The difficulty of designing such tools in EOO modeling environments is linked to the difficulty of mapping simulation form to the model sources. Furthermore; debugging of complex models consisting of over thousand equations by traversing each equation may be very ineffective; especially when the fault has multiple and not very evident causes.
A model reduction methods is proposed and discussed as a method of verification. With model reduction methods it is possible to identify the most important parts of the model which have contributed to the specific model behavior. Because model reduction can be performed on original model representation; the difficulty of mapping simulation form back to model source is avoided.
Keywords: verification; debugging of EOO models; verification by model reduction
3rd International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools; Oslo; Norway; October 3
 Peter Bunus. Debugging Techniques for Equation-Based Languages. PhD thesis; Link¨oping University; 2004.
 F. E. Cellier and E. Kofman. Continous System Simulation. Springer Science+Business Media; New York; 2006.
 Samuel Y. Chang; Christopher R. Carlson Carlson; and J. Christian Gerdes. A lyapunov function approach to energy based model reduction. In Proceedings of the ASME Dynamic Systems and Control Division – 2001 IMECE; pages 363–370; New York; USA; 2001.
 Sanjay Lall; Petr Krysl; et al. Structure-preserving model reduction for mechanical systems. Physica D; 284:304–318; 2003.
 Loucas Sotiri Louca. An Energy-based Model Reduction Methodology for Automated Modeling. PhD thesis; University of Michigan; 1998.
 S. E. Mattsson and H. Elmqvist. Unit checking and quantity conservation. In Proceedings of the 6th Modelica Conference; pages 13–20; Bielefeld; Germany; 2008.
 Modelica Association. Modelica Specification; version 3.1; 2009. http://www.modelica.org/documents/ ModelicaSpec31.pdf.
 H. Olsson et al. Balanced models in modelica 3.0 for increased model quality. In Proceedings of the 6th Modelica Conference; pages 21–33; Bielefeld; Germany; 2008.
 A. Pop and P. Fritzson. A portable debugger for algorithmic modelica code. In Proceedings of the 4th Internationl Modelica Conference; pages 435–443; Hamburg; Germany; 2005.
 R. Rosenberg and T. Zhou. Power-based model insight. In Proceedings of the ASME WAM Symposium on Automated Modeling for Design; pages 1–67; New York; USA; 1988.
 P. Schwarz et al. A tool-box approach to computer-aided generation of reduced-order models. In Proceedings EUROSIM 2007; Ljubljana; Slovenia; 2007.
 Ralf Sommer; Thomas Halfmann; and Jochen Broz. Automated behavioral modeling and analytical model-order reduction by application of symbolic circuit analysis for multiphysical systems. Simulation Modelling Practice and Theory; 16:1024–1039; 2008.
 R. B. Whitner and O. Balci. Guidelines for selecting and using simulation model verification techniques. Technical report; Department of Computer Science; Virgina Polytechnic Institute and State University; Blacksburg; Virginia; 1989. Technical Report TR-89-17.
 Y. Ye and K. Youcef-Youmi. Model reduction in the physical domain. In Proceedings of the American Control Conference;pages 4486–4490; San Diego; CA; USA; 1999.