The program dependence graph and its use in optimization
ACM Transactions on Programming Languages and Systems (TOPLAS)
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
Practical Software Maintenance: Best Practices for Managing Your Software Investment
Practical Software Maintenance: Best Practices for Managing Your Software Investment
ICSE '81 Proceedings of the 5th international conference on Software engineering
Locating causes of program failures
Proceedings of the 27th international conference on Software engineering
Scalable statistical bug isolation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
Locating faulty code using failure-inducing chops
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
The pitfalls of verifying floating-point computations
ACM Transactions on Programming Languages and Systems (TOPLAS)
Fault localization using value replacement
ISSTA '08 Proceedings of the 2008 international symposium on Software testing and analysis
Mitigating the confounding effects of program dependences for effective fault localization
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
Statistical debugging with elastic predicates
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
A Survey of Automated Techniques for Formal Software Verification
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Reducing confounding bias in predicate-level statistical debugging metrics
Proceedings of the 34th International Conference on Software Engineering
Investigating unexpected outcomes through the application of statistical debuggers
Proceedings of the Winter Simulation Conference
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In order to effectively deal with increased complexity and production pressures for the development of safety-critical systems, organizations need automated assistance in program analysis and testing. This need is intensified for systems that make heavy use of floating-point computations. Challenges related to the use of floating-point computations exist in the fields of testing, formal verification and debugging. While testing and formal verification provide mechanisms to identify possible failures within safety-critical systems, debugging techniques are employed to automatically isolate the cause of the failure. Recent advances in predicate-level statistical debugging have addressed localizing faults due to floating-point computations. Here, we present a methodology to modify the composition of a test suite to enable predicate-level statistical debuggers to more effectively isolate the causes of failures in safety-critical systems. Our methodology makes test suites significantly more effective for a class of debuggers, including those built to address faults due to floating-point computations.