Time for Statistical Model Checking of Real-Time Systems

Abstract. We propose the first tool for solving complex (some unde-cidable) problems of timed systems by using Statistical Model Checking (SMC). The tool monitors several runs of the system, and then relies on statistical algorithms to get an estimate of the correctness of the entire design. Contrary to other existing toolsets, ours relies on i) a natural stochastic semantics for networks of timed systems, ii) an engine capable to solve problems that are beyond the scope of classical model checkers, and iii) a friendly user interface.

Exploring model-based development for the verification of real-time Java code

Many safety- and security-critical systems are real-time systems and, as a result, tools and techniques for verifying real-time systems are extremely important. Simulation and testing such systems can be exceedingly time-consuming and these techniques provide only probabilistic measures of correctness. There are a number of model-checking tools for real-time systems. However, they provide formal verification for models, not programs. To increase the confidence in real-time programs written in real-time Java, this paper takes a modelling approach to the design of such programs. First, models can be mechanically verified, to check whether they satisfy particular properties, by using current real-time model-checking tools. Then, programs are derived from the model by following a systematic approach. To illustrate the approach we use a nontrivial example: a gear controller

From offline toward real-time: A hybrid systems model checking and CPS co-design approach for Medical Device Plug-andPlay (MDPnP

Abstract—Hybrid systems model checking is a great success in guaranteeing the safety of computerized control cyber-physical systems (CPS). However, when applying hybrid systems model checking to Medical Device Plug-and-Play (MDPnP) CPS, we encounter two challenges due to the complexity of human body: i) there are no good offline differential equation based models for many human body parameters; ii) the complexity of human body can result in many variables, complicating the system model. In an attempt to address the challenges, we propose to alter the traditional approach of offline hybrid systems model checking of time-unbounded (i.e., infinite-horizon, a.k.a., long-run) future behavior to online hybrid systems model checking of time-bounded (i.e., finite-horizon, a.k.a., short-run) future behavior. According to this proposal, online model checking runs as a real-time task to prevent faults. To meet the real-time requirements, certain design patterns must be followed, which brings up the co-design issue. We propose two sets of system co-design patterns for hard real-time and soft real-time respectively. To evaluate our proposals, a case study on laser tracheotomy MDPnP is carried out. The study shows the necessity of online model checking. Furthermore, test results based on real-world human subject trace show the feasibility and effectiveness of our proposed co-design.

Scaling BDD-based timed verification with simulation reduction

Digitization is a technique that has been widely used in real-time model checking. With the assumption of digital clocks, symbolic model checking techniques (like those based on BDDs) can be applied for real-time systems. The problem of model checking real-time systems based on digitization is that the number of tick transitions increases rapidly with the increment of clock upper bounds. In this paper, we propose to improve BDD-based verification for real-time systems using simulation reduction. We show that simulation reduction allows us to verify timed automata with large clock upper bounds and to converge faster to the fixpoint. The presented approach is applied to reachability and LTL verification for real-time systems. Finally, we compare our approach with existing tools such as Rabbit, Uppaal, and CTAV and show that our approach outperforms them and achieves a significant speedup.No Full Tex

Verification of Timed Automata Using Rewrite Rules and Strategies

ELAN is a powerful language and environment for specifying and prototyping deduction systems in a language based on rewrite rules controlled by strategies. Timed automata is a class of continuous real-time models of reactive systems for which efficient model-checking algorithms have been devised. In this paper, we show that these algorithms can very easily be prototyped in the ELAN system. This paper argues through this example that rewriting based systems relying on rules and strategies are a good framework to prototype, study and test rather efficiently symbolic model-checking algorithms, i.e. algorithms which involve combination of graph exploration rules, deduction rules, constraint solving techniques and decision procedures

Approximate Model Checking of Real-Time Systems for Linear Duration Invariants

Real-time systems are usually modelled with timed automata and real-time requirements relating to the state durations of the system are often specifiable using Linear Duration Invariants, which is a decidable subclass of Duration Calculus formulas. Various algorithms have been developed to check timed automata or real-time automata for linear duration invariants, but each needs complicated preprocessing and exponential calculation. To the best of our knowledge, these algorithms have not been implemented. In this paper, we present an approximate model checking technique based on a genetic algorithm to check real-time automata for linear durration invariants in reasonable times. Genetic algorithm is a good optimization method when a problem needs massive computation and it works particularly well in our case because the fitness function which is derived from the linear duration invariant is linear. ACM Computing Classification System (1998): D.2.4, C.3