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Exploiting interleaving semantics in symbolic state-space generation
- Formal Methods in System Design
"... Abstract. Symbolic techniques based on Binary Decision Diagrams (BDDs) are widely employed for reasoning about temporal properties of hardware circuits and synchronous controllers. However, they often perform poorly when dealing with the huge state spaces underlying systems based on interleaving sem ..."
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Abstract. Symbolic techniques based on Binary Decision Diagrams (BDDs) are widely employed for reasoning about temporal properties of hardware circuits and synchronous controllers. However, they often perform poorly when dealing with the huge state spaces underlying systems based on interleaving semantics, such as communications protocols and distributed software, which are composed of independently acting subsystems that communicate via shared events. This article shows that the efficiency of state–space exploration techniques using decision diagrams can be drastically improved by exploiting the interleaving semantics underlying many event–based and component–based system models. A new algorithm for symbolically generating state spaces is presented that (i) encodes a model’s state vectors with Multi–valued Decision Diagrams (MDDs) rather than flattening them into BDDs and (ii) partitions the model’s Kronecker–consistent next–state function by event and subsystem, thus enabling multiple lightweight next–state transformations rather than a single heavyweight one. Together, this paves the way for a novel iteration order, called saturation, which replaces the breadth–first search order of traditional algorithms. The resulting saturation algorithm is implemented in the tool SMART, and experimental studies show that it is often several orders of magnitude better in terms of time efficiency, final memory consumption, and peak memory consumption than existing symbolic algorithms.
Formal Verification of the NASA Runway Safety Monitor
- SOFTWARE TOOLS FOR TECHNOLOGY TRANSFER
, 2007
"... The Runway Safety Monitor (RSM) designed by Lockheed Martin is part of NASA’s effort to reduce aviation accidents. We developed a Petri net model of the RSM protocol and used the model checking functions of our tool SmArT to investigate a number of safety properties for the RSM. To mitigate the imp ..."
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Cited by 13 (8 self)
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The Runway Safety Monitor (RSM) designed by Lockheed Martin is part of NASA’s effort to reduce aviation accidents. We developed a Petri net model of the RSM protocol and used the model checking functions of our tool SmArT to investigate a number of safety properties for the RSM. To mitigate the impact of statespace explosion, we built a highly discretized model of the system, obtained by partitioning the monitored runway zone into a grid of smaller volumes and by considering scenarios involving only two aircraft. The model also assumes that there are no communication failures, such as bad input from radar or lack of incoming data, thus it relies on a consistent view of reality by all participants. In spite of these simplifications, we were able to expose potential problems in the conceptual design of RSM. Our findings were forwarded to the design engineers, who undertook corrective action. Additionally, the results stress the efficiency attained by the new model checking algorithms implemented in SmArT, and demonstrate their applicability to real-world systems. Attempts to verify RSM with similar NuSMV and SPIN models have failed due to excessive memory consumption.
Symbolic State-space Generation of Asynchronous Systems Using Extensible Decision Diagrams
"... Abstract. We propose a new type of canonical decision diagrams, which allows a more efficient symbolic state-space generation for general asynchronous systems by allowing on-the-fly extension of the possible state variable domains. After implementing both breadth-first and saturationbased state-spac ..."
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Abstract. We propose a new type of canonical decision diagrams, which allows a more efficient symbolic state-space generation for general asynchronous systems by allowing on-the-fly extension of the possible state variable domains. After implementing both breadth-first and saturationbased state-space generation with this new data structure in our tool SmArT, we are able to exhibit substantial efficiency improvements with respect to traditional “static ” decision diagrams. Since our previous works demonstrated that saturation outperforms breadth-first approaches, saturation with this new structure is now arguably the state-of-the-art algorithm for symbolic state-space generation of asynchronous systems. 1
Restructuring tensor products to enhance the numerical solution of structured Markov chains (accepted
- In Proc. of the 6th Int. Conf. on the Num. Sol. of Markov Chains (NSMC ’10
, 2010
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Activity-local symbolic state graph generation for high-level stochastic models
- In Proceedings of the 13th GI/ITG Conference on Measurement, Modeling, and Evaluation of Computer and Communication Systems (MMB
, 2006
"... Abstract. This paper introduces a new, efficient method for deriving compact symbolic representations of very large (labelled) Markov chains resulting from high-level model specifications such as stochastic Petri nets, stochastic process algebras, etc.. This so called “activity-local” scheme is comb ..."
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Cited by 4 (2 self)
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Abstract. This paper introduces a new, efficient method for deriving compact symbolic representations of very large (labelled) Markov chains resulting from high-level model specifications such as stochastic Petri nets, stochastic process algebras, etc.. This so called “activity-local” scheme is combined with a new data structure, called zero-suppressed multi-terminal binary decision diagram, and a new efficient “activityoriented” scheme for symbolic reachability analysis. Several standard benchmark models from the literature are analyzed in order to show the superiority of our approach. 1
Implicit data structures for logic and stochastic systems analysis
, 2005
"... Both logic and stochastic analysis have strong theoretical underpinnings, but they have been traditionally relegated to separate areas of computer science, the former focusing on logic and discrete algorithms, the latter on exact or approximate numerical methods. In the last few years, though, there ..."
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Cited by 1 (0 self)
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Both logic and stochastic analysis have strong theoretical underpinnings, but they have been traditionally relegated to separate areas of computer science, the former focusing on logic and discrete algorithms, the latter on exact or approximate numerical methods. In the last few years, though, there has been a convergence of research in these two areas, due to the realization that data structures used in one area can benefit the other and that, by merging the goals of the two areas, a more integrated approach to system analysis can be derived. In this paper, we describe some of the beneficial interactions between the two, and some of the research challenges ahead.
Comparison of encoding schemes for symbolic model checking of bounded petri nets
, 2010
"... Part of the Computer Sciences Commons This Thesis is brought to you for free and open access by the Graduate College at Digital Repository @ Iowa State University. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Digital Repository @ Iowa Stat ..."
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Part of the Computer Sciences Commons This Thesis is brought to you for free and open access by the Graduate College at Digital Repository @ Iowa State University. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Digital Repository @ Iowa State University. For more information, please contact
Reachablestatespace generationfor structuredmodelswhichuse functionaltransitions
"... Abstract—This paper presents a new approach to obtain the Reachable State Space (RSS) of a structured model which uses functional transitions. We use Multi-valued Decision Diagrams (MDD) to store sets of reachable spaces and Stochastic Automata Networks (SAN) formalism to describe structured models. ..."
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Abstract—This paper presents a new approach to obtain the Reachable State Space (RSS) of a structured model which uses functional transitions. We use Multi-valued Decision Diagrams (MDD) to store sets of reachable spaces and Stochastic Automata Networks (SAN) formalism to describe structured models. We focus our contribution in the proposal of a method to generate a compact MDD description taking advantage of the modular structure of SAN formalism, which also allows to represent the transition rate matrix of a continuous-time Markov chain by means of a sum of generalized Kronecker products. The method is tested on some models and the conclusion presents future work.
Verification of Software via Integration of Design and Implementation
"... Model checking is usually applied at the design phase to verify that preliminary high–level design specifications conform to their requirements. Source code analysis, on the other hand, is used to check for correctness of implementation once it is realized from the design specifications. However, th ..."
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Model checking is usually applied at the design phase to verify that preliminary high–level design specifications conform to their requirements. Source code analysis, on the other hand, is used to check for correctness of implementation once it is realized from the design specifications. However, the current practice of validating a design and its implementation in isolation makes it necessary to employ rigorous testing analysis to empirically ensure that the implementation satisfies the design specification. This article describes a formal framework that allows design models to contain embedded partial implementations as components; these models are then formally analyzed to ensure that global requirements are satisfied. This framework can be utilized to incrementally develop and ensure correctness of the design and the corresponding implementation. Realization of this framework requires consolidation and expansion of traditional formal verification techniques by integration of model checking, program analysis and constraint solving. 1