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[72] N. T. M. Nguyen and M. L. Soffa. Program representations for
testing wireless sensor network applications. In Workshop on Do-
main specific approaches to software test automation: in conjunc-
tion with the 6th ESEC/FSE joint meeting , DOSTA '07, pages
20-26, New York, NY, USA, 2007. ACM.
[73] P. C. Olveczky and J. Meseguer. Semantics and pragmatics of
real-time maude. Higher Order Symbol. Comput. , 20(1-2):161-196,
June 2007.
[74] P. C. Olveczky and S. Thorvaldsen. Formal modeling, performance
estimation, and model checking of wireless sensor network algo-
rithms in real-time maude. Theor. Comput. Sci. , 410(2-3):254-280,
Feb. 2009.
[75] J. Pei, J. Han, B. Mortazavi-Asl, J. Wang, H. Pinto, Q. Chen,
U. Dayal, and M.-C. Hsu. Mining sequential patterns by pattern-
growth: The prefixspan approach. IEEE TRANSACTIONS ON
KNOWLEDGE AND DATA ENGINEERING , 16(11):1424-1440,
2004.
[76] C. Perrow. Normal Accidents: Living With High-Risk Technologies .
Princeton University Press, 1984.
[77] P. A. Pevzner. Computational Molecular Biology: An Algorithmic
Approach . MIT Press, 2000.
[78] N. Ramanathan, K. Chang, R. Kapur, L. Girod, E. Kohler, and
D. Estrin. Sympathy for the sensor network debugger. In Proceed-
ings of the 3rd international conference on Embedded networked
sensor systems (SenSys'05) , pages 255-267, 2005.
[79] R. Sasnauskas, O. Landsiedel, M. Alizai, C. Weise, S. Kowalewski,
and K. Wehrle. Kleenet: Discovering insidious interaction bugs in
wireless sensor networks before deployment. In In Proc. of the 9th
ACM/IEEE International Conference on Information Processing
in Sensor Networks (IPSN) , pages 186-196, Stockholm, Sweden,
April 2010.
[80] R. Sasnauskas, J. A. B. Link, M. H. Alizai, and K. Wehrle. Kleenet:
automatic bug hunting in sensor network applications. In Pro-
ceedings of the 6th ACM conference on Embedded network sensor
systems , SenSys '08, pages 425-426, New York, NY, USA, 2008.
ACM.
[81] E. Seo, M. M. H. Khan, P. Mohapatra, J. Han, and T. Abdelzaher.
Exposing complex bug-triggering conditions in distributed systems
via graph mining. In Proceedings of the 2011 International Confer-
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