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Challenges & Opportunities in Low-Code Testing

Abstract : Low-code is a growing development approach supported by many platforms. It fills the gap between business and IT by supporting the active involvement of non-technical domain experts, named Citizen Developer, in the application development lifecycle. Low-code introduces new concepts and characteristics. However, it is not investigated yet in academic research to point out the existing challenges and opportunities when testing low-code software. This shortage of resources motivates this research to provide an explicit definition to this area that we call it Low-Code Testing. In this paper, we initially conduct an analysis of the testing components of five commercial Low-Code Development Platforms (LCDP) to present low-code testing advancements from a business point of view. Based on the low-code principles as well as the result of our analysis, we propose a feature list for low-code testing along with possible values for them. This feature list can be used as a base-line for comparing low-code testing components and as a guideline for building new ones. Accordingly, we specify the status of the testing components of investigated LCDPs based on the proposed features. Finally, the challenges of low-code testing are introduced considering three concerns: the role of citizen developer in testing, the need for high-level test automation, and cloud testing. We provide references to the state-of-the-art to specify the difficulties and opportunities from an academic perspective. The results of this research can be used as a starting point for future research in low-code testing area.
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https://hal.archives-ouvertes.fr/hal-02946812
Contributor : Faezeh Khorram <>
Submitted on : Wednesday, September 23, 2020 - 2:22:20 PM
Last modification on : Wednesday, July 21, 2021 - 7:36:01 AM
Long-term archiving on: : Thursday, December 3, 2020 - 4:05:10 PM

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Faezeh Khorram, Jean-Marie Mottu, Gerson Sunyé. Challenges & Opportunities in Low-Code Testing. ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems (MODELS ’20 Companion), Oct 2020, Virtual, Canada. ⟨10.1145/3417990.3420204⟩. ⟨hal-02946812⟩

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