Rule modularity and execution control enhancements for a Java-based rule engine

Mark Proctor, Mario Fusco, Edoardo Vacchi, Davide Sottara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Drools is a popular and well known Java-based production rule system. Production rule systems, like Drools, present challenges when applied to large and complex systems. This industrial paper evaluates the prior art with regards to rulebase modularity and execution control. It then looks at how that can be applied to Drools and what further enhancements can be made. Consideration is given to ensure the work is more palatable for developers in a Java-based rule environment. Venus and RuleWorks are identified as two differing \textit{state of the art} systems. Venus provides a decoupling of rules and data as well as a declarative guard based system, without life cycle callbacks. RuleWorks provides imperative subroutines with lifecycle callbacks.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 2nd International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages89-96
Number of pages8
ISBN (Electronic)9781728114880
DOIs
StatePublished - Jun 2019
Event2nd IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2019 - Cagliari, Sardinia, Italy
Duration: Jun 3 2019Jun 5 2019

Publication series

NameProceedings - IEEE 2nd International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2019

Conference

Conference2nd IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2019
CountryItaly
CityCagliari, Sardinia
Period6/3/196/5/19

Keywords

  • Drools
  • Execution-control
  • Modularity
  • Production-rule-system
  • Rete
  • Rule-engine

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management

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  • Cite this

    Proctor, M., Fusco, M., Vacchi, E., & Sottara, D. (2019). Rule modularity and execution control enhancements for a Java-based rule engine. In Proceedings - IEEE 2nd International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2019 (pp. 89-96). [8791690] (Proceedings - IEEE 2nd International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AIKE.2019.00023