Probabilistic Inference for Predicate Constraint Satisfaction

Authors: Yuki Satake, Hiroshi Unno, Hinata Yanagi1644-1651

AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We have implemented the presented method and obtained promising results on existing benchmarks as well as new ones that are beyond the scope of existing CHC solvers. 5 Implementation and Evaluation We have implemented a constraint solver PCSAT for the full class of p CSP based on the presented method. We adopted MINISAT (E en and S orensson 2004) and Z3 (de Moura and Bjørner 2008) as the backend SAT and SMT solvers, respectively. We conducted three sets of experiments.
Researcher Affiliation Academia Yuki Satake,1 Hiroshi Unno,1,2 Hinata Yanagi1 1University of Tsukuba, 2RIKEN AIP {satake, uhiro, hinata}@logic.cs.tsukuba.ac.jp
Pseudocode No The paper describes its methods in prose and does not include any explicit pseudocode or algorithm blocks.
Open Source Code No The paper states 'We have implemented the presented method' but does not provide an explicit statement about releasing the source code for their implementation or a link to a code repository.
Open Datasets Yes We have implemented the presented method and obtained promising results on existing benchmark sets from Sy Gu S-Comp 2017 and 2018 (Invariant Synthesis Track), and CHC-COMP 2019 (LIA-nonlin Track) as well as a new benchmark set... 6http://sygus.org/comp/ 7https://chc-comp.github.io/
Dataset Splits No The paper uses existing benchmark sets (Sy Gu S-Comp, CHC-COMP) but does not provide explicit details about train/validation/test dataset splits, such as percentages or sample counts, that would be needed to reproduce the data partitioning for these benchmarks.
Hardware Specification Yes All the experiments were conducted on 3.1GHz Intel Xeon Platinum 8000 CPU and 32 Gi B RAM.
Software Dependencies No The paper mentions using 'MINISAT (E en and S orensson 2004) and Z3 (de Moura and Bjørner 2008) as the backend SAT and SMT solvers' but does not provide specific version numbers for these software dependencies.
Experiment Setup Yes We evaluated the impact of our SID-based multiple solution enumeration technique on the convergence speed of CEGIS using the benchmark set consisting of 127 linear CHCs from the Inv Track category of Sy Gu S-Comp 2018 with 300s timeout. Figure 1 summarizes the results of running PCSAT with different configurations obtained by varying the number #cand of candidate solutions generated in the synthesis phase, and enabling or disabling SID...