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FPA-FL: Incorporating Static Fault-proneness Analysis into Statistical Fault Localization
Despite the proven applicability of the statistical methods in automatic...
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Selecting Fault Revealing Mutants
Mutant selection refers to the problem of choosing, among a large number...
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IBIR: Bug Report driven Fault Injection
Much research on software engineering and software testing relies on exp...
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Network-Clustered Multi-Modal Bug Localization
Developers often spend much effort and resources to debug a program. To ...
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Termination Analysis of Polynomial Programs with Equality Conditions
In this paper, we investigate the termination problem of a family of pol...
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Truth Discovery with Memory Network
Truth discovery is to resolve conflicts and find the truth from multiple...
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CADET: A Systematic Method For Debugging Misconfigurations using Counterfactual Reasoning
Modern computing platforms are highly-configurable with thousands of int...
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Inforence: Effective Fault Localization Based on Information-Theoretic Analysis and Statistical Causal Inference
In this paper, a novel approach, Inforence, is proposed to isolate the suspicious codes that likely contain faults. Inforence employs a feature selection method, based on mutual information, to identify those bug-related statements that may cause the program to fail. Because the majority of a program faults may be revealed as undesired joint effect of the program statements on each other and on program termination state, unlike the state-of-the-art methods, Inforence tries to identify and select groups of interdependent statements which altogether may affect the program failure. The interdependence amongst the statements is measured according to their mutual effect on each other and on the program termination state. To provide the context of failure, the selected bug-related statements are chained to each other, considering the program static structure. Eventually, the resultant cause-effect chains are ranked according to their combined causal effect on program failure. To validate Inforence, the results of our experiments with seven sets of programs include Siemens suite, gzip, grep, sed, space, make and bash are presented. The experimental results are then compared with those provided by different fault localization techniques for the both single-fault and multi-fault programs. The experimental results prove the outperformance of the proposed method compared to the state-of-the-art techniques.
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