Explaining inconsistent code

Schäf, Martin; Schwartz-Narbonne, Daniel; Wies, Thomas

doi:10.1145/2491411.2491448

Cited by 15 publications

(8 citation statements)

References 38 publications

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“…The use of error invariants [7,13,18,29] is a closely-related fault-localization technique. Error invariants are computed from Craig interpolants along an error trace and capture which states will produce the error from that point on.…”

Section: Related Workmentioning

confidence: 99%

Semantic Fault Localization and Suspiciousness Ranking

Christakis

Heizmann

Mansur

et al. 2019

Tools and Algorithms for the Construction and Analysis of Systems

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Static program analyzers are increasingly effective in checking correctness properties of programs and reporting any errors found, often in the form of error traces. However, developers still spend a significant amount of time on debugging. This involves processing long error traces in an effort to localize a bug to a relatively small part of the program and to identify its cause. In this paper, we present a technique for automated fault localization that, given a program and an error trace, efficiently narrows down the cause of the error to a few statements. These statements are then ranked in terms of their suspiciousness. Our technique relies only on the semantics of the given program and does not require any test cases or user guidance. In experiments on a set of C benchmarks, we show that our technique is effective in quickly isolating the cause of error while out-performing other state-of-the-art faultlocalization techniques.

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Section: Related Workmentioning

confidence: 99%

Semantic Fault Localization and Suspiciousness Ranking

Christakis

Heizmann

Mansur

et al. 2019

Tools and Algorithms for the Construction and Analysis of Systems

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“…Since a flow-sensitive TF represents itself more information, it is larger and more complex than a flow-insensitive TF. Furthermore, as in flow-insensitive TF, it is necessary to construct many TF in order to deal with independent faults because the flow-sensitive TF does not encode all execution paths [23]. Concerning data flowdependent faults, they can be identified with both flow-insensitive and flow-sensitive TF.…”

Section: Importance Of Trace Formulasmentioning

confidence: 99%

A Formula-based Approach for Automatic Fault Localization of Multi-fault Programs

Lamraoui

Nakajima

2016

Journal of Information Processing

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Formula-based fault localization approach is an algorithmic method that is able to provide fine-grained information account for identified root causes. The method combines the SAT-based formal verification techniques with the Reiter's model-based diagnosis theory. This paper adapts the formula-based fault localization method, and introduces a new program encoding, called full flow-sensitive trace formula. This encoding is particularly useful for programs with multiple faults. Furthermore, we improve the efficiency of computing the potential root causes by using the push & pop mechanism of the Yices solver. We implemented the method in a tool, SNIPER, which was applied to some benchmarks. All single and multiple faults were successfully identified and discriminated.

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“…FBFL techniques represent an error trace using an SMT formula and analyze it to find suspicious locations. These techniques include using error invariants [6,14,17,40], maximum satisfiability [21,24,25], and weakest preconditions [7]. What we were able to show in this paper, is that the methods of [6,14,21] are not must.…”

Section: Related Workmentioning

confidence: 72%

“…Other approaches for fault localization include spectrum-based (SBFL) [1,13,20,31,44], mutation-based (MBFL) [15,18,30,35] and formula-based (FBFL) [7,14,17,21,40]. Both SBFL and MBFL techniques compute the suspiciousness of a statement using coverage information from failing and passing test executions.…”

Section: Related Workmentioning

confidence: 99%

Must Fault Localization for Program Repair

Rothenberg

Grumberg

2020

Lecture Notes in Computer Science

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This work is concerned with fault localization for automated program repair. We define a novel concept of a must location set. Intuitively, such a set includes at least one program location from every repair for a bug. Thus, it is impossible to fix the bug without changing at least one location from this set. A fault localization technique is considered a must algorithm if it returns a must location set for every buggy program and every bug in the program. We show that some traditional fault localization techniques are not must. We observe that the notion of must fault localization depends on the chosen repair scheme, which identifies the changes that can be applied to program statements as part of a repair. We develop a new algorithm for fault localization and prove that it is must with respect to commonly used schemes in automated program repair. We incorporate the new fault localization technique into an existing mutation-based program repair algorithm. We exploit it in order to prune the search space when a buggy mutated program has been generated. Our experiments show that must fault localization is able to significantly speed-up the repair process, without losing any of the potential repairs.

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Explaining inconsistent code

Cited by 15 publications

References 38 publications

Semantic Fault Localization and Suspiciousness Ranking

Semantic Fault Localization and Suspiciousness Ranking

A Formula-based Approach for Automatic Fault Localization of Multi-fault Programs

Must Fault Localization for Program Repair

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