Artifact for RE'26 paper: Mode-Based Requirements Decomposition for Scalable Reactive Synthesis [* Cross-Reference *]

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Matías Brizzio; Andoni Rodríguez; César Sánchez; Renzo Degiovanni, 2026, "Artifact for RE'26 paper: Mode-Based Requirements Decomposition for Scalable Reactive Synthesis [* Cross-Reference *]", https://lore.list.lu/citation?persistentId=perma:LIST.B7JQLD, LIST Open Repository, V1
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Description
This artifact contains the implementation, benchmarks, and a ready-to-run Docker image for MoBy, a tool for reactive synthesis based on mode-based decomposition. Given a Safety-LTL specification and a set of operational modes, MoBy decomposes the global problem into mode-specific sub-problems and propagates knowledge across modes (via winning regions, duty variables, and landing variables) to produce modular controllers using off-the-shelf synthesis tools. The method is sound and complete.The package bundles every backend already compiled and configured: Strix (realizability/synthesis), SyFCo (TLSF↔LTL), Black (LTL satisfiability), AIGLE (Safety-LTL→AIGER translation), and AbsSynthe (BDD-based winning-region computation via CUDD), together with the Java engine (OWL, LogicNG).Contents: source code, benchmark specifications (including the RE 2026 case studies), experiment scripts, a prebuilt Docker image (moby.tar), and installation/usage instructions (README.md). Quick start: load the image with docker load -i moby.tar and run the experiments, e.g. docker run --platform=linux/x86_64 --rm --memory=10g betsy:latest ./run-all-real-lambda-fixpoint.sh 1 real-re 600. See the README for full instructions, manual build steps, and guidance on swapping the LTL solver.For the latest version of the code, see the tool webpage: https://sites.google.com/view/remodes26 (2026-06-15)
***This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to https://doi.org/10.5281/zenodo.20698202 for the original and latest version of the publication*** (2026-07-01)
Subject Computer and Information Science; Physics
Keyword Modular design, Scalability, Artifact (error), Set (abstract data type), Benchmark (surveying), Computation, Java, Image (mathematics)
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