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 baseline 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.

Publication
In Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (Companion Proceedings)
Faezeh Khorram
Faezeh Khorram
Senior Research Engineer | PhD

My research interests include Model-Based Verification and Validation, Model-Driven Engineering (MDE), Domain-Specific Languages (DSL), Language Engineering, Debugging and Testing of models.