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The paper shows the decidability of the reachability problem for planar, monotonic, linear hybrid automata without resets. These automata are a special class of linear hybrid automata with only two variables, whose flows in all states is monotonic along some direction in the plane, and in which the continuous variables are not reset on a discrete transition. [ABSTRACT FROM AUTHOR]

Abstraction is a key technique to combat the state space explosion problem in model checking probabilistic systems. In this paper we present new ways to abstract Discrete Time Markov Chains (DTMCs), Markov Decision Processes (MDPs), and Continuous Time Markov Chains (CTMCs). The main advantage of our abstractions is that they result in abstract models that are purely probabilistic, which maybe more amenable to automatic analysis than models with both nondeterministic and probabilistic steps that typically arise from previously known abstraction techniques. A key technical tool, developed in this paper, is the construction of least upper bounds for any collection of probability measures. This upper bound construction may be of independent interest that could be useful in the abstract interpretation and static analysis of probabilistic programs. [ABSTRACT FROM AUTHOR]

We investigate the problem of model checking Interval-valued Discrete-time Markov Chains (IDTMC). IDTMCs are discrete-time finite Markov Chains for which the exact transition probabilities are not known. Instead in IDTMCs, each transition is associated with an interval in which the actual transition probability must lie. We consider two semantic interpretations for the uncertainty in the transition probabilities of an IDTMC. In the first interpretation, we think of an IDTMC as representing a (possibly uncountable) family of (classical) discrete-time Markov Chains, where each member of the family is a Markov Chain whose transition probabilities lie within the interval range given in the IDTMC. This semantic interpretation we call Uncertain Markov Chains (UMC). In the second semantics for an IDTMC, which we call Interval Markov Decision Process (IMDP), we view the uncertainty as being resolved through non-determinism. In other words, each time a state is visited, we adversarially pick a transition distribution that respects the interval constraints, and take a probabilistic step according to the chosen distribution. We show that the PCTL model checking problem for both Uncertain Markov Chain semantics and Interval Markov Decision Process semantics is decidable in PSPACE. We also prove lower bounds for these model checking problems. [ABSTRACT FROM AUTHOR]

In the paper, we introduce a new tree automata framework, called propositional tree automata, capturing the class of tree languages that are closed under an equational theory and Boolean operations. This framework originates in work on developing a sufficient completeness checker for specifications with rewriting modulo an equational theory. Propositional tree automata recognize regular equational tree languages. However, unlike regular equational tree automata, the class of propositional tree automata is closed under Boolean operations. This extra expressiveness does not affect the decidability of the membership problem. This paper also analyzes in detail the emptiness problem for propositional tree automata with associative theories. Though undecidable in general, we present a semi-algorithm for checking emptiness based on machine learning that we have found useful in practice. [ABSTRACT FROM AUTHOR]

Boolean programs with recursion are convenient abstractions of sequential imperative programs, and can be represented as recursive state machines (RSMs) or pushdown automata. Motivated by the special structure of RSMs, we define a notion of modular visibly pushdown automata (modular VPA) and show that for the class of languages accepted by such automata, unique minimal modular VPA exist. This yields an efficient approximate minimization theorem that minimizes RSMs to within a factor of k of the minimal RSM, where k is the maximum number of parameters in any module. Using the congruence defined for minimization, we show an active learning algorithm (with a minimally adequate teacher) for context free languages in terms of modular VPAs. We also present an algorithm that constructs complete test suites for Boolean program specifications. Finally, we apply our results on learning and test generation to perform model checking of black-box Boolean programs. [ABSTRACT FROM AUTHOR]

Software systems are often modeled using infinite structures such as unbounded integers, infinite message queues and call stacks, and unbounded number of processes. This makes verification of these systems hard- in fact, for most common classes of infinite state systems, the verification problem is undecidable. [ABSTRACT FROM AUTHOR]

In order to make multithreaded programming manageable, programmers often follow a design principle where they break the problem into tasks which are then solved asynchronously and concurrently on different threads. This paper investigates the problem of model checking programs that follow this idiom. We present a programming language Spl that encapsulates this design pattern. Spl extends simplified form of sequential Java to which we add the capability of making asynchronous method invocations in addition to the standard synchronous method calls and the ability to execute asynchronous methods in threads atomically and concurrently. Our main result shows that the control state reachability problem for finite Spl programs is decidable. Therefore, such multithreaded programs can be model checked using the counterexample guided abstraction-refinement framework. [ABSTRACT FROM AUTHOR]

Statistical methods to model check stochastic systems have been, thus far, developed only for a sublogic of continuous stochastic logic (CSL) that does not have steady state operator and unbounded until formulas. In this paper, we present a statistical model checking algorithm that also verifies CSL formulas with unbounded untils. The algorithm is based on Monte Carlo simulation of the model and hypothesis testing of the samples, as opposed to sequential hypothesis testing. We have implemented the algorithm in a tool called VESTA, and found it to be effective in verifying several examples. [ABSTRACT FROM AUTHOR]

We study congruences on words in order to characterize the class of visibly pushdown languages (Vpl), a subclass of context-free languages. For any language L, we define a natural congruence on words that resembles the syntactic congruence for regular languages, such that this congruence is of finite index if, and only if, L is a Vpl. We then study the problem of finding canonical minimal deterministic automata for Vpls. Though Vpls in general do not have unique minimal automata, we consider a subclass of VPAs called k-module single-entry VPAs that correspond to programs with recursive procedures without input parameters, and show that the class of well-matched Vpls do indeed have unique minimal k-module single-entry automata. We also give a polynomial time algorithm that minimizes such k-module single-entry VPAs. [ABSTRACT FROM AUTHOR]

Traditional network simulators perform well in evaluating the performance of network protocols but lack the capability of verifying the correctness of protocols. To address this problem, we have extended the J-Sim network simulator with a model checking capability that explores the state space of a network protocol to find an execution that violates a safety invariant. In this paper, we demonstrate the usefulness of this integrated tool for verification and performance evaluation by analyzing two widely used and important network protocols: AODV and directed diffusion. Our analysis discovered a previously unknown bug in the J-Sim implementation of AODV. More importantly, we also discovered a serious deficiency in directed diffusion. To enable the analysis of these fairly complex protocols, we needed to develop protocol-specific search heuristics that guide state-space exploration. We report our findings on discovering good search heuristics to analyze network protocols similar to AODV and directed diffusion. [ABSTRACT FROM AUTHOR]