14,937 research outputs found

    TAPAs: A Tool for the Analysis of Process Algebras

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    Process algebras are formalisms for modelling concurrent systems that permit mathematical reasoning with respect to a set of desired properties. TAPAs is a tool that can be used to support the use of process algebras to specify and analyze concurrent systems. It does not aim at guaranteeing high performances, but has been developed as a support to teaching. Systems are described as process algebras terms that are then mapped to labelled transition systems (LTSs). Properties are verified either by checking equivalence of concrete and abstract systems descriptions, or by model checking temporal formulae over the obtained LTS. A key feature of TAPAs, that makes it particularly suitable for teaching, is that it maintains a consistent double representation of each system both as a term and as a graph. Another useful didactical feature is the exhibition of counterexamples in case equivalences are not verified or the proposed formulae are not satisfied

    A Time-Triggered Constraint-Based Calculus for Avionic Systems

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    The Integrated Modular Avionics (IMA) architec- ture and the Time-Triggered Ethernet (TTEthernet) network have emerged as the key components of a typical architecture model for recent civil aircrafts. We propose a real-time constraint-based calculus targeted at the analysis of such concepts of avionic embedded systems. We show our framework at work on the modelisation of both the (IMA) architecture and the TTEthernet network, illustrating their behavior by the well-known Flight Management System (FMS)

    A Symmetric Compositional Approach for Adaptive Ubiquitous Systems

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    International audienceIn ubiquitous computing, systems evolve surrounded by a heterogeneous smart-devices and software services, offering functionalities that enable new applications to be created. In such system, we need to consider the unpredictability of software infrastructure changes. To tackle the issue of the dynamic variation of the software infrastructure, compositional adaptation is now often used. The problem is that adaptation entities are independent-written. In such case, they may interfere when they are composed. In this paper, we propose a formal approach that allows composing applications at run time and managing these interferences. The formal model of the system and adaptations are defined in term of graphs. In particular, we demonstrate the symmetry property of our composition proces

    GPU Accelerated Particle Visualization with Splotch

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    Splotch is a rendering algorithm for exploration and visual discovery in particle-based datasets coming from astronomical observations or numerical simulations. The strengths of the approach are production of high quality imagery and support for very large-scale datasets through an effective mix of the OpenMP and MPI parallel programming paradigms. This article reports our experiences in re-designing Splotch for exploiting emerging HPC architectures nowadays increasingly populated with GPUs. A performance model is introduced for data transfers, computations and memory access, to guide our re-factoring of Splotch. A number of parallelization issues are discussed, in particular relating to race conditions and workload balancing, towards achieving optimal performances. Our implementation was accomplished by using the CUDA programming paradigm. Our strategy is founded on novel schemes achieving optimized data organisation and classification of particles. We deploy a reference simulation to present performance results on acceleration gains and scalability. We finally outline our vision for future work developments including possibilities for further optimisations and exploitation of emerging technologies.Comment: 25 pages, 9 figures. Astronomy and Computing (2014

    Connectors meet Choreographies

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    We present Cho-Reo-graphies (CR), a new language model that unites two powerful programming paradigms for concurrent software based on communicating processes: Choreographic Programming and Exogenous Coordination. In CR, programmers specify the desired communications among processes using a choreography, and define how communications should be concretely animated by connectors given as constraint automata (e.g., synchronous barriers and asynchronous multi-casts). CR is the first choreography calculus where different communication semantics (determined by connectors) can be freely mixed; since connectors are user-defined, CR also supports many communication semantics that were previously unavailable for choreographies. We develop a static analysis that guarantees that a choreography in CR and its user-defined connectors are compatible, define a compiler from choreographies to a process calculus based on connectors, and prove that compatibility guarantees deadlock-freedom of the compiled process implementations

    Analysis and Verification of Service Interaction Protocols - A Brief Survey

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    Modeling and analysis of interactions among services is a crucial issue in Service-Oriented Computing. Composing Web services is a complicated task which requires techniques and tools to verify that the new system will behave correctly. In this paper, we first overview some formal models proposed in the literature to describe services. Second, we give a brief survey of verification techniques that can be used to analyse services and their interaction. Last, we focus on the realizability and conformance of choreographies.Comment: In Proceedings TAV-WEB 2010, arXiv:1009.330

    Neural-Augmented Static Analysis of Android Communication

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    We address the problem of discovering communication links between applications in the popular Android mobile operating system, an important problem for security and privacy in Android. Any scalable static analysis in this complex setting is bound to produce an excessive amount of false-positives, rendering it impractical. To improve precision, we propose to augment static analysis with a trained neural-network model that estimates the probability that a communication link truly exists. We describe a neural-network architecture that encodes abstractions of communicating objects in two applications and estimates the probability with which a link indeed exists. At the heart of our architecture are type-directed encoders (TDE), a general framework for elegantly constructing encoders of a compound data type by recursively composing encoders for its constituent types. We evaluate our approach on a large corpus of Android applications, and demonstrate that it achieves very high accuracy. Further, we conduct thorough interpretability studies to understand the internals of the learned neural networks.Comment: Appears in Proceedings of the 2018 ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE
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