Published October 5, 2022 | Version v0.1.0
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From SMT to ASP: Solver-Based Approaches to Solving Datalog Synthesis-as-Rule-Selection Problems (POPL 2023 Artifact)

Creators

  • 1. Harvard University
  • 2. Stevens Institute of Technology

Description

This is the artifact corresponding to the paper "From SMT to ASP: Solver-Based Approaches to Solving Datalog Synthesis-as-Rule-Selection Problems" by Aaron Bembenek, Michael Greenberg, and Stephen Chong, which has been conditionally accepted at POPL 2023. Please check for the newest version of the artifact.

Files

LICENSE.txt

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