Ethan K. Jackson

Semantic anchoring with model transformations

Model-Integrated Computing (MIC) is an approach to Model-Driven Architecture (MDA), which has been developed primarily for embedded systems. MIC places strong emphasis on the use of domain-specific modeling languages (DSML-s) and model transformations. A metamodeling process facilitated by the Generic Modeling Environment (GME) tool suite enables the rapid and inexpensive development of DSML-s. However, the specification of semantics for DSML-s is still a hard problem. In order to simplify the DSML semantics, this paper discusses semantic anchoring, which is based on the transformational specification of semantics. Using a mathematical model, Abstract State Machine (ASM), as a common semantic framework, we have developed formal operational semantics for a set of basic models of computations, called semantic units. Semantic anchoring of DSML-s means the specification of model transformations between DSML-s (or aspects of complex DSML-s) and selected semantic units. The paper describes the semantic anchoring process using the meta-programmable MIC tool suite.

Formalizing the structural semantics of domain-specific modeling languages

Model-based approaches to system design are now widespread and successful. These approaches make extensive use of model structure to describe systems using domain-specific abstractions, to specify and implement model transformations, and to analyze structural properties of models. In spite of its general importance the structural semantics of modeling languages are not well-understood. In this paper we develop the formal foundations for the structural semantics of domain-specific modeling languages (DSML), including the mechanisms by which metamodels specify the structural semantics of DSMLs. Additionally, we show how our formalization can complement existing tools, and how it yields algorithms for the analysis of DSMLs and model transformations.

Components, platforms and possibilities: towards generic automation for MDA

Model-driven architecture (MDA) is a model-based approach for engineering complex software systems. MDA is particularly attractive for designing embedded systems because models can be easily evolved as hardware and software requirements evolve. However, efforts to apply MDA in industrial settings expose several open problems surrounding tooling: Engineers need automated techniques that are scalable, general, and extensible. In this paper we describe the formula framework as a novel approach towards general automation for MDA. We develop a running example and benchmarks to compare our tools with other state-of-theart approaches.

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.

An approach for effective design space exploration

Design space exploration (DSE) refers to the activity of exploring design alternatives prior to implementation. The power to operate on the space of potential design candidates renders DSE useful for many engineering tasks, including rapid prototyping, optimization, and system integration. The main challenge in DSE arises from the sheer size of the design space that must be explored. Typically, a large system has millions, if not billions, of possibilities, and so enumerating every point in the design space is prohibitive. In this paper, we present a method for systematically exploring the design space in a cost-effective manner. The key idea is that many of the design candidates may be considered equivalent as far as the user is concerned, and so only a small subset of the space needs to be explored. Our approach takes the user-defined notion of equivalence, and generates symmetry breaking predicates to ensure that the underlying exploration engine does not sample multiple equivalent design candidates. We describe how the method is integrated into our DSE framework, FORMULA, which uses an SMT solver to solve a set of global design constraints and search for valid design instances.

Towards a formal foundation for domain specific modeling languages

Embedded system design is inherently domain specific and typically model driven.As a result, design methodologies like OMGs model driven architecture (MDA)and model integrated computing (MIC)evolved to support domain specific modeling language(DSMLs). The success of the DSML approach has encouraged work on the heterogeneous composition of DSMLs, model transformations between DSMLs, approximations of formal properties within DSMLs, and reuse of DSML semantics. However, in the effort to produce a mature design approach that can handle both the structural and behavioral semantics of embedded system design,many foundational issues concerning DSMLs have been overlooked. In this paper we present a formal foundation for DSMLs and for their construction within metamodeling frameworks. This foundation allows us to algorithmically decide if two DSMLs or metamodels are equivalent, if model transformations preserve properties, and if metamodeling frameworks have metametamodels. These results are key to building correct embedded systems with DSMLs.

OpenMETA: A Model- and Component-Based Design Tool Chain for Cyber-Physical Systems

Model- and component-based design have yielded dramatic increase in design productivity in several narrowly focused homogeneous domains, such as signal processing, control and aspects of electronic design. However, significant impact on the design and manufacturing of complex cyber-physical systems (CPS) such as vehicles has not yet been achieved. This paper describes challenges of and solution approaches to building a comprehensive design tool suite for complex CPS. The primary driver for the OpenMETA tool chain was to push the boundaries of the “correct-by-construction” principle to decrease significantly the costly design-build-test-redesign cycles in design flows. In the discussions we will focus on the impact of heterogeneity in modeling CPS. This challenge is compounded by the need for rapidly evolving the design flow by changing/updating the selection of modeling languages, analysis and verification tools and synthesis methods. Based on our experience with the development of OpenMETA and with the evaluation of its performance in a complex CPS design challenge we argue that the current vertically integrated, discipline-specific tool chains for CPS design need to be complemented with horizontal integration layers that support model integration, tool integration and design process integration. This paper will examine the OpenMETA technical approach to construct the new integration layers, provides and overview of the technical framework we established for their implementation and summarize our experience with their application.

Specifying and Composing Non-functional Requirements in Model-Based Development

Non-functional requirements encompass important design concerns such as schedulability, security, and communication constraints. In model-based development they non-locally impact admissible platform-mappings and design spaces. In this paper we present a novel and formal approach for specifying non-functional requirements as con straint-systems over the space of models. Our approach, based on structured logic programming, allows interacting requirements to be specified independently from each other and composed together. Correct-by- construction operators eliminate some composition mistakes. Our approach is implemented in our formal modeling tool FORMULA , which can analyze the impacts of interacting non-functional requirements on platform mappings and design spaces.

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

Model Generation for Horn Logic with Stratified Negation

Model generation is an important formal technique for finding interesting instances of computationally hard problems. In this paper we study model generation over Horn logic under the closed world assumption extended with stratified negation. We provide a novel three-stage algorithm that solves this problem: First, we reduce the relevant Horn clauses to a set of non-monotonic predicates. Second, we apply a fixed-point procedure to these predicates that reveals candidate solutions to the model generation problem. Third, we encode these candidates into a satisfiability problem that is evaluated with a state-of-the-art SMT solver. Our algorithm is implemented, and has been successfully applied to key problems arising in model-based design.