DoME: An Architecture for Domain Model Evolution at Runtime Using NLP
Pages 186 - 195
Abstract
In traditional information systems, domain models are represented as database tables with attributes and relationships. Changes in the domain models exist due to system evolution and the emergence of new requirements. In these applications, domain models evolve using CRUD operations requested by users. However, it is necessary to support changes in domain models during the applications’ runtime when new (unforeseen) situations may occur. This work presents an architecture called DoME, which relies on natural language processing (NLP) to allow users to trigger changes in the domain models and self-adaptation techniques to update the models at runtime. It is instantiated in a concrete architecture using a chatbot in Telegram and Transformers Libraries for NLP. The architecture has been preliminary evaluated regarding its assertiveness and user satisfaction, resulting in an 82.55% hit rate and confirming that NL provides good usability and facilitates data manipulation.
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Index Terms
- DoME: An Architecture for Domain Model Evolution at Runtime Using NLP
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September 2023
570 pages
ISBN:9798400707872
DOI:10.1145/3613372
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Publication History
Published: 25 September 2023
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- Research-article
- Research
- Refereed limited
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- Brazilian Ministry of Science, Technology and Innovation
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SBES 2023
SBES 2023: XXXVII Brazilian Symposium on Software Engineering
September 25 - 29, 2023
Campo Grande, Brazil
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Overall Acceptance Rate 147 of 427 submissions, 34%
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