We present a general framework for the formal specification and algorithmic analysis of hybrid systems. A hybrid system consists of a discrete program with an analog environment. We model hybrid systems as nite automata equipped with variables that evolve continuously with time according to dynamical laws. For verification purposes, we restrict ourselves to linear hybrid systems, where all variables follow piecewise-linear trajectories. We provide decidability and undecidability results for classes of linear hybrid systems, and we show that standard program-analysis techniques can be adapted to linear hybrid systems. In particular, we consider symbolic model-checking and minimization procedures that are based on the reachability analysis of an infinite state space. The procedures iteratively compute state sets that are definable as unions of convex polyhedra in multidimensional real space. We also present approximation techniques for dealing with systems for which the iterative procedures do not converge.

Linear Relation Analysis [CH78] is an abstract interpretation devoted to the automatic discovery of invariant linear inequalities among numerical variables of a program. In this paper, we apply such an analysis to the verification of quantitative time properties of two kinds of systems: synchronous programs and linear hybrid systems.

We present a new application of the abstract interpretation by means of convex polyhedra, to a class of hybrid systems, i.e., systems involving both discrete and continuous variables. The result is an efficient automatic tool for approximate, but conservative, verification of reachability properties of these systems. 1 Introduction Timed automata [AD90] have been recently introduced to model real-time systems. A timed automaton is a finite automaton associated with a finite set of clocks, each clock counting the continuous elapsing of time. Each transition of the automaton can be guarded by a simple linear condition on the clock values, and can result in resetting some clocks to zero. A nice feature of this model is that it can be abstracted into a finite state system, and that all the standard verification problems (reachability, TCTL model-checking [ACD90, HNSY92]) are decidable. However, many interesting extensions of this model have been shown to lose this decidability propert...

We present a new method for the generation of linear invariants which reduces the problem to a non-linear constraint solving problem. Our method, based on Farkas' Lemma, synthesizes linear invariants by extracting non-linear constraints on the coefficients of a target invariant from a program. These constraints guarantee that the linear invariant is inductive. We then apply existing techniques, including specialized quantifier elimination methods over the reals, to solve these non-linear constraints. Our method has the advantage of being complete for inductive invariants. To our knowledge, this is the first sound and complete technique for generating inductive invariants of this form. We illustrate the practicality of our method on several examples, including cases in which traditional methods based on abstract interpretation with widening fail to generate sufficiently strong invariants.