Javier Troya
Antonio Ruiz-Cortés
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Abstract
Model transformations play a cornerstone role in Model-Driven Engineering (MDE), as they provide the essential mechanisms for manipulating and transforming models. The correctness of software built using MDE techniques greatly relies on the correctness of model transformations. However, it is challenging and error prone to debug them, and the situation gets more critical as the size and complexity of model transformations grow, where manual debugging is no longer possible.
Spectrum-Based Fault Localization (SBFL) uses the results of test cases and their corresponding code coverage information to estimate the likelihood of each program component (e.g., statements) of being faulty. In this article we present an approach to apply SBFL for locating the faulty rules in model transformations. We evaluate the feasibility and accuracy of the approach by comparing the effectiveness of 18 different state-of-the-art SBFL techniques at locating faults in model transformations. Evaluation results revealed that the best techniques, namely Kulcynski2, Mountford, Ochiai, and Zoltar, lead the debugger to inspect a maximum of three rules to locate the bug in around 74% of the cases. Furthermore, we compare our approach with a static approach for fault localization in model transformations, observing a clear superiority of the proposed SBFL-based method.
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- Spectrum-Based Fault Localization in Model Transformations
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Fault density, fault types, and spectra-based fault localization
This paper presents multiple empirical experiments that investigate the impact of fault quantity and fault type on statistical, coverage-based fault localization techniques and fault-localization interference. Fault-localization interference is a ...
Spectrum‐based fault localization using empirical mode decomposition algorithm
AbstractSpectrum‐based fault localization (SBFL) is considered as the most popular lightweight fault localization method. However, pure SBFL is proved to be tedious and time‐consuming for programmers to detect faults. This is because the suspiciousness ...
We propose a new spectral fault localization technique using empirical mode decomposition method to improve the accuracy of automatic software debugging. To accomplish that, the faulty program is evaluated by spectrum‐based fault localization, and then, ...
On the influence of multiple faults on coverage-based fault localization
ISSTA '11: Proceedings of the 2011 International Symposium on Software Testing and AnalysisThis paper presents an empirical study on the effects of the quantity of faults on statistical, coverage-based fault localization techniques. The former belief was that the effectiveness of fault-localization techniques was inversely proportional to the ...
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