A semantic anchoring infrastructure for model-integrated computing

Abstract

Model-Integrated Computing (MIC) is an approach for model-based design of embedded software and systems. MIC places strong emphasis on the use of domain-specific modeling languages (DSMLs) and model transformation techniques in design flows. Metamodeling facilitates the rapid, inexpensive development of DSMLs. However, the semantics specification for DSMLs is still a hard problem.

In this thesis, we propose a semantic anchoring infrastructure including a set of reusable “semantic units” that provide reference semantics for basic behavioral categories using the Abstract State Machine framework. A tool suite for the semantic anchoring methodology is developed to facilitate the transformational specification of DSML semantics. If the semantics of a DSML can be directly mapped onto one of the basic behavioral categories, its semantics can be defined by simply specifying the semantic anchoring rules between the DSML and a semantic unit.

However, in heterogeneous systems, the semantics is not always fully captured by a predefined semantic unit. If the semantics is specified from scratch it is not only expensive but we loose the advantages of anchoring the semantics to a set of common and well-established semantic units. Therefore, we extend the semantic anchoring framework to heterogeneous behaviors by developing an approach for the composition of semantic units. The compositional semantics specification approach reduces the required effort from DSML designers and improves the quality of the specification.

This thesis also includes three case studies for different purposes. The FSM domain in Ptolemy is used as a case study to explain the semantic anchoring methodology and to illustrate how the semantic anchoring tool suite is applied to design DSMLs. The Timed Automata Semantic Unit is defined as an example to illustrate how to specify semantic units. An industrial-strength modeling language, EFSM, is employed as a case study to explain the compositional semantics specification approach.