nips nips2009 nips2009-143 nips2009-143-reference knowledge-graph by maker-knowledge-mining

143 nips-2009-Localizing Bugs in Program Executions with Graphical Models


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Author: Laura Dietz, Valentin Dallmeier, Andreas Zeller, Tobias Scheffer

Abstract: We devise a graphical model that supports the process of debugging software by guiding developers to code that is likely to contain defects. The model is trained using execution traces of passing test runs; it reflects the distribution over transitional patterns of code positions. Given a failing test case, the model determines the least likely transitional pattern in the execution trace. The model is designed such that Bayesian inference has a closed-form solution. We evaluate the Bernoulli graph model on data of the software projects AspectJ and Rhino. 1


reference text

[1] James A. Jones and Mary J. Harrold. Empirical evaluation of the tarantula automatic faultlocalization technique. In Proceedings of the International Conference on Automated Software Engineering, 2005.

[2] Ben Liblit, Mayur Naik, Alice X. Zheng, Alex Aiken, and Michael I. Jordan. Scalable statistical bug isolation. In Proceedings of the Conference on Programming Language Design and Implementation, 2005.

[3] Trishul Chilimbi, Ben Liblit, Krishna Mehra, Aditya Nori, and Kapil Vaswani. Holmes: Effective statistical debugging via efficient path profiling. In Proceedings of the International Conference on Software Engineering, 2009.

[4] David Andrzejewski, Anne Mulhern, Ben Liblit, and Xiaojin Zhu. Statistical debugging using latent topic models. In Proceedings of the European Conference on Machine Learning, 2007.

[5] David M. Blei, Andrew Y. Ng, and Michael I. Jordan. Latent Dirichlet allocation. Journal of Machine Learning Research, 3:993–1022, 2003.

[6] Tom Minka and John Winn. Gates. In Advances in Neural Information Processing Systems, 2008.

[7] Hal Daume III. Hbc: Hierarchical Bayes Compiler. http://hal3.name/HBC, 2007.

[8] Andrew McCallum and Kamal Nigam. A comparison of event models for Naive Bayes text classification. In Proceedings of the AAAI Workshop on Learning for Text Categorization, 1998.

[9] Hyunsook Do, Sebastian Elbaum, and Gregg Rothermel. Supporting controlled experimentation with testing techniques: An infrastructure and its potential impact. Empirical Software Engineering, 10(4):405–435, October 2005.

[10] Lionel C. Briand. A critical analysis of empirical research in software testing. In Proceedings of the Symposium on Empirical Software Engineering and Measurement, 2007.

[11] Ben Liblit, Mayur Naik, Alice X. Zheng, Alex Aiken, and Michael I. Jordan. Public deployment of cooperative bug isolation. In Proceedings of the Workshop on Remote Analysis and Measurement of Software Systems, 2004.

[12] Valentin Dallmeier and Thomas Zimmermann. Extraction of bug localization benchmarks from history. In Proceedings of the International Conference on Automated Software Engineering, 2007. 9