys a de facto formal underground for free; second, it is easier to define appropriate abstractions for targeting specific analysis for this full-fledged semantics than defining specific semantics for each possible kind of analysis. To illustrate this point, we have selected Maude, a powerful rewriting system based on algebraic specifications equipped with model-checking and theorem-proving capabilities. Maude was chosen because its underlying formalism is close to the mathematical tools we use for specifying the formal semantics, reducing the implementation gap and consequently limiting the possible implementation mistakes. We validate our approach by illustrating behavioural properties of small, yet representative DSLs from the literature
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