Symbolic model checking: 10/sup 20/ states and beyond

Burch, Jerry R.; Clarke, Edmund M.; McMillan, Kenneth L.; Dill, David L.; Hwang, L.J.

doi:10.1109/lics.1990.113767

Cited by 603 publications

(722 citation statements)

References 8 publications

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“…2.3]). Several approaches for mitigating this problem have been suggested, such as abstraction techniques like the one proposed by Clarke in [CGL94], partial order reduction approaches (see [GvLH + 96]), symbolic model checking using binary decision diagrams (BDDs) [BCM92], bounded model checking using SAT solvers [CBRZ01], or distributed model checking like the swarm verification extension of the SPIN model checker [HJG08]. All of these methods have in common that they are committed to solve the model checking problem in an exact manner, which means that when the algorithm terminates without finding a counter-example, this is interpreted as proof that the checked property is fulfilled by the model.…”

Section: Temporal Logics and Model Checkingmentioning

confidence: 99%

Simulation and Statistical Model Checking of Logic-Based Multi-Agent System Models

Kroiß

2014

Advances in Intelligent Systems and Computing

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This thesis presents SALMA (Simulation and Analysis of Logic-Based MultiAgent Models), a new approach for simulation and statistical model checking of multi-agent system models.Statistical model checking is a relatively new branch of model-based approximative verification methods that help to overcome the well-known scalability problems of exact model checking. In contrast to existing solutions, SALMA specifies the mechanisms of the simulated system by means of logical axioms based upon the well-established situation calculus. Leveraging the resulting first-order logic structure of the system model, the simulation is coupled with a statistical model-checker that uses a first-order variant of time-bounded linear temporal logic (LTL) for describing properties. This is combined with a procedural and process-based language for describing agent behavior. Together, these parts create a very expressive framework for modeling and verification that allows direct fine-grained reasoning about the agents' interaction with each other and with their (physical) environment.SALMA extends the classical situation calculus and linear temporal logic (LTL) with means to address the specific requirements of multi-agent simulation models. In particular, cyber-physical domains are considered where the agents interact with their physical environment. Among other things, the thesis describes a generic situation calculus axiomatization that encompasses sensing and information transfer in multi agent systems, for instance sensor measurements or inter-agent messages. The proposed model explicitly accounts for real-time constraints and stochastic effects that are inevitable in cyber-physical systems.In order to make SALMA's statistical model checking facilities usable also for more complex problems, a mechanism for the efficient on-the-fly evaluation of first-order LTL properties was developed. In particular, the presented algorithm uses an interval-based representation of the formula evaluation state together with several other optimization techniques to avoid unnecessary computation.Altogether, the goal of this thesis was to create an approach for simulation and statistical model checking of multi-agent systems that builds upon well-proven logical and statistical foundations, but at the same time takes a pragmatic software engineering perspective that considers factors like usability, scalability, and extensibility. In fact, experience gained during several small to mid-sized experiments that are presented in this thesis suggest that the SALMA approach seems to be able to live up to these expectations.

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Section: Temporal Logics and Model Checkingmentioning

confidence: 99%

Simulation and Statistical Model Checking of Logic-Based Multi-Agent System Models

Kroiß

2014

Advances in Intelligent Systems and Computing

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“…The symbolic algorithm allows it to scale well, at least up to medium size specifications [4]. While checking realizability / unrealizability is completely symbolic, the computation of a concrete implementation (or counter-implementation) requires the enumeration of states, which in some cases is much slower and does not scale well (specifically when dealing with data rather than control).…”

Section: Implementation and Evaluationmentioning

confidence: 99%

Two-Way Traceability and Conflict Debugging for AspectLTL Programs

Maoz¹,

Sa’ar²

2013

Lecture Notes in Computer Science

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Tracing program actions back to the concerns that have caused them and blaming specific code artifacts for concern interference are known challenges of AOP and related advanced modularity paradigms. In this work we address these challenges in the context of AspectLTL, a temporallogic based language for the specification and implementation of crosscutting concerns, which has a composition and synthesis-based weaving process whose output is a correctby-construction executable artifact. When a specification is realizable, we provide two-way traceability information that links each allowed or forbidden transition in the generated program with the aspects that have justified its presence or elimination. When a specification is unrealizable, we provide an interactive game proof that demonstrates conflicts that should be fixed. The techniques are implemented and demonstrated using running examples.

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“…Most research in temporal logic model checking is focussed on e cient data structures to represent state space. Perhaps the biggest pragmatic breakthrough in the area of model checking was the use of Ordered Binary Decision Diagrams (OBDDs) to represent the set of states during model checking [11,13]. When OBDDs are used to represent state sets in model checking, it is called symbolic model checking.…”

Section: Acknowledgementsmentioning

confidence: 99%

Symmetry and induction in model checking

Clarke

Jha

1995

Computer Science Today

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With the increasing complexity of digital systems, testing of digital systems is becoming increasingly important. Perhaps, the most popular method for testing hardware is simulation. The incompleteness of simulation based testing methods has spurred the recent surge in the research on formal veri cation. In formal veri cation, one builds a precise model of the hardware under scrutiny and proves that the model satis es a speci cation of interest. For example, suppose one wants to verify that a router chip does not deadlock. In this case the user will build a precise model of the router and the speci cation will express the property of deadlock freedom. The two approaches to formal veri cation are model checking and theorem proving. In this thesis we will only discuss model checking. Most model checking procedures su er from the state explosion problem, i.e., the size of the state space of the system can be exponential in the number of state variables of the system. For certain systems, exploiting the inherent symmetry can alleviate the state-explosion problem. We discuss Model Checking procedures which exploit symmetry. Current model checkers can only verify a single state-transition system at a time. We also want to extend the model checking techniques to handle in nite families of nite-state systems. In practice, nite state concurrent systems often exhibit considerable symmetry. W e i n v estigate techniques for reducing the complexity o f temporal logic model checking in the presence of symmetry. In particular, we show that symmetry can frequently be used to reduce the size of the state space that must be explored during model checking. We also investigate complexity o f v arious problems related to exploiting symmetry in model checking. Partial order based reduction techniques exploit independence of actions. We demonstrate that partial order and symmetry based reduction techniques can be applied simultaneously. The ability to reason automatically about entire families of similar state-transition systems is an important research goal. Such families arise frequently in the design of reactive systems in both hardware and software. The in nite family of token rings is a simple example. More complicated examples are trees of processes consisting of one root, several internal and leaf nodes, and hierarchical buses with di erent n umbers of processors and caches. A technique for verifying entire families of state-transition systems based on network grammars and process invariants is presented here.

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Symbolic model checking: 10/sup 20/ states and beyond

Cited by 603 publications

References 8 publications

Simulation and Statistical Model Checking of Logic-Based Multi-Agent System Models

Simulation and Statistical Model Checking of Logic-Based Multi-Agent System Models

Two-Way Traceability and Conflict Debugging for AspectLTL Programs

Symmetry and induction in model checking

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