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Automatic Testing of Design Faults in MapReduce Applications

New processing models are being adopted in Big Data engineering to overcome the limitations of traditional technology. Among them, MapReduce stands out by allowing for the processing of large volumes of data over a distributed infrastructure that can change during runtime. The developer only designs the functionality of the program and its execution is managed by a distributed system. As a consequence, a program can behave differently at each execution because it is automatically adapted to the resources available at each moment. Therefore, when the program has a design fault, this could be revealed in some executions and masked in others. However, during testing, these faults are usually masked because the test infrastructure is stable, and they are only revealed in production because the environment is more aggressive with infrastructure failures, among other reasons. This paper proposes new testing techniques that aimed to detect these design faults by simulating different infrastructure configurations. The testing techniques generate a representative set of infrastructure configurations that as whole are more likely to reveal failures using random testing, and partition testing together with combinatorial testing. The techniques are automated by using a test execution engine called MRTest that is able to detect these faults using only the test input data, regardless of the expected output. Our empirical evaluation shows that MRTest can automatically detect these design faults within a reasonable time.

Performance metamorphic testing: A Proof of concept

Sergio Segura, Javier Troya, Amador Durán, Antonio Ruiz-Cortés. «Performance Metamorphic Testing: A Proof of Concept». Information and Software Technology, 98:1-4, 2018. https://doi.org/10.1016/j.infsof.2018.01.013Impact indicators:- JCR FI: 2.62 TOP 15% (Q1) CS/SE.- 2 citations in GScholar (http://bit.ly/2WnrYYj)A preliminary version of this paper was presented in the track of New Ideas an Emerging Results at ICSE 2017, with an acceptance rate of 16% (14 papers accepted out of 85 submissions) [1]. All four reviewers agreed on the value of the work with an overall score of 9 (out of 12), and a novelty score of 11 (out of 12).[1] Sergio Segura, Javier Troya, Amador Durán, Antonio Ruiz-Cortés. «Performance metamorphic testing: motivation and challenges». In Proceedings of the 39th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE NIER’17) Track. IEEE Press, Piscataway, NJ, USA, 7-10, 2017. [Acceptance rate: 16%. Main track ranked as Class 1 in SCIE Ranking] https://doi.org/10.1109/ICSE-NIER.2017.16

Automated inference of likely metamorphic relations for model transformations (YA PUBLICADO)

Model transformations play a cornerstone role in Model-Driven Engineering (MDE) as they provide the essential mechanisms for manipulating and transforming models. Checking whether the output of a model transformation is correct is a manual and errorprone task, referred to as the oracle problem. Metamorphic testing alleviates the oracle problem by exploiting the relations among different inputs and outputs of the program under test, so-called metamorphic relations (MRs). One of the main challenges in metamorphic testing is the automated inference of likely MRs. This paper proposes an approach to automatically infer likely MRs for ATL model transformations, where the tester does not need to have any knowledge of the transformation. The inferred MRs aim at detecting faults in model transformations in three application scenarios, namely regression testing, incremental transformations and migrations among transformation languages. In the experiments performed, the inferred likely MRs have proved to be quite accurate, with a precision of 96.4% from a total of 4101 true positives out of 4254 MRs inferred. Furthermore, they have been useful for identifying mutants in regression testing scenarios, with a mutation score of 93.3%. Finally, our approach can be used in conjunction with current approaches for the automatic generation of test cases. Artículo publicado en The Journal of Systems and Software, Vol 136, pp 188-208 (Available Online May 2017; Final Published Version February 2018) – Q1. http://dx.doi.org/10.1016/j.jss.2017.05.043

ARTICULO RELEVANTE: Metamorphic Testing of RESTful Web APIs

S. Segura, J. A. Parejo, J. Troya and A. Ruiz-Cortés, «Metamorphic Testing of RESTful Web APIs» in IEEE Transactions on Software Engineering, Oct 2017 (online) vol. PP, no. 99, pp. 1-1. https://doi.org/10.1109/TSE.2017.2764464Aceptado para ser presentado en ICSE 2018 en la categoría de journal-first: https://www.icse2018.org/track/icse-2018-Journal-first-papers#event-overview166 lecturas en ResearchGate desde su publicación (118 en IEEE Xplore).

A Survey on Metamorphic Testing

S. Segura, G. Fraser, A. B. Sanchez and A. Ruiz-Cortés, A Survey on Metamorphic Testing, in IEEE Transactions on Software Engineering, vol. 42, no. 9, pp. 805-824, Sept. 1 2016. https://doi.org/10.1109/TSE.2016.2532875 Indicadores de calidad: – Revista de referencia en el área de Ingeniería del Software (CS-SE: 20/106). – Ha recibido 9 citas desde su publicación en febrero de 2016 (más otras 5-7 citas por aparecer en las actas del segundo workshop internacional de pruebas metamórficas [1]). – Hemos sido invitados a presentar el trabajo en ICSE17 como parte de la iniciativa journal-first (ver programa de la conferencia [2]). – Colaboración internacional con el profesor Gordon Fraser. [1] https://www.cs.montana.edu/met17/ [2] http://icse2017.gatech.edu/?q=technical-research-accepted