论文信息 - Localizing Bugs in Program Executions with Graphical Models

Localizing Bugs in Program Executions with Graphical Models

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] Thomas P. Minka,et al. Gates , 2008, NIPS.

[2] Gregg Rothermel,et al. Supporting Controlled Experimentation with Testing Techniques: An Infrastructure and its Potential Impact , 2005, Empirical Software Engineering.

[3] Lionel C. Briand. A Critical Analysis of Empirical Research in Software Testing , 2007, First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007).

[4] Andrew McCallum,et al. A comparison of event models for naive bayes text classification , 1998, AAAI 1998.

[5] Michael I. Jordan,et al. Scalable statistical bug isolation , 2005, PLDI '05.

[6] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[7] Michael I. Jordan,et al. Advances in Neural Information Processing Systems 30 , 1995 .

[8] Ben Liblit,et al. Public deployment of cooperative bug isolation , 2004, ICSE 2004.

[9] Xiaojin Zhu,et al. Statistical Debugging Using Latent Topic Models , 2007, ECML.

[10] Mary Jean Harrold,et al. Empirical evaluation of the tarantula automatic fault-localization technique , 2005, ASE.

[11] Thomas Zimmermann,et al. Extraction of bug localization benchmarks from history , 2007, ASE.

[12] Trishul M. Chilimbi,et al. HOLMES: Effective statistical debugging via efficient path profiling , 2009, 2009 IEEE 31st International Conference on Software Engineering.