Bellomarini, L., Gentili, A., Magnanimi, D., & Sallinger, E. (2025). Vadacode: A Logician-Friendly IDE for Datalog±. Proceedings of the VLDB Endowment, 18(12), 5411–5414. https://doi.org/10.14778/3750601.3750684
E192-02 - Forschungsbereich Databases and Artificial Intelligence E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML)
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Journal:
Proceedings of the VLDB Endowment
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ISSN:
2150-8097
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Date (published):
1-Aug-2025
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Number of Pages:
4
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Publisher:
ASSOC COMPUTING MACHINERY
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Peer reviewed:
Yes
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Keywords:
Datalog; Vadacode; Integrated Development Environment (IDE); Knowledge Representation and Reasoning (KRR)
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Abstract:
Languages, namely, fragments, of the Datalog+/-family are attracting interest in both academia and industry because of their possibility to balance high expressive power and computational complexity. However, understanding the differences among the fragments, mastering them to achieve scalable industrial applications, and communicating their peculiarities to a non-expert audience is challenging for researchers, developers, logicians, and educators. In this demo, we introduce Vadacode, an IDE for Datalog+/-designed to support a broad category of users. The tool offers advanced features, including fragment detection, syntax highlighting, code completion, error diagnostics, schema inference, debugging support, and AI-assisted coding capabilities. Thanks to our experience in the financial context, our demo will guide the audience in modeling financial Datalog+/-programs, showcasing a seamless and effective coding experience.
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Project title:
Scalable Reasoning in Knowledge Graphs: VRG18-013 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds) Knowledge Graph-driven Tour Management for Sustainable Waste Processing: NXT22-018 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds)
