The GRID infrastructure provides an aggregation of a wide variety of distributed resources for solving large-scale data intensive problems in various fields. The aim of this paper is to propose a method for grid resou...
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This paper presents a methodology to design automatically a QFT (Quantitative Feedback Theory) robust controller for plants with model uncertainty. The method proposed has as objective to find a QFT robust controller ...
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Abstraction is the key when learning behavioral models of realistic systems, but also the cause of a major problem: the introduction of non-determinism. In this paper, we introduce a method for refining a given abstra...
ISBN:
(纸本)9783642182747
Abstraction is the key when learning behavioral models of realistic systems, but also the cause of a major problem: the introduction of non-determinism. In this paper, we introduce a method for refining a given abstraction to automatically regain a deterministic behavior on-the-fly during the learning process. Thus the control over abstraction becomes part of the learning process, with the effect that detected nondeterminism does not lead to failure, but to a dynamic alphabet abstraction refinement. Like automata learning itself, this method in general is neither sound nor complete, but it also enjoys similar convergence properties even for infinite systems as long as the concrete system itself behaves deterministically, as illustrated along a concrete example.
Program optimization on multi-core systems must preserve the program memory consistency. This paper studies TSO-preserving binary optimization. We introduce a novel approach to formally model TSO-preserving binary opt...
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Program optimization on multi-core systems must preserve the program memory consistency. This paper studies TSO-preserving binary optimization. We introduce a novel approach to formally model TSO-preserving binary optimization based on the formal TSO memory model. The major contribution of the modeling is a sound and complete algorithm to verify TSO-preserving binary optimization with O(N 2 ) complexity. We also developed a dynamic binary optimization system to evaluate the performance impact of TSO-preserving optimization. We show in our experiments that, dynamic binary optimization without memory optimizations can improve performance by 8.1%. TSO-preserving optimizations can further improve the performance by 4.8% to a total 12.9%. Without considering the restriction for TSO-preserving optimizations, the dynamic binary optimization can improve the overall performance to 20.4%.
In this paper, we leverage service-orientation as a means for combining the strengths of the UML-based code generator framework AndroMDA for generating static application aspects with code generators focussing on the ...
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In this paper, we leverage service-orientation as a means for combining the strengths of the UML-based code generator framework AndroMDA for generating static application aspects with code generators focussing on the dynamic aspects. The latter are developed with Genesys, a code generation framework that combines the ideas of model-driven development and service-orientation in order to enable a high-level engineering of code generators. This demonstrates a new level of reusability and even has the potential for full code generation, which elegantly eliminates the need for the typical round-trip engineering in model-driven development environments. We demonstrate the applicability of our approach by means of an example from the field of bioinformatics.
PROPHETS is our flexible framework for the synthesis of processes from libraries of basic services. In this paper we demonstrate how its synthesis strategy can be tailored to the considered application domain. For thi...
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PROPHETS is our flexible framework for the synthesis of processes from libraries of basic services. In this paper we demonstrate how its synthesis strategy can be tailored to the considered application domain. For this purpose, PROPHETS provides a number of configuration options, such as different data exchange formats (e.g. shared variables and pipe lining) for the resulting process, as well as structural and temporal logic constraints for minimizing the inherent search space. We illustrate the impact of adequate synthesis tailoring by contrasting two real-life case studies with diametric characteristics.
In this paper we present a flexible framework for fine tuning the quality of program analysis based on variations, generalizations, and pragmatic extensions of Plotkin's Structured Operational Semantics (SOS). Key...
ISBN:
(纸本)9783642182747
In this paper we present a flexible framework for fine tuning the quality of program analysis based on variations, generalizations, and pragmatic extensions of Plotkin's Structured Operational Semantics (SOS). Key to these variations is the idea of Property-Oriented Expansion, here the non-standard use of the data component in SOS configurations, which ranges from simple abstract interpretations, over arbitrary data flow information, to e.g., temporal constraints. In its most general form, which is characterized by the notion of unifying models, this results in a framework not only for fine-tuning program analysis according to an aspect (quality) of choice, but also for synthesizing orchestrations for service-oriented applications based on loose temporal specifications. From an engineering perspective, the simple interface pattern underlying the unifying models approach was key for realizing our experimental platform. Our experimental results, in particular concerning the state explosion problem, indicate that, in practice, limiting the expansion to the previously determined areas of impact suffices to keep the code growth quite moderate.
Data flow processing is a common task of embedded systems which is usually modeled as a pipeline. Errors in a block of this pipeline can be propagated through it thus leading to unexpected and erroneous behaviors. For...
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Large-scale systems increasingly consist of a mixture of co-dependent software and hardware. The differing nature of software and hardware means that they are often modeled separately and with different approaches. Co...
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Large-scale systems increasingly consist of a mixture of co-dependent software and hardware. The differing nature of software and hardware means that they are often modeled separately and with different approaches. Comodeling is a design strategy that allows hardware/software integration issues to be identified, investigated and resolved in the early stages of development. Previous work described a comodeling approach that integrates Behavior Engineering with Modelica. This paper revisits this approach and introduces a new means of integration that natively executes Behavior Trees in Modelica rather than utilizing external functions. This enhanced integration has several benefits. Firstly, it makes comodeling easier to apply as the comodel is captured solely in Modelica. Secondly, it makes the ability to execute Behavior Trees widely available. Finally, it opens the possibility to use comodeling with other complementary approaches such as the virtual verification of system designs against system requirements.
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