Conrad E. Bock

PSL: A semantic domain for flow models

Flow models underlie popular programming languages and many graphical behavior specification tools. However, their semantics is typically ambiguous, causing miscommunication between modelers and unexpected implementation results. This article introduces a way to disambiguate common flow modeling constructs, by expressing their semantics as constraints on runtime sequences of behavior execution. It also shows that reduced ambiguity enables more powerful modeling abstractions, such as partial behavior specifications. The runtime representation considered in this paper uses the Process Specification Language (PSL), which is defined in first-order logic, making it amenable to automated reasoning. The activity diagrams of the Unified Modeling Language are used for example flow models.

Ontological product modeling for collaborative design

This paper shows how to combine ontological and model-based techniques in languages that facilitate collaborative design exploration. The proposed approach uses ontology to capture alternative designs and incremental refinements that meet requirements and earlier design commitments. Model-based techniques are applied to develop more powerful, engineering-friendly languages for using ontology. It uses ontologys open world semantics to support design collaboration with flexible and accurate design combination, refinement, and consistency checking. It also leads to more reliable interpretation of models across the product lifecycle due to more rigorous language semantics. An example language is described using these techniques.

Systems Engineering in the Product Lifecycle

This paper introduces basic elements of systems engineering that are useful in managing the product lifecycle, as expressed in an extension to the Unified Modeling Language. It presents models of product requirements for capturing stakeholder needs, system structure for defining the static relations of its elements, behaviour for the transformation of inputs to outputs, parametrics for constraining properties of structure and allocation for assigning behaviour to structure. The relation of behaviour to structure is identified as a central issue in the integration of systems and software engineering.

A Semantic Product Modeling Framework and Its Application to Behavior Evaluation

Supporting different stakeholder viewpoints across the product lifecycle requires semantic richness to represent product-related information and enable multiview engineering simulations. This paper proposes a multilevel product modeling framework enabling stakeholders to define product models and relate them to physical or simulated instances. The framework is defined within the Model-Driven Architecture using the multilevel (data, model, metamodel) approach. The data level represents real-world products, the model level describes models (product models) of real-world products, and the metamodel level describes models of the product models. The metamodel defined in this paper is specialized from a web ontology language enabling product designers to express the semantics of product models in an engineering-friendly way. The interactions between these three levels are described to show how each level in the framework is used in a product engineering context. A product design scenario and user interface for the product metamodel is provided for further understanding of the framework.

Evaluating reasoning systems

A review of the literature on evaluating reasoning systems reveals that it is a very broad area with wide variation in depth and breadth of research on metrics and tests. This is the second of a two-part series that begins to bring order to the area by categorizing reasoning systems according to their capabilities. These can be used as a basis for evaluating and testing reasoning systems claiming to be in each category. Capabilities are analyzed along the dimensions of representation languages and inference. The first part introduces information metrology, model theory, and inference to facilitate understanding of the reasoning categories presented. It also groups representation languages by their relation to first-order logic, and model-theoretic properties, such as soundness and completeness. This part examines inference procedures, dividing them into deduction, induction, abduction, and analogical reasoning. It explains the subcategories and characteristics of each, and concludes with recommendations for future work.

Componentization in the Systems Modeling Language

This paper describes new capabilities in the Systems Modeling Language that reduce the complexity of specifying systems through componentization, and increase the range of systems that can be specified. Modelers can identify portions of components available for connection to other components, and specify how systems make use of them. This reduces the complexity of specifying system by lowering the number of ways components can be connected, partly by hiding portions of components, and partly by limiting how exposed portions can be connected to others. The paper introduces basic SysML concepts and notations for specifying components and assembling them into a system. It covers capabilities added to SysML enabling a wider range of systems to be modeled, through detailed specification of the portions of components available for connection to other components, and detailed specification of the connections between them. These capabilities are described by relating models to potential systems built to meet the specifications, an approach typical in specifying semantics of formal languages. The paper is intended for those concerned with increased precision in SysML concepts, such as builders of model analyzers, checkers, and other automated support for systems engineering. It also enables more reliable interpretation of the SysML models generally, for example, during manufacturing and other stages of the product lifecycle. Examples are given in SysML notation for each concept.

Product modeling framework and language for behavior evaluation

Supporting different stakeholder viewpoints across the products entire lifecycle requires semantic richness for representing product related information. This paper proposes a multi-layered product-modeling framework that enables stakeholders to define their product-specific models and relate product-specific models to physical or simulated instances. The framework is defined within the Model-driven Architecture and adapted to the multi-layer approach of the architecture. The data layer represents real world products, the model layer includes models of those products, and the meta-model layer defines the product modeling language. The semantic-based product modeling language described in this paper is specialized from a web ontology language enabling product designers to express the semantics of their product models explicitly and logically in an engineering-friendly way. The interactions between these three layers are described to illustrate how each layer in the framework is used in a product engineering context.

Reusing metamodels and notation with Diagram Definition

It is increasingly common for language specifications to describe visual forms (concrete syntax) separately from underlying concepts (abstract syntax). This is typically to enable interchange of visual information between graphical modeling tools, such as positions of nodes and routings of lines. Often overlooked is that separation of visual forms and abstract concepts enables languages to define multiple visual forms for the same underlying concepts and for the same visual form to be used for similar underlying concepts in different languages (many-to-many relationships between concrete and abstract syntax). Visual forms can be adapted to communities using different notations for the same concepts and can be used to integrate communities using the same notation for similar concepts. Models of concrete syntax have been available for some time, but are rarely used to capture these many-to-many relationships with abstract syntax. This paper shows how to model these relationships using concrete graphical syntax expressed in the Diagram Definition standard, examining cases drawn from the Unified Modeling Language and the Business Process Model and Notation. This gives definers of graphical languages a way to specify visual forms for multiple communities.

An Extension of the Systems Modeling Language for Physical Interaction and Signal Flow Simulation

Computer-interpretable representations of system structure and behavior are at the center of developing today’s complex systems. Systems engineers create and review these representations using graphicalmodeling languages that capture requirements, designs, and tests (such as the Systems Modeling Language, SysML). However, these languages must be used in conjunction with analysis tools, in particular, with simulators for physical interaction and numeric signal flow based on ordinary and algebraic differential equation solvers. These kind of simulation tools are often used separately from system modeling tools, leading to inconsistencies that require additional work to eliminate, preventing multidisciplinary concerns from being reflected in the overall system design. As a result, there is an increasing need for integrating physical interaction and signal flow simulation tools and languages into system modeling under a single framework. In this article, we first present an abstraction of the constructs and semantics these simulation tools and languages have in common, based on earlier reviews. Then, we compare SysML to our simulation abstraction to find the parts of SysML closest to simulation modeling, and to identify simulation conceptsion to find the parts of SysML closest to simulation modeling, and to identify simulation concepts missing from SysML. This leads to extensions of SysML to bridge the gaps, illustrated with an example application. Next, we address issues in translating extended SysML models to common simulation tools and languages, including the differences between them. Finally, we validate the approach by applying the extension to an example SysML model, automating the translations in software, and showing that the results execute the same way on different simulation platforms. C⃝ 2017 Wiley Periodicals, Inc. Syst Eng 20: