A DSL-Driven Solution and Code Generation for Accelerated Tourism Decision Support System Development
Decision Support Systems (DSS) play a crucial role in commerce and tourism by assisting decision-making through data analysis, modeling, and visualization. However, their development is often complex, costly, and requires expertise in both software engineering and Artificial Intelligence, making the...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11029257/ |
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| Summary: | Decision Support Systems (DSS) play a crucial role in commerce and tourism by assisting decision-making through data analysis, modeling, and visualization. However, their development is often complex, costly, and requires expertise in both software engineering and Artificial Intelligence, making them inaccessible to many organizations. To address these challenges, this paper introduces a Domain-Specific Language (DSL), a graphical decision rule modeling tool, and code generation templates designed to streamline DSS development for smart tourism. The proposed framework enables rule-based system modeling and automatic code generation, leveraging Drools, a powerful rule engine, to manage business rules, execute inferences, and optimize decision processes. This approach significantly reduces development time while improving system flexibility and adaptability to meet the diverse needs of smart tourism. A comparative study demonstrates a substantial reduction in development time, while a case study confirms the framework’s ability to generate functional applications suited to real-world environments. Our contribution lies in automating and simplifying DSS development by integrating a dedicated DSL and Drools, reducing manual programming complexity, and ensuring the generation of optimized, maintainable, and easily integrable code. This enhances productivity, reduces development effort, and ensures adaptability to changing business needs. |
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| ISSN: | 2169-3536 |