Spectrum-Based Multiple Fault Localization

By Rui Abreu, Peter Zoeteweij, A. V. Gemund. 2009 IEEE/ACM International Conference on Automated Software Engineering, 2009

433 citations recorded by the source corpus.

Fault diagnosis approaches can generally be categorized into spectrum-based fault localization (SFL, correlating failures with abstractions of program traces), and model-based diagnosis (MBD, logic reasoning over a behavioral model). Although MBD approaches are inherently more accurate than SFL, their high computational complexity prohibits application to large programs. We present a framework to combine the best of both worlds, coined BARINEL. The program is modeled using abstractions of program traces (as in SFL) while Bayesian reasoning is used to deduce multiple-fault candidates and their probabilities (as in MBD). A particular feature of BARINEL is the usage of a probabilistic component model that accounts for the fact that faulty components may fail intermittently. Experimental results on both synthetic and real software programs show that BARINEL typically outperforms current SFL approaches at a cost complexity that is only marginally higher. In the context of single faults this superiority is established by formal proof.

Subfields: Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/6c79fde9539ae9df401f3841a4410b12a31fc7f6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Mike Papadakis
2. Yves Le Traon
3. Yihao Li
4. Ruizhi Gao
5. Rui Abreu
6. W. E. Wong
7. Tao Xie
8. Franz Wotawa

In Software

1. Yves Le Traon
2. Mike Papadakis
3. Yihao Li
4. Ruizhi Gao
5. W. E. Wong
6. Franz Wotawa
7. Rui Abreu
8. Tao Xie

Citations in the corpus

• Fault Analysis and Debugging of Microservice Systems: Industrial Survey, Benchmark System, and Empirical Study (2018, methodology): “There has been some research on debugging concurrent programs [38], [59], [60] and distributed systems [10], [61], [62], [63].”
• Metallaxis‐FL: mutation‐based fault localization (2015, methodology): “[40] suggested using Bayesian reasoning in assigning suspiciousness values to the program spectra.”
• Evaluating and Improving Fault Localization (2017, neutral): “(0.09) [-0.000, 0.003] (12–233–65) Barinel > Tarantula [4] yes (-0.05) [-0.001, -0.000] (9–2986–0) (insig.)”
• A Survey on Software Fault Localization (2016, methodology): “A potential weakness of most techniques based on Bayesian reasoning (e.g., [14], [64], [193]) is that they all assume program components fail independently; in other words, interferences between multiple bugs are ignored, which is not necessarily the case in practice.”