Iulia Dragomir

LO
4papers
7citations
Novelty51%
AI Score21

4 Papers

LOOct 23, 2017
The Refinement Calculus of Reactive Systems Toolset

Iulia Dragomir, Viorel Preoteasa, Stavros Tripakis

We present the Refinement Calculus of Reactive Systems Toolset, an environment for compositional modeling and reasoning about reactive systems, built on top of Isabelle, Simulink, and Python.

LOOct 11, 2017
The Refinement Calculus of Reactive Systems

Viorel Preoteasa, Iulia Dragomir, Stavros Tripakis

The Refinement Calculus of Reactive Systems (RCRS) is a compositional formal framework for modeling and reasoning about reactive systems. RCRS provides a language which allows to describe atomic components as symbolic transition systems or QLTL formulas, and composite components formed using three primitive composition operators: serial, parallel, and feedback. The semantics of the language is given in terms of monotonic property transformers, an extension to reactive systems of monotonic predicate transformers, which have been used to give compositional semantics to sequential programs. RCRS allows to specify both safety and liveness properties. It also allows to model input-output systems which are both non-deterministic and non-input-receptive (i.e., which may reject some inputs at some points in time), and can thus be seen as a behavioral type system. RCRS provides a set of techniques for symbolic computer-aided reasoning, including compositional static analysis and verification. RCRS comes with a publicly available implementation which includes a complete formalization of the RCRS theory in the Isabelle proof assistant.

SEDec 16, 2016
Type Inference of Simulink Hierarchical Block Diagrams in Isabelle

Viorel Preoteasa, Iulia Dragomir, Stavros Tripakis

Simulink is a de-facto industrial standard for the design of embedded systems. In previous work, we developed a compositional analysis framework for Simulink models in Isabelle -- the Refinement Calculus of Reactive Systems (RCRS), which allows checking compatibility and substitutability of components. However, standard type checking was not considered in that work. In this paper we present a method for the type inference of hierarchical block diagrams using the Isabelle theorem prover. A Simulink diagram is translated into an (RCRS) Isabelle theory. Then the Isabelle's powerful type inference mechanism is used to infer the types of the diagram based on the types of the basic blocks. One of the aims is to handle formally as many diagrams as possible. In particular, we want to be able to handle even those diagrams that may have typing ambiguities, provided that they are accepted by Simulink. This method is implemented in our toolset that translates Simulink diagrams into Isabelle theories and simplifies them. We evaluate our technique on several case studies, most notably, an automotive fuel control system benchmark provided by Toyota.

SEOct 16, 2015
Translating Hierarchical Block Diagrams into Composite Predicate Transformers

Iulia Dragomir, Viorel Preoteasa, Stavros Tripakis

Simulink is the de facto industrial standard for designing embedded control systems. When dealing with the formal verification of Simulink models, we face the problem of translating the graphical language of Simulink, namely, hierarchical block diagrams (HBDs), into a formalism suitable for verification. In this paper, we study the translation of HBDs into the compositional refinement calculus framework for reactive systems. Specifically, we consider as target language an algebra of atomic predicate transformers to capture basic Simulink blocks (both stateless and stateful), composed in series, in parallel, and in feedback. For a given HBD, there are many possible ways to translate it into a term in this algebra, with different tradeoffs. We explore these tradeoffs, and present three translation algorithms. We report on a prototype implementation of these algorithms in a tool that translates Simulink models into algebra terms implemented in the Isabelle theorem prover. We test our tool on several case studies including a benchmark Simulink model by Toyota. We compare the three translation algorithms, with respect to size and readability of generated terms, simplifiability of the corresponding formulas, and other metrics.