A theory of diagnosis from first principles
Artificial Intelligence
Abstract debugging of higher-order imperative languages
PLDI '93 Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation
Bandera: extracting finite-state models from Java source code
Proceedings of the 22nd international conference on Software engineering
Quickly detecting relevant program invariants
Proceedings of the 22nd international conference on Software engineering
On the relationship between model-based debugging and program slicing
Artificial Intelligence
POPL '77 Proceedings of the 4th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Predicate Abstraction of ANSI-C Programs Using SAT
Formal Methods in System Design
Explaining abstract counterexamples
Proceedings of the 12th ACM SIGSOFT twelfth international symposium on Foundations of software engineering
Locating causes of program failures
Proceedings of the 27th international conference on Software engineering
No faults in structure?: how to diagnose hidden interactions
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
What went wrong: explaining counterexamples
SPIN'03 Proceedings of the 10th international conference on Model checking software
A formalization of program debugging in the situation calculus
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Exploiting count spectra for Bayesian fault localization
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
Simultaneous debugging of software faults
Journal of Systems and Software
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Developing model-based automatic debugging strategies has been an active research area for several years. We present a model-based debugging approach that is based on Abstract Interpretation, a technique borrowed from program analysis. The Abstract Interpretation mechanism is integrated with a classical model-based reasoning engine. We test the approach on sample programs and provide the first experimental comparison with earlier models used for debugging. The results show that the Abstract Interpretation based model provides more precise explanations than previous models or standard non-model based approaches.