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Multiperspective Web Testing Supported by a Generation Hyper-Heuristic

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Computational Science and Its Applications – ICCSA 2022 Workshops (ICCSA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13381))

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Abstract

Web interface testing is a sort of system testing level and it is laborious if accomplished manually, since it is necessary to map each of the elements that make up the interface with its respective code. Furthermore, this mapping makes test scripts very sensitive to any changes to the interface’s source code. Approaches for automated web testing have been proposed but the use of hyper-heuristics, higher-level search techniques aiming to address the generalization issues of metaheuristics, for web testing are scarce in the literature. In this article we present a multi-objective web testing method, MWTest, which automates the generation of test cases based only on the URL of the web application and a new proposed generation hyper-heuristic, called GECOMBI. The GECOMBI hyper-heuristic takes into account combinatorial designs to generate low-level heuristics to support our goal. Moreover, the implementation of the MWTest method creates a Selenium test script quickly and without human interaction, exclusively based on the URL in order to support the automated execution of test cases too. In our evaluation, we compared GECOMBI to another generation hyper-heuristic, GEMOITO, and four metaheuristics (NSGA-II, IBEA, MOMBI, NSGA-III). Results show superior performance of GECOMBI compared to the other approaches.

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Authors and Affiliations

  1. Instituto Nacional de Pesquisas Espaciais (INPE), Av. dos Astronautas 1758, São José dos Campos, SP, Brazil

    Juliana Marino Balera & Valdivino Alexandre de Santiago Júnior

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  1. Juliana Marino Balera
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  2. Valdivino Alexandre de Santiago Júnior
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Corresponding author

Correspondence to Juliana Marino Balera .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Østfold University College, Halden, Norway

    Sanjay Misra

  4. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  5. University of Cagliari, Cagliari, Italy

    Chiara Garau

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Balera, J.M., de Santiago Júnior, V.A. (2022). Multiperspective Web Testing Supported by a Generation Hyper-Heuristic. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds) Computational Science and Its Applications – ICCSA 2022 Workshops. ICCSA 2022. Lecture Notes in Computer Science, vol 13381. Springer, Cham. https://doi.org/10.1007/978-3-031-10548-7_33

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  • DOI: https://doi.org/10.1007/978-3-031-10548-7_33

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