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Analysis Framework

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Masoud Esmaili – One of the best experts on this subject based on the ideXlab platform.

  • Application of a new sensitivity Analysis Framework for voltage contingency ranking
    IEEE Transactions on Power Systems, 2005
    Co-Authors: Nima Amjady, Masoud Esmaili

    Abstract:

    In this paper, a new sensitivity Analysis Framework for voltage contingency ranking has been presented. The proposed sensitivity Analysis is a combination of linear sensitivities and eigenvalue Analysis. The sensitivity Analysis Framework can determine the voltage stability status of the power system due to the occurrence of each contingency. Moreover, stability margin or instability depth of the post-contingency state is determined in the Framework. In other words, a severity index is obtained for each voltage contingency and so the contingencies can be ranked. This rank shows bottlenecks of the power system in the priority order, a property that is a key issue for both planners and operators of the power system. The proposed method can also evaluate islanding contingencies as well as the nonislanding ones. Moreover, the method can consider the generator contingencies in addition to the branch contingencies in a unique Framework. The proposed method has been tested on the New Zealand test system and Iran’s power network. Obtained results, discussed comprehensively, confirm the validity of the developed approach.

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Johann Blieberger – One of the best experts on this subject based on the ideXlab platform.

  • A symbolic Analysis Framework for static Analysis of imperative programming languages
    Journal of Systems and Software, 2012
    Co-Authors: Bernd Burgstaller, Bernhard Scholz, Johann Blieberger

    Abstract:

    Highlights? We present a generic symbolic Analysis Framework for imperative programming languages. ? Our Framework computes all valid variable bindings at a given program point. ? Variable bindings are kept in an algebraic structure called supercontext. ? Path expression algebra models control flow information of programs. ? A homomorphism maps path expressions into the symbolic domain. We present a generic symbolic Analysis Framework for imperative programming languages. Our Framework is capable of computing all valid variable bindings of a program at given program points. This information is invaluable for domain-specific static program analyses such as memory leak detection, program parallelization, and the detection of superfluous bound checks, variable aliases and task deadlocks.We employ path expression algebra to model the control flow information of programs. A homomorphism maps path expressions into the symbolic domain. At the center of the symbolic domain is a compact algebraic structure called supercontext. A supercontext contains the complete control and data flow Analysis information valid at a given program point.Our approach to compute supercontexts is based purely on algebra and is fully automated. This novel representation of program semantics closes the gap between program Analysis and computer algebra systems, which makes supercontexts an ideal symbolic intermediate representation for all domain-specific static program analyses.Our approach is more general than existing methods because it can derive solutions for arbitrary (even intra-loop and nested loop) nodes of reducible and irreducible control flow graphs. We prove the correctness of our symbolic Analysis method. Our experimental results show that the problem sizes arising from real-world applications such as the SPEC95 benchmark suite are tractable for our symbolic Analysis Framework.

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Bliebergerjohann – One of the best experts on this subject based on the ideXlab platform.

  • A symbolic Analysis Framework for static Analysis of imperative programming languages
    Journal of Systems and Software, 2012
    Co-Authors: Burgstallerbernd, Scholzbernhard, Bliebergerjohann

    Abstract:

    Highlights We present a generic symbolic Analysis Framework for imperative programming languages. Our Framework computes all valid variable bindings at a given program point. Variable bindings are …

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