99,649 research outputs found

    A graph-semantics of business configurations

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    In this paper we give graph-semantics to a fundamental part of the semantics of the service modeling language SRML. To achieve this goal we develop a new graph transformation system for what we call 2-level symbolic graphs. These kind of graphs extend symbolic graphs with a simple 2-level hierarchy that can be generalized to arbitrary hierarchies. We formalize the semantics using this new graph transformation system using a simple example of a trip booking agent.Postprint (published version

    The probability of non-confluent systems

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    We show how to provide a structure of probability space to the set of execution traces on a non-confluent abstract rewrite system, by defining a variant of a Lebesgue measure on the space of traces. Then, we show how to use this probability space to transform a non-deterministic calculus into a probabilistic one. We use as example Lambda+, a recently introduced calculus defined through type isomorphisms.Comment: In Proceedings DCM 2013, arXiv:1403.768

    Extending Hybrid CSP with Probability and Stochasticity

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    Probabilistic and stochastic behavior are omnipresent in computer controlled systems, in particular, so-called safety-critical hybrid systems, because of fundamental properties of nature, uncertain environments, or simplifications to overcome complexity. Tightly intertwining discrete, continuous and stochastic dynamics complicates modelling, analysis and verification of stochastic hybrid systems (SHSs). In the literature, this issue has been extensively investigated, but unfortunately it still remains challenging as no promising general solutions are available yet. In this paper, we give our effort by proposing a general compositional approach for modelling and verification of SHSs. First, we extend Hybrid CSP (HCSP), a very expressive and process algebra-like formal modeling language for hybrid systems, by introducing probability and stochasticity to model SHSs, which is called stochastic HCSP (SHCSP). To this end, ordinary differential equations (ODEs) are generalized by stochastic differential equations (SDEs) and non-deterministic choice is replaced by probabilistic choice. Then, we extend Hybrid Hoare Logic (HHL) to specify and reason about SHCSP processes. We demonstrate our approach by an example from real-world.Comment: The conference version of this paper is accepted by SETTA 201

    Continuation-Passing C: compiling threads to events through continuations

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    In this paper, we introduce Continuation Passing C (CPC), a programming language for concurrent systems in which native and cooperative threads are unified and presented to the programmer as a single abstraction. The CPC compiler uses a compilation technique, based on the CPS transform, that yields efficient code and an extremely lightweight representation for contexts. We provide a proof of the correctness of our compilation scheme. We show in particular that lambda-lifting, a common compilation technique for functional languages, is also correct in an imperative language like C, under some conditions enforced by the CPC compiler. The current CPC compiler is mature enough to write substantial programs such as Hekate, a highly concurrent BitTorrent seeder. Our benchmark results show that CPC is as efficient, while using significantly less space, as the most efficient thread libraries available.Comment: Higher-Order and Symbolic Computation (2012). arXiv admin note: substantial text overlap with arXiv:1202.324

    Independence and concurrent separation logic

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    A compositional Petri net-based semantics is given to a simple language allowing pointer manipulation and parallelism. The model is then applied to give a notion of validity to the judgements made by concurrent separation logic that emphasizes the process-environment duality inherent in such rely-guarantee reasoning. Soundness of the rules of concurrent separation logic with respect to this definition of validity is shown. The independence information retained by the Petri net model is then exploited to characterize the independence of parallel processes enforced by the logic. This is shown to permit a refinement operation capable of changing the granularity of atomic actions

    Formally Specifying and Proving Operational Aspects of Forensic Lucid in Isabelle

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    A Forensic Lucid intensional programming language has been proposed for intensional cyberforensic analysis. In large part, the language is based on various predecessor and codecessor Lucid dialects bound by the higher-order intensional logic (HOIL) that is behind them. This work formally specifies the operational aspects of the Forensic Lucid language and compiles a theory of its constructs using Isabelle, a proof assistant system.Comment: 23 pages, 3 listings, 3 figures, 1 table, 1 Appendix with theorems, pp. 76--98. TPHOLs 2008 Emerging Trends Proceedings, August 18-21, Montreal, Canada. Editors: Otmane Ait Mohamed and Cesar Munoz and Sofiene Tahar. The individual paper's PDF is at http://users.encs.concordia.ca/~tphols08/TPHOLs2008/ET/76-98.pd

    Beyond Covariation: Cues to Causal Structure

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    Causal induction has two components: learning about the structure of causal models and learning about causal strength and other quantitative parameters. This chapter argues for several interconnected theses. First, people represent causal knowledge qualitatively, in terms of causal structure; quantitative knowledge is derivative. Second, people use a variety of cues to infer causal structure aside from statistical data (e.g. temporal order, intervention, coherence with prior knowledge). Third, once a structural model is hypothesized, subsequent statistical data are used to confirm, refute, or elaborate the model. Fourth, people are limited in the number and complexity of causal models that they can hold in mind to test, but they can separately learn and then integrate simple models, and revise models by adding and removing single links. Finally, current computational models of learning need further development before they can be applied to human learning
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