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Isolating cause-effect chains from computer programs
Abstract
Consider the execution of a failing program as a sequence of program states. Each state induces the following state, up to the failure. Which variables and values of a program state are relevant for the failure? We show how the Delta Debugging algorithm isolates the relevant variables and values by systematically narrowing the state difference between a passing run and a failing run---by assessing the outcome of altered executions to determine wether a change in the program state makes a difference in the test outcome. Applying Delta Debugging to multiple states of the program automatically reveals the cause-effect chain of the failure---that is, the variables and values that caused the failure.In a case study, our prototype implementation successfully isolated the cause-effect chain for a failure of the GNU C compiler: "Initially, the C program to be compiled contained an addition of 1.0; this caused an addition operator in the intermediate RTL representation; this caused a cycle in the RTL tree---and this caused the compiler to crash."
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Cited by
A Survey on Software Fault Localization
Wong, W. E., Gao, R., Li, Y., Abreu, R., & Wotawa, F. (2016) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2016.2521368 · Cited by 1,110
Designing the whyline: a debugging interface for asking questions about program behavior
Ko, A. J., & Myers, B. A. (2004) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/985692.985712 · Cited by 361
SOBER: statistical model-based bug localization
Liu, C., Yan, X., Fei, L., Han, J., & Midkiff, S. P. (2005) · Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering · doi:10.1145/1081706.1081753 · Cited by 357
A theoretical analysis of the risk evaluation formulas for spectrum-based fault localization
Xie, X., Chen, T. Y., Kuo, F.-C., & Xu, B. (2013) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/2522920.2522924 · Cited by 353
Understanding and detecting real-world performance bugs
Jin, G., Song, L., Shi, X., Scherpelz, J., & Lu, S. (2012) · Proceedings of the 33rd ACM SIGPLAN Conference on Programming Language Design and Implementation · doi:10.1145/2254064.2254075 · Cited by 304
Metadata
- Authors
- Zeller, A.
- Venue
- Proceedings of the 10th ACM SIGSOFT symposium on Foundations of software engineering
- Publisher
- ACM
- Published
- 2002-11-18
- Pages
- 1-10
- OpenAlex
- W2121081915
- Cited by
- 530
- References
- 0
- FWCI
- 13.83
- Type
- conference paper
- Language
- en
- Open access
- closed
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