A visual editor for marked-up codes with auto-completion

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Po, Trevor and D'Souza, Leander and Fuchs, Stefan and Amor, Robert; Moreno-Rangel, Alejandro and Kumar, Bimal, eds. (2025) A visual editor for marked-up codes with auto-completion. In: EG-ICE 2025. University of Strathclyde Publishing, GBR. ISBN 9781914241826 (https://doi.org/10.17868/strath.00093267)

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Abstract

Manual translation of codes and standards into a marked-up and computerised form is not well supported for the code experts who would be expected to undertake this task. This research examines development of a visual LegalRuleML editor built with a deep learning model trained on legal clauses to automate manual translation tasks with intelligent auto-completion. Furthermore, this research aims to evaluate if visual programming languages can provide a viable and user-friendly LegalRuleML representation and whether visual auto-completion with deep learning is an effective feature to streamline the workflow when translating legal clauses. A user study identified that the implemented visual editor provided a user-friendly and intuitive interface that successfully aided users with no prior knowledge within the field in learning and applying LegalRuleML constructs more efficiently.

  • Item type:Book Section
    ID code:93267
    Dates:
    Date
    Event
    1 July 2025
    Published
    9 June 2025
    Accepted
    Subjects:Fine Arts > Architecture
    Department:Faculty of Engineering > Architecture
    Depositing user: Pure Administrator
    Date deposited:27 Jun 2025 10:53
    Last modified:01 Jul 2025 11:27
    URI:https://strathprints.strath.ac.uk/id/eprint/93267
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