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Visibility Matrix: Efficient User Interface Modelling for Low-Code Development Platforms

Author

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  • Robert Waszkowski

    (Faculty of Cybernetics, Military University of Technology, 00-908 Warszawa, Poland)

  • Grzegorz Bocewicz

    (Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland)

Abstract

In this paper, we introduce the idea of the ‘visibility matrix’ for automated data entry form generation in low-code development platforms. We then focus on the problem of software development productivity in the area of automated software generation as the main factor of the Industry 4.0 concept in the area of business information. In our study, two different approaches to user interface development in a business process management low-code platform were evaluated. The first, the multi-form model, assumes that input forms are prepared separately for each user task in the business process being automated. The second approach, the single-form model, assumes that there is one global input form for every task in the business process. Since users have access to different data in different process tasks, it is necessary to prepare the visibility matrix to define which data are relevant to which tasks. The experiments presented in this paper help to answer the following question: which approach yields better results in terms of productivity, which is measured as costs and time required to prepare the application? Several dozen real business processes were analysed to examine the properties of their visibility matrix. Additionally, the real project team members were evaluated to determine their productivity. Then, the productivity parameters were calculated for real business processes and real project teams. The results show which approach is better suited for real-world business process development.

Suggested Citation

  • Robert Waszkowski & Grzegorz Bocewicz, 2022. "Visibility Matrix: Efficient User Interface Modelling for Low-Code Development Platforms," Sustainability, MDPI, vol. 14(13), pages 1-24, July.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:8103-:d:854451
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    References listed on IDEAS

    as
    1. Anas Alokla & Walaa Gad & Waleed Nazih & Mustafa Aref & Abdel-Badeeh Salem, 2022. "Retrieval-Based Transformer Pseudocode Generation," Mathematics, MDPI, vol. 10(4), pages 1-16, February.
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