Abstract
Current model-based approaches to software debugging use static program analysis to derive a model of the program. In contrast, in the software engineering domain diagnosis approaches are based on analyzing dynamic execution behavior. We present a model-based approach where the program model is derived from dynamic execution behavior, and evaluate its diagnostic performance on the Siemens software benchmark, extended by us to accommodate multiple faults. We show that our approach outperforms other model-based software debugging techniques, which is partly due to the use of De Kleer’s intermittency model to account for the variability of software component behavior.
This work has been carried out as part of the TRADER project under the responsibility of the Embedded Systems Institute. This project is partially supported by the Netherlands Ministry of Economic Affairs under the BSIK03021 grant.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abreu, R., Zoeteweij, P., van Gemund, A.J.C.: On the accuracy of spectrum-based fault localization. In: Proc. TAIC PART 2007 (2007)
Abreu, R., Zoeteweij, P., van Gemund, A.J.C.: A Dynamic Modeling Approach to Software Multiple-fault Localization. In: Proc. DX 2008 (2008)
Abreu, R., Zoeteweij, P., van Gemund, A.J.C.: An observation-based model for fault localization. In: Proc. WODA 2008 (2008)
De Kleer, J.: Diagnosing intermittent faults. In: Proc. DX 2007 (2007)
De Kleer, J., Mackworth, A.K., Reiter, R.: Characterizing diagnoses and systems. Artif. Intell. 56, 197–222 (1992)
De Kleer, J., Williams, B.C.: Diagnosing multiple faults. Artif. Intell. 32(1), 97–130 (1987)
Groce, A.: Error explanation with distance metrics. In: Jensen, K., Podelski, A. (eds.) TACAS 2004. LNCS, vol. 2988, pp. 108–122. Springer, Heidelberg (2004)
Jones, J.A., Harrold, M.J.: Empirical evaluation of the tarantula automatic fault-localization technique. In: Proc. ASE 2005 (2005)
Liu, C., Yan, X., Fei, L., Han, J., Midkiff, S.P.: Sober: Statistical model-based bug localization. In: Proc. ESEC/FSE-13
Mayer, W., Stumptner, M.: Evaluating models for model-based debugging. In: Proc. ASE 2008 (2008)
Pucel, X., Bocconi, S., Picardi, C., Dupre, D., Massuyes, L.: Diagnosability analysis for web services with constraint-based models. In: Proc. DX 2007 (2007)
Reiter, R.: A theory of diagnosis from first principles. Artif. Intell. 32(1), 57–95 (1987)
Renieris, M., Reiss, S.P.: Fault localization with nearest neighbor queries. In: Proc. ASE 2003 (2003)
Wotawa, F., Stumptner, M., Mayer, W.: Model-based debugging or how to diagnose programs automatically. In: Hendtlass, T., Ali, M. (eds.) IEA/AIE 2002. LNCS, vol. 2358, p. 746. Springer, Heidelberg (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Abreu, R., Zoeteweij, P., van Gemund, A.J.C. (2009). A Model-Based Software Reasoning Approach to Software Debugging. In: Chien, BC., Hong, TP. (eds) Opportunities and Challenges for Next-Generation Applied Intelligence. Studies in Computational Intelligence, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92814-0_36
Download citation
DOI: https://doi.org/10.1007/978-3-540-92814-0_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92813-3
Online ISBN: 978-3-540-92814-0
eBook Packages: EngineeringEngineering (R0)