822 research outputs found

    Counterexample Generation in Probabilistic Model Checking

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    Providing evidence for the refutation of a property is an essential, if not the most important, feature of model checking. This paper considers algorithms for counterexample generation for probabilistic CTL formulae in discrete-time Markov chains. Finding the strongest evidence (i.e., the most probable path) violating a (bounded) until-formula is shown to be reducible to a single-source (hop-constrained) shortest path problem. Counterexamples of smallest size that deviate most from the required probability bound can be obtained by applying (small amendments to) k-shortest (hop-constrained) paths algorithms. These results can be extended to Markov chains with rewards, to LTL model checking, and are useful for Markov decision processes. Experimental results show that typically the size of a counterexample is excessive. To obtain much more compact representations, we present a simple algorithm to generate (minimal) regular expressions that can act as counterexamples. The feasibility of our approach is illustrated by means of two communication protocols: leader election in an anonymous ring network and the Crowds protocol

    Enhancing Test Coverage by Back-tracing Model-checker Counterexamples

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    AbstractThe automatic detection of unreachable coverage goals and generation of tests for "corner-case" scenarios is crucial to make testing and simulation based verification more effective. In this paper we address the problem of coverability analysis and test case generation in modular and component based systems. We propose a technique that, given an uncovered branch in a component, either establishes that the branch cannot be covered or produces a test case at the system level which covers the branch. The technique is based on the use of counterexamples returned by model checkers, and exploits compositionality to cope with large state spaces typical of real applications

    On the Complex Network Structure of Musical Pieces: Analysis of Some Use Cases from Different Music Genres

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    This paper focuses on the modeling of musical melodies as networks. Notes of a melody can be treated as nodes of a network. Connections are created whenever notes are played in sequence. We analyze some main tracks coming from different music genres, with melodies played using different musical instruments. We find out that the considered networks are, in general, scale free networks and exhibit the small world property. We measure the main metrics and assess whether these networks can be considered as formed by sub-communities. Outcomes confirm that peculiar features of the tracks can be extracted from this analysis methodology. This approach can have an impact in several multimedia applications such as music didactics, multimedia entertainment, and digital music generation.Comment: accepted to Multimedia Tools and Applications, Springe

    Generation of counterexamples for the my--calculus

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    Symbolic temporal logic model checking is an automatic verification method. One of its main features is that a counterexample can be constructed when a temporal formula does not hold for the model. Most model checkers so far have restricted the type of formulae that can be checked to fair CTL formulae. Model checkers constructed just recently can check arbitrary ÎĽ\mu-calculus formulae. How to construct counterexamples for arbitrary \muf has not been investigated yet. This paper shows how counterexamples and witnesses for the whole ÎĽ\mu-calculus can be constructed

    Model-Based Scenario Testing and Model Checking with Applications in the Railway Domain

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    This thesis introduces Timed Moore Automata, a specification formalism, which extends the classical Moore Automata by adding the concept of abstract timers without concrete delay time values, which can be started and reset, and which can change their state from running to elapsed. The formalism is used in real-world railway domain applications, and algorithms for the automated test data generation and explicit model checking of Timed Moore Automata models are presented. In addition, this thesis deals with test data generation for larger scale test models using standardized modeling formalisms. An existing framework for the automated test data generation is presented, and its underlying work-flow is extended and modified in order to allow user interaction and guidance within the generation process. As opposed to specifying generation constraints for entire test scenarios, the modified work flow then allows for an iterative approach to elaborating and formalizing test generation goals

    A Computable Economist’s Perspective on Computational Complexity

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    A computable economist's view of the world of computational complexity theory is described. This means the model of computation underpinning theories of computational complexity plays a central role. The emergence of computational complexity theories from diverse traditions is emphasised. The unifications that emerged in the modern era was codified by means of the notions of efficiency of computations, non-deterministic computations, completeness, reducibility and verifiability - all three of the latter concepts had their origins on what may be called 'Post's Program of Research for Higher Recursion Theory'. Approximations, computations and constructions are also emphasised. The recent real model of computation as a basis for studying computational complexity in the domain of the reals is also presented and discussed, albeit critically. A brief sceptical section on algorithmic complexity theory is included in an appendix

    IST Austria Technical Report

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    A fundamental algorithmic problem at the heart of static analysis is Dyck reachability. The input is a graphwhere the edges are labeled with different types of opening and closing parentheses, and the reachabilityinformation is computed via paths whose parentheses are properly matched. We present new results for Dyckreachability problems with applications to alias analysis and data-dependence analysis. Our main contributions,that include improved upper bounds as well as lower bounds that establish optimality guarantees, are asfollows:First, we consider Dyck reachability on bidirected graphs, which is the standard way of performing field-sensitive points-to analysis. Given a bidirected graph withnnodes andmedges, we present: (i) an algorithmwith worst-case running timeO(m+n·α(n)), whereα(n)is the inverse Ackermann function, improving thepreviously knownO(n2)time bound; (ii) a matching lower bound that shows that our algorithm is optimalwrt to worst-case complexity; and (iii) an optimal average-case upper bound ofO(m)time, improving thepreviously knownO(m·logn)bound.Second, we consider the problem of context-sensitive data-dependence analysis, where the task is to obtainanalysis summaries of library code in the presence of callbacks. Our algorithm preprocesses libraries in almostlinear time, after which the contribution of the library in the complexity of the client analysis is only linear,and only wrt the number of call sites.Third, we prove that combinatorial algorithms for Dyck reachability on general graphs with truly sub-cubic bounds cannot be obtained without obtaining sub-cubic combinatorial algorithms for Boolean MatrixMultiplication, which is a long-standing open problem. Thus we establish that the existing combinatorialalgorithms for Dyck reachability are (conditionally) optimal for general graphs. We also show that the samehardness holds for graphs of constant treewidth.Finally, we provide a prototype implementation of our algorithms for both alias analysis and data-dependenceanalysis. Our experimental evaluation demonstrates that the new algorithms significantly outperform allexisting methods on the two problems, over real-world benchmarks
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