A set of metrics for characterizing simulink model comprehension

  • Erik Aceiro Antonio Federal University of São Carlos, Department of Computer Science, São Carlos, Brazil
  • Fabiano Ferrari Federal University of São Carlos, Department of Computer Science, São Carlos, Brazil
  • Glauco A. de P. Caurin University of São Paulo, Center of Robot São Carlos, Brazil
  • Sandra C. P. F. Fabbri Federal University of São Carlos, Department of Computer Science, São Carlos, Brazil
Keywords: Simulink, Metrics, Comprehension, Embedded Systems

Abstract

Simulink is a powerful tool for Embedded Systems, playing a key role in dynamic systems modeling. However, far too little attention has been paid to quality of Simulink models. In addition, no research has been found linking the relationship between model complexity and its impact in the comprehension quality of Simulink models. The aim of this paper is to define a set of metrics to support the characterization of Simulink models and to investigate their relationship with the model comprehension property. For this study, we performed a controlled experiment using two versions of a robotic Simulink model — one of them was constructed through the ad hoc development approach and the other one through the re-engineered development approach. The results of the experiment show that the re-engineered model is more comprehensible than the ad hoc model. In summary, the set of metrics collected from each version of the Simulink model suggests an inverse relationship with the model comprehension, i.e., the lower the metrics, the greater the model comprehension.

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References

[1] R. S. Pressman, Software Engineering: A Practitioner’s Approach, 7o ed. McGraw-Hill Higher Education, 2009.
[2] E. A. Antonio, F. Ferrari, e S. Fabbri, “A Systematic Mapping of Architectures for Embedded Software”, in II Conference on Critical Embedded Systems (CBSEC), Campinas, Brazil, 2012, p. 1–6.
[3] R. Obermaisser e H. Kopetz, Orgs., GENESYS: An ARTEMIS Cross-Domain Reference Architecture for Embedded Systems. Suedwestdeutscher Verlag fuer Hochschulschriften, 2009.
[4] M. Olszewska (pląska), Simulink-Specific Design Quality Metrics. Turku Centre for Computer Science, 2011.
[5] G. Menkhaus e B. Andrich, “Metric suite for directing the failure mode analysis of embedded software systems”, Information Systems Journal, p. 266–273, 2005.
[6] C. Cu, Y. Jeppu, S. Hariram, N. N. Murthy, e P. R. Apte, “A new inputoutput based model coverage paradigm for control blocks”, in 2011 IEEE Aerospace Conference, 2011, p. 1–12.
[7] J. Prabhu, “Complexity Analysis of Simulink Models to improve the Quality of Outsourcing in an Automotive Company”, Technical University of Eindhoven (TUE), ago. 2010.
[8] P. Marwedel, Embedded System Design:Embedded Systems Foundations of Cyber-Physical Systems, 2o ed. 2011.
[9] K. Petersen, R. Feldt, S. Mujtaba, e M. Mattsson, “Systematic Mapping Studies in Software engineering”, presented at the 12th International Conference on Evaluation and Assessment in Software Engineering, Bari, Italy, 2008, p. 71–80.
[10] R. Martin, “OO Design Quality Metrics - An Analysis of Dependencies”, in Workshop Pragmatic and Theoretical Directions in Object-Oriented Software Metrics, 1994.
[11] S. Fujiwara, G. von Bochmann, F. Khendek, M. Amalou, e A. Ghedamsi, “Test Selection Based on Finite State Models”, IEEE Trans. Softw. Eng., vol. 17, no 6, p. 591–603, jun. 1991.
[12] S. C. Pinto Ferraz Fabbri, M. E. Delamaro, J. C. Maldonado, e P. C. Masiero, “Mutation analysis testing for finite state machines”, in Software Reliability Engineering, 1994. Proceedings., 5th International Symposium on, 1994, p. 220–229.
[13] S. Henry e D. Kafura, “Software Structure Metrics Based on Information Flow”, IEEE Transactions on Software Engineering, vol. SE-7, no 5, p. 510– 518, set. 1981.
[14] R. C. Martin, “UML Tutorial: Finite State Machines”, Engineering Notebook Column C++ Report, jun. 1998.
[15] G. Freire, L. Pedro, E. Antonio, J. Nepomuceno, G. Caurin, e S. Fabbri, “Applying Reengineering on Simulink Model Assisted by UML Statechart”, in Conference on Critical Embedded Systems (CBSEC), São Carlos, Brazil, 2011, p. 1–6.
[16] C. Wohlin, P. Runeson, M. Host, C. Ohlsson, B. Regnell, e A. Wesslén, Experimentation in Software Engineering: an Introduction. Kluver Academic Publishers, 2000.
[17] V. Basili, G. Caldiera, e D. Rombach, “The goal question metric approach”, in Encyclopedia of Software Engineering, Wiley, 1994.
[18] William Navidi, Statistics for Engineers and Scientists, 3o ed. New York: McGraw-Hill, 2010.
Published
2014-10-01
How to Cite
Antonio, E. A., Ferrari, F., Caurin, G. A. de P., & Fabbri, S. C. P. F. (2014). A set of metrics for characterizing simulink model comprehension. Journal of Computer Science and Technology, 14(02), p. 88-94. Retrieved from http://journal.info.unlp.edu.ar/JCST/article/view/574
Section
Original Articles