Wodel-Test: a model-based framework for language-independent mutation testing

Gómez‐Abajo, Pablo; Guerra, Esther; Lara, Juan de; Merayo, Mercedes G.

doi:10.1007/s10270-020-00827-0

Cited by 21 publications

(17 citation statements)

References 71 publications

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“…Another interesting scenario is given when we consider distributed systems, possibly with asynchronous communications, whose specifications are represented as a variant of an FSM [65,66]. In order to confront these more complicated formalisms, we can use current work that make it possible to apply a systematic approach to the generation of mutants [67,68]. In principle, it should also be possible to apply BMI even when there is no specification, since an initial random testing phase could be used to produce estimates of input/output pair frequency.…”

Section: Discussionmentioning

confidence: 99%

Using mutual information to test from Finite State Machines: Test suite selection

Ibias

Núñez

Hierons

2021

Information and Software Technology

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Section: Discussionmentioning

confidence: 99%

Using mutual information to test from Finite State Machines: Test suite selection

Ibias

Núñez

Hierons

2021

Information and Software Technology

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“…This is especially crucial when testing reactive models that require many interactions, and thus multiple "back-and-forth" between the test case and the model. Likewise, regarding test quality measurement, while a recent approach aims to provide mutation analysis for xD-SLs [15], this approach is incomplete as it is not yet able to actually run tests cases on the generated mutants.…”

Section: Introductionmentioning

confidence: 99%

“…(ii) to measure the quality of a TDL test suite defined with the proposed approach, we provide an integration of our generic testing approach with the mutation testing framework proposed in [15].…”

Section: Introductionmentioning

confidence: 99%

Advanced testing and debugging support for reactive executable DSLs

et al. 2022

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Executable Domain-Specific Languages (xDSLs) allow the definition and the execution of behavioral models. Some behavioral models are reactive, meaning that during their execution, they accept external events and react by exposing events to the external environment. Since complex interaction may occur between the reactive model and the external environment, they should be tested as early as possible to ensure the correctness of their behavior. In this paper, we propose a set of generic testing facilities for reactive xDSLs using the standardized Test Description Language (TDL). Given a reactive xDSL, we generate a TDL library enabling the domain experts to write and run event-driven TDL test cases for conforming reactive models. To further support the domain expert, the approach integrates interactive debugging to help in localizing defects, and mutation analysis to measure the quality of test cases. We evaluate the level of genericity of the approach by successfully writing,

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“…Hence, test suite is applied for the different versions of the source program. The failure of the test function indicates the presence of mutated codes 5,6 . Mutation score is an important metric utilized to judge the effectiveness of the test suites.…”

Section: Introductionmentioning

confidence: 99%

“…The failure of the test function indicates the presence of mutated codes. 5,6 Mutation score is an important metric utilized to judge the effectiveness of the test suites. The ratio of total mutant identified to entered mutant minus equivalent mutant is known as mutation score.…”

Section: Introductionmentioning

confidence: 99%

Equivalent mutant identification using hybrid wavelet convolutional rain optimization

Jammalamadaka

Parveen

2021

Softw Pract Exp

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Mutation testing is a significant software testing approach that identifies the faults present in the source codes and the potentiality of the test cases in detecting the mutated codes. In this testing approach, equivalent mutant detection is complicated as the test cases will not identify the mutated codes from the source program. To overcome this problem, the article proposes a novel hybrid strategy known as the hybrid wavelet convolutional rain optimization (HWCRO) to classify the equivalent mutants present in the source codes accurately. The proposed technique considers three different classes of equivalent mutants based on the RIPR model and exactly identifies the mutated code. Initially, the features such as the semantic similarity and the information entropy are extracted, and these features are given as the input to the wavelet convolutional neural network (wCNN) classifier. The dimensions of the features are reduced in the convolutional layers using the wavelet function, which enhances the classifier's performance. To improve the classification accuracy, the loss function is minimized with an adaptive rain optimization algorithm (ROA) that iteratively tunes the parameter of wCNN. The proposed approach is compared with the existing classification techniques based on the parameters such as precision, recall, f1-score, and accuracy, and the simulation results yielded 85.17% accuracy value for the proposed approach.

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Wodel-Test: a model-based framework for language-independent mutation testing

Cited by 21 publications

References 71 publications

Using mutual information to test from Finite State Machines: Test suite selection

Using mutual information to test from Finite State Machines: Test suite selection

Advanced testing and debugging support for reactive executable DSLs

Equivalent mutant identification using hybrid wavelet convolutional rain optimization

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