Tihamer Levendovszky

Model Reuse with Metamodel-Based Transformations

Metamodel-based transformations permit descriptions of mappings between models created using different concepts from possibly overlapping domains. This paper describes the basic algorithms used in matching metamodel constructs, and how this match is to be applied. The transformation process facilitates the reuse of models specified in one domain-specific modeling language in another context: another domain-specific modeling language. UML class diagrams are used as the language of the metamodels. The focus of the paper is on the matching and firing of transformation rules, and on finding efficient and generic algorithms. An illustrative case study is provided.

Automatic Domain Model Migration to Manage Metamodel Evolution

Metamodel evolution is a significant problem in domain specific software development for several reasons. Domain-specific modeling languages (DSMLs) are likely to evolve much more frequently than programming languages and commonly used software formalisms, often resulting in a large number of valuable instance models that are no longer compliant with the metamodel. In this paper, we present the Model Change Language (MCL), aimed at satisfying these requirements.

Reasoning about metamodeling with formal specifications and automatic proofs

Metamodeling is foundational to many modeling frameworks, and so it is important to formalize and reason about it. Ideally, correctness proofs and test-case generation on the metamodeling framework should be automatic. However, it has yet to be shown that extensive automated reasoning on metamodeling frameworks can be achieved. In this paper we present one approach to this problem: Metamodeling frameworks are specified modularly using algebraic data types and constraint logic programming (CLP). Proofs and test-case generation are encoded as CLP satisfiability problems and automatically solved.

A novel approach to semi-automated evolution of DSML model transformation

In the industrial applications of Model-Based Development, the evolution of modeling languages is an inevitable issue. The migration to the new language involves the reuse of the existing artifacts created for the original language, such as models and model transformations. This paper is devoted to an evolution method for model transformations as well as the related algorithms. The change description is assumed to be available in a modeling language specific to the evolution. Based on the change description, our method is able to automate certain parts of the evolution. When automation is not possible, our algorithms automatically alert the user about the missing semantic information, which can then be provided manually after the automatic part of the interpreter evolution. The algorithms have been implemented and tested in an industrial environment. The results indicate that the semi-automated evolution of model transformations decreases the time and effort required with a manual approach.

Supporting domain-specific model patterns with metamodeling

Metamodeling is a widely applied technique in the field of graphical languages to create highly configurable modeling environments. These environments support the rapid development of domain-specific modeling languages (DSMLs). Design patterns are efficient solutions for recurring problems. With the proliferation of DSMLs, there is a need for domain-specific design patterns to offer solutions to problems recurring in different domains. The aim of this paper is to provide theoretical and practical foundations to support domain-specific model patterns in metamodeling environments. In order to support the treatment of premature model parts, we weaken the instantiation relationship. We provide constructs relaxing the instantiation rules, and we show that these constructs are appropriate and sufficient to express patterns. We provide the necessary modifications in metamodeling tools for supporting patterns. With the contributed results, a well-founded domain-specific model pattern support can be realized in metamodeling tools.

Foundation for Model Integration: Semantic Backplane

One of the primary goals of the Adaptive Vehicle Make (AVM) program of DARPA is the construction of a model-based design flow and tool chain, META, that will provide significant productivity increase in the development of complex cyber-physical systems. In model-based design, modeling languages and their underlying semantics play fundamental role in achieving compositionality. A significant challenge in the META design flow is the heterogeneity of the design space. This challenge is compounded by the need for rapidly evolving the design flow and the suite of modeling languages supporting it. Heterogeneity of models and modeling languages is addressed by the development of a model integration language – CyPhy – supporting constructs needed for modeling the interactions among different modeling domains. CyPhy targets simplicity: only those abstractions are imported from the individual modeling domains to CyPhy that are required for expressing relationships across sub-domains. This “semantic interface” between CyPhy and the modeling domains is formally defined, evolved as needed and verified for essential properties (such as well-formedness and invariance). Due to the need for rapid evolvability, defining semantics for CyPhy is not a “one-shot” activity; updates, revisions and extensions are ongoing and their correctness has significant implications on the overall consistency of the META tool chain. The focus of this paper is the methods and tools used for this purpose: the META Semantic Backplane. The Semantic Backplane is based on a mathematical framework provided by term algebra and logics, incorporates a tool suite for specifying, validating and using formal structural and behavioral semantics of modeling languages, and includes a library of metamodels and specifications of model transformations.Copyright

Towards a theory for cyber-physical systems modeling

Modeling the heterogeneous composition of physical, computational and communication systems is an important challenge in engineering Cyber-Physical Systems (CPS), where the major sources of heterogeneity are causality, time semantics, and different physical domains. Classical physical laws capture acausal continuous-time dynamics, thus the behavior of physical systems are inherently characterized by acausal continuous-time equations. On the other hand, computational and communication systems are based on the notion of causality and discrete-time semantics. Connecting the two worlds is challenging, and calls for proper formalization of the composition. In this paper, we discuss a formalism that captures both acausal physical laws, unidirectional analog signals, and is capable of describing causal computational systems, as well as the composition of CPS models.

Specification of Cyber-Physical Components with Formal Semantics --- Integration and Composition

Model-Based Engineering of Cyber-Physical Systems CPS needs correct-by-construction design methodologies, hence CPS modeling languages require mathematically rigorous, unambiguous, and sound specifications of their semantics. The main challenge is the formalization of the heterogeneous composition and interactions of CPS systems. Creating modeling languages that support both the acausal and causal modeling approaches, and which has well-defined and sound behavior across the heterogeneous time domains is a challenging task. In this paper, we discuss the difficulties and as an example develop the formal semantics of a CPS-specific modeling language called CyPhyML. We formalize the structural semantics of CyPhyML by means of constraint rules and its behavioral semantics by defining a semantic mapping to a language for differential algebraic equations. The specification language is based on an executable subset of first-order logic, which facilitates model conformance checking, model checking and model synthesis.

9 Model Evolution and Management

As complex software and systems development projects need models as an important planning, structuring and development technique, models now face issues resolved for software earlier: models need to be versioned, differences captured, syntactic and semantic correctness checked as early as possible, documented, presented in easily accessible forms, etc. Quality management needs to be established for models as well as their relationship to other models, to code and to requirement documents precisely clarified and tracked. Business and product requirements, product technologies as well as development tools evolve. This also means we need evolutionary technologies both for models within a language and if the language evolves also for an upgrade of the models. This chapter discusses the state of the art in model management and evolution and sketches what is still necessary for models to become as usable and used as software.

A transformation instance-based approach to traceability

Although traceability is often a suggested requirement for general software development, there are areas such as airborne systems, where traceability is a compulsory part of the development process. This paper describes a tool chain that is able to generate and to follow traceability links across model-to-model and model-to-code transformations, and capable of providing navigability support along these traceability links. We elaborate on the conceptual design of our tool chain and provide details on its realization in a DSML environment underpinned by graph rewriting-based model transformation.