sle2023/paper08

SLE 2023 paper:
Reuse and Automated Integration of Recommenders for Modelling Languages

Lissette Almonte, Antonio Garmendía, Esther Guerra, Juan de Lara

• DOI: 10.1145/3623476.3623523
• T1E: Reuse
  • The core contribution is enabling reuse of recommenders across modelling languages and reducing duplication when integrating them.
• T4A: Workbenches
  • The paper proposes infrastructure to integrate recommenders into modelling tools with less engineering effort.
• T3C: DSLs
  • The setting is modelling languages (DSLs), for which recommendation services are built and reused.

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