IMITATOR: A Tool for Synthesizing Constraints on Timing Bounds of Timed Automata

Abstract

Abstract. We present here Imitator, a tool for synthesizing constraints on timing bounds (seen as parameters) in the framework of timed automata. Unlike classical synthesis methods, we take advantage of a given reference valuation of the parameters for which the system is known to behave properly. Our aim is to generate a constraint such that, under any valuation satisfying this constraint, the system is guaranteed to behave, in terms of alternating sequences of locations and actions, as under the reference valuation. This is useful for safely relaxing some values of the reference valuation, and optimizing timing bounds of the system. We have successfully applied our tool to various examples of asynchronous circuits and protocols. ContextTimed automata [1] are finite control automata equipped with clocks, which are real-valued variables which increase uniformly. This model is useful for reasoning about real-time systems, because one can specify quantitatively the interval of time during which the transitions can occur, using timing bounds. However, the behavior of a system is very sensitive to the values of these bounds, and it is rather difficult to find their correct values. It is therefore interesting to reason parametrically, by considering that these bounds are unknown constants, or parameters, and try to synthesize a constraint (i.e., a conjunction of linear inequalities) on these parameters which will guarantee a correct behavior of the system. Such automata are called parametric timed automata (PTA) [2,11].The synthesis of constraints for PTA has been mainly done by supposing given a set of "bad states" (see, e.g., [8,9]). The goal is to find a set of parameters for which the considered timed automaton does not reach any of these bad states. We call such a method a bad-state oriented method. By contrast, we present in this paper a tool based on a good-state oriented method. Principle of ImitatorThe tool Imitator (Inverse Method for Inferring Time AbstracT behaviOR) implements the algorithm InverseMethod , described in [4]. We assume given a

Parametric Verification and Test Coverage for Hybrid Automata Using the Inverse Method

“…The algorithm has first been described for parametric timed automata in [4]. It has been applied for the synthesis of timing constraints for memory circuits [2].…”

An extension of the inverse method to probabilistic timed automata

“…The Python program contains about 1500 lines of code, and its writing took about 4 man-months of work (see [5]). …”

“…Using the tool IMITATOR [5], which implements the inverse method in the nonprobabilistic framework, we generate a constraint K 0 for the non-probabilistic version of the protocol.…”

IMITATOR II: A Tool for Solving the Good Parameters Problem in Timed Automata

“…IMITATOR II is a new version of IMITATOR [7], a prototype written in Python [26] implementing the inverse method, and calling the model checker HYTECH [18]. IMITATOR II has been entirely rewritten and is now a standalone tool, making use of the APRON library [20] and the Parma Polyhedra Library [9].…”