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Jian-Wan Ding, Li-Ping Chen, Fan-Li Zhou. A Component-Based Debugging Approach for Detecting Structural Inconsistencies in Declarative Equation Based Models[J]. Journal of Computer Science and Technology, 2006, 21(3): 450-458.
Citation: Jian-Wan Ding, Li-Ping Chen, Fan-Li Zhou. A Component-Based Debugging Approach for Detecting Structural Inconsistencies in Declarative Equation Based Models[J]. Journal of Computer Science and Technology, 2006, 21(3): 450-458.

A Component-Based Debugging Approach for Detecting Structural Inconsistencies in Declarative Equation Based Models

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  • Received Date: May 23, 2005
  • Revised Date: February 15, 2006
  • Published Date: May 14, 2006
  • Object-oriented modeling with declarative equation based languages oftenunconsciously leads to structural inconsistencies. Component-baseddebugging is a new structural analysis approach that addresses thisproblem by analyzing the structure of each component in a model toseparately locate faulty components. The analysis procedure isperformed recursively based on the depth-first rule. It first generatesfictitious equations for a component to establish a debuggingenvironment, and then detects structural defects by using graphtheoretical approaches to analyzing the structure of the system ofequations resulting from the component. The proposed method canautomatically locate components that cause the structuralinconsistencies, and show the user detailed error messages. Thisinformation can be a great help in finding and localizing structuralinconsistencies, and in some cases pinpoints them immediately.
  • [1]
    Bunus P, Fritzson P. Automated static analysis of equation-based components. Simulation: Trans. the Society for Modeling and Simulation International, 2004, 80(8): 321--345.
    [2]
    Mattsson S E. Simulation of object-oriented continuous time models.Mathematics and Computers in Simulation, 1995, 39(5-6): 513--518.
    [3]
    Morton W, Collingwood C. An equation analyzer for process models.Computers and Chemical Engineering, 1998, 22(4-5): 571--585.
    [4]
    Reissig G, Feldmann U. A simple and general method for detecting structural inconsistencies in large electrical networks. IEEE Trans. Circuits and Systems I: Fundamental Theory and Applications, 2003, 50(11): 1482--1485.
    [5]
    Fritzson P, Engelson V. Modelica---A unified object-oriented language for system modeling and simulation. Lecture Notes in Computer Science 1445, Springer-Verlag, 1998, pp.67--90.
    [6]
    Elmqvist H, Mattsson S E, Otter M. Modelica---A language for physical system modeling, visualization and interaction. In Proc. the IEEE Symposium on Computer-Aided Control System Design, Hawaii, USA, 1999, pp.630--639.
    [7]
    Fritzson P. Principles of Object-Oriented Modeling and Simulation with Modelica 2.1. IEEE Press, 2003.
    [8]
    Tiller M. Introduction to Physical Modeling with Modelica. Boston: Kluwer Academic, 2001.
    [9]
    Asratian A S, Denley T, H"aggkvist R. Bipartite Graphs and Their Applications. Cambridge University Press, 1998.
    [10]
    Dulmage A L, Mendelsohn N S. Coverings of bipartite graphs. Canadian Journal of Mathematics, 1963, 10: 517--534.
    [11]
    Ait-Aoudia S, Jegou R, Michelucci D. Reduction of constraint systems. In Proc. Compugraphics, Alvor, Portugal, 1993, pp.83--92.
    [12]
    Pothen A, Fan C J. Computing the block triangular form of a sparse matrix. ACM Trans. Mathematical Software, 1990, 16(4): 303--324.
    [13]
    Hopcroft J E, Karp R M. An n5/2 algorithm for maximum matchings in bipartite graphs. SIAM Journal of Computing, 1973, 2(4): 225--231.
    [14]
    Uno T. Algorithms for enumerating all perfect, maximum and maximal matchings in bipartite graphs. Lecture Notes in Computer Science 1350, Springer-Verlag, 1997, pp.92--101.
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