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TesCaV: An Approach for Learning Model-Based Testing and Coverage in Practice

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Research Challenges in Information Science (RCIS 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 385))

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Abstract

Academy and industry permanently remark the importance of software-testing techniques to improve software quality and to reduce development and maintenance costs. A testing method to be considered for this purpose is Model-Based Testing (MBT), which generates test cases from a model that represents the structure and the behavior of the system to be developed. The generated test suite is easier to maintain and adapt to changes in requirements or evolution of the developed system. However, teaching and learning MBT techniques are not easy tasks; students need to know the different testing techniques to assure that the requirements are fulfilled as well as to identify any failure in the software system modeled. In this work, we present TesCaV, an MBT teaching tool for university students, which is based on a model-driven technology for the automatic software generation from UML diagrams. TesCaV allows validating the test cases defined by students and graphically determines the level of testing coverage over the system modeled. Preliminary results show TesCaV as a promising approach for MBT teaching/learning processes.

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Acknowledgement

This work was funded by CONICYT project ENSE REDI170020, 2017–2019.

Author information

Authors and Affiliations

  1. Universidad Diego Portales, Santiago, Chile

    Beatriz Marín & Sofía Alarcón

  2. Universidad Tecnológica de Chile INACAP, Santiago, Chile

    Giovanni Giachetti

  3. KU Leuven, Leuven, Belgium

    Monique Snoeck

Authors
  1. Beatriz Marín
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  2. Sofía Alarcón
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  3. Giovanni Giachetti
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  4. Monique Snoeck
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Corresponding author

Correspondence to Beatriz Marín .

Editor information

Editors and Affiliations

  1. Utrecht University, Utrecht, The Netherlands

    Fabiano Dalpiaz

  2. Stockholm University, Kista, Sweden

    Jelena Zdravkovic

  3. The Institute of Digital Innovation and Research, Dublin, Ireland

    Pericles Loucopoulos

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Marín, B., Alarcón, S., Giachetti, G., Snoeck, M. (2020). TesCaV: An Approach for Learning Model-Based Testing and Coverage in Practice. In: Dalpiaz, F., Zdravkovic, J., Loucopoulos, P. (eds) Research Challenges in Information Science. RCIS 2020. Lecture Notes in Business Information Processing, vol 385. Springer, Cham. https://doi.org/10.1007/978-3-030-50316-1_18

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  • DOI: https://doi.org/10.1007/978-3-030-50316-1_18

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  • Online ISBN: 978-3-030-50316-1

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