Fate and free will in error traces

Jin, Hyunjong; Ravi, Kavita; Somenzi, Fabio

doi:10.1007/s10009-004-0146-9

Cited by 59 publications

(56 citation statements)

References 20 publications

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“…Jin, Ravi, and Somenzi proposed a game-like explanation (directed more at hardware than software systems) in which an adversary tries to force the system into error [14]. Of these, only JPF uses a (weak) notion of distance between traces, and it cannot solve for nearest successful executions.…”

Section: Related Workmentioning

confidence: 99%

Error Explanation with Distance Metrics

Groce

2004

Tools and Algorithms for the Construction and Analysis of Systems

135

187

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Abstract. In the event that a system does not satisfy a specification, a model checker will typically automatically produce a counterexample trace that shows a particular instance of the undesirable behavior. Unfortunately, the important steps that follow the discovery of a counterexample are generally not automated. The user must first decide if the counterexample shows genuinely erroneous behavior or is an artifact of improper specification or abstraction. In the event that the error is real, there remains the difficult task of understanding the error well enough to isolate and modify the faulty aspects of the system. This paper describes an automated approach for assisting users in understanding and isolating errors in ANSI C programs. The approach is based on distance metrics for program executions. Experimental results show that the power of the model checking engine can be used to provide assistance in understanding errors and to isolate faulty portions of the source code.

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Section: Related Workmentioning

confidence: 99%

Error Explanation with Distance Metrics

Groce

2004

Tools and Algorithms for the Construction and Analysis of Systems

135

187

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“…In [25], the authors introduce the notion of neighborhood of counterexamples which can be used to understand the cause of counter-examples. A different approach based on game-theoretic techniques is put forth in [20] where counter-examples are augmented into free segments (choices) and fated segments (unavoidable). Errors are most likely to be removed by careful selection of free segments.…”

Section: Related Workmentioning

confidence: 99%

Localizing Program Errors for Cimple Debugging

Basu

Saha

Smolka

2004

Lecture Notes in Computer Science

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Abstract. We present automated techniques for the explanation of counter-examples, where a counter-example should be understood as a sequence of program statements. Our approach is based on variable dependency analysis and is applicable to programs written in Cimple, an expressive subset of the C programming language. Central to our approach is the derivation of a focus-statement sequence (FSS) from a given counter-example: a subsequence of the counter-example containing only those program statements that directly or indirectly affect the variable valuation leading to the program error behind the counter-example. We develop a ranking procedure for FSSs where FSSs of higher rank are conceptually easier to understand and correct than those of lower rank. We also analyze constraints over uninitialized variables in order to localize program errors to specific program segments; this often allows the user to subsequently take appropriate debugging measures. We have implemented our techniques in the FocusCheck model checker, which efficiently checks for assertion violations in Cimple programs on a perprocedure basis. The practical utility of our approach is illustrated by its successful application to a fast, linear-time median identification algorithm commonly used in statistical analysis and in the Resolution Advisory module of the Traffic Collision Avoidance System.

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“…They constitute the key to successful abstraction-refinement techniques [10], and are at the core of obtaining feasible schedules in e.g., timed model checking [8]. As a result, advanced counterexample generation and analysis techniques have intensively been investigated, see e.g., [21,7,13].…”

Section: Introductionmentioning

confidence: 99%

Counterexamples in Probabilistic Model Checking

Han

Katoen

Tools and Algorithms for the Construction and Analysis of Systems

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Abstract. This paper considers algorithms for counterexample generation for (bounded) probabilistic reachability properties in fully probabilistic systems. Finding the strongest evidence (i.e, the most probable path) violating a (bounded) until-formula is shown to be reducible to a single-source (hop-constrained) shortest path problem. Counterexamples of smallest size that are mostly deviating from the required probability bound can be computed by adopting (partially new hopconstrained) k shortest paths algorithms that dynamically determine k.

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Fate and free will in error traces

Cited by 59 publications

References 20 publications

Error Explanation with Distance Metrics

Error Explanation with Distance Metrics

Localizing Program Errors for Cimple Debugging

Counterexamples in Probabilistic Model Checking

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