Methods and Tool Support for Analyzing Architectural Models of Embedded Systems

Embedded systems are ubiquitous in the modern world. They are microcomputers most often included incomplete devices consisting of software and hardware. Embedded systems range from small devices to large systems monitoring and controlling complex processes. Design and development of such systems is a complex task, since embedded systems often need to fulfill extra-functional requirements, on top of functional ones, within constrained amounts of platform resources. Some embedded systems are mission critical; hence, they are not allowed to fail during the mission. One way to ensure that a system works in accordance to its specification is to define the system in an Architecture Description Language (ADL) and apply formal verification methods. The Architecture Design and Analysis Language (AADL) has become popular in the avionic and automobile industry, and is equipped with several annexes, among them the Behavior Annex. However, AADL still misses a formal semantics, which prevents the possibility to prove correctness of architecture features by performing model checking on AADL models. Moreover, AADL does not support time annotations, which prevents modeling of real-time systems in AADL. In this thesis, we address these issues by presenting a formal analysis framework including a denotationalsemantics for a subset of the AADL and its Behavior Annex, which evaluates properties defined in Computation Tree Logic (CTL) by providing model checking. Model checking is a formal verification method that has proved to be powerful as well as effective. Our AADL-semantics is supported by a tool with an implementation of the semantics in Standard ML, which in turn is encapsulated in an Eclipse plugin.We also present a time annotation extension of AADL, implemented in a tool translating time annotated AADL and its Behavior Annex into the Timed Abstract State Machine (TASM) for simulation of real-time features. Another closely related problem is how to achieve optimal component distribution; in order to address this issue we have developed a tool that perform near-optional component distribution in regard to a series of parameters. The research results, which have been validated thought case studies, provides the possibility for a system engineer to model a system and prove its correctness. The research has been conducted in the context of the PROGRESS research center, for predictable embedded software systems