4,932 research outputs found

    EnPAC: Petri Net Model Checking for Linear Temporal Logic

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    State generation and exploration (counterexample search) are two cores of explicit-state Petri net model checking for linear temporal logic (LTL). Traditional state generation updates a structure to reduce the computation of all transitions and frequently encodes/decodes to read each encoded state. We present the optimized calculation of enabled transitions on demand by dynamic fireset to avoid such a structure. And we propose direct read/write (DRW) operation on encoded markings without decoding and re-encoding to make state generation faster and reduce memory consumption. To search counterexamples more quickly under an on-the-fly framework, we add heuristic information to the Buchi automaton to guide the exploration in the direction of accepted states. The above strategies can optimize existing methods for LTL model checking. We implement these optimization strategies in a Petri net model-checking tool called EnPAC (Enhanced Petri-net Analyser and Checker) for linear temporal logic. Then, we evaluate it on the benchmarks of MCC (Model Checking Contest), which shows a drastic improvement over the existing methods.Comment: 11 pages, 5 figure

    Safety-Aware Apprenticeship Learning

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    Apprenticeship learning (AL) is a kind of Learning from Demonstration techniques where the reward function of a Markov Decision Process (MDP) is unknown to the learning agent and the agent has to derive a good policy by observing an expert's demonstrations. In this paper, we study the problem of how to make AL algorithms inherently safe while still meeting its learning objective. We consider a setting where the unknown reward function is assumed to be a linear combination of a set of state features, and the safety property is specified in Probabilistic Computation Tree Logic (PCTL). By embedding probabilistic model checking inside AL, we propose a novel counterexample-guided approach that can ensure safety while retaining performance of the learnt policy. We demonstrate the effectiveness of our approach on several challenging AL scenarios where safety is essential.Comment: Accepted by International Conference on Computer Aided Verification (CAV) 201

    Model Checker Execution Reports

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    Software model checking constitutes an undecidable problem and, as such, even an ideal tool will in some cases fail to give a conclusive answer. In practice, software model checkers fail often and usually do not provide any information on what was effectively checked. The purpose of this work is to provide a conceptual framing to extend software model checkers in a way that allows users to access information about incomplete checks. We characterize the information that model checkers themselves can provide, in terms of analyzed traces, i.e. sequences of statements, and safe cones, and present the notion of execution reports, which we also formalize. We instantiate these concepts for a family of techniques based on Abstract Reachability Trees and implement the approach using the software model checker CPAchecker. We evaluate our approach empirically and provide examples to illustrate the execution reports produced and the information that can be extracted

    On minimising the maximum expected verification time

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    Cyber Physical Systems (CPSs) consist of hardware and software components. To verify that the whole (i.e., software + hardware) system meets the given specifications, exhaustive simulation-based approaches (Hardware In the Loop Simulation, HILS) can be effectively used by first generating all relevant simulation scenarios (i.e., sequences of disturbances) and then actually simulating all of them (verification phase). When considering the whole verification activity, we see that the above mentioned verification phase is repeated until no error is found. Accordingly, in order to minimise the time taken by the whole verification activity, in each verification phase we should, ideally, start by simulating scenarios witnessing errors (counterexamples). Of course, to know beforehand the set of such scenarios is not feasible. In this paper we show how to select scenarios so as to minimise the Worst Case Expected Verification Tim

    PrIC3: Property Directed Reachability for MDPs

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    IC3 has been a leap forward in symbolic model checking. This paper proposes PrIC3 (pronounced pricy-three), a conservative extension of IC3 to symbolic model checking of MDPs. Our main focus is to develop the theory underlying PrIC3. Alongside, we present a first implementation of PrIC3 including the key ingredients from IC3 such as generalization, repushing, and propagation

    Minimal Proof Search for Modal Logic K Model Checking

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    Most modal logics such as S5, LTL, or ATL are extensions of Modal Logic K. While the model checking problems for LTL and to a lesser extent ATL have been very active research areas for the past decades, the model checking problem for the more basic Multi-agent Modal Logic K (MMLK) has important applications as a formal framework for perfect information multi-player games on its own. We present Minimal Proof Search (MPS), an effort number based algorithm solving the model checking problem for MMLK. We prove two important properties for MPS beyond its correctness. The (dis)proof exhibited by MPS is of minimal cost for a general definition of cost, and MPS is an optimal algorithm for finding (dis)proofs of minimal cost. Optimality means that any comparable algorithm either needs to explore a bigger or equal state space than MPS, or is not guaranteed to find a (dis)proof of minimal cost on every input. As such, our work relates to A* and AO* in heuristic search, to Proof Number Search and DFPN+ in two-player games, and to counterexample minimization in software model checking.Comment: Extended version of the JELIA 2012 paper with the same titl
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