Detection of Commutative Factors Revised (DECOR+)

This directory contains the source code of the Detection of Commutative Factors Revised (DECOR+) algorithm, the Apriori-Style Detection of Commutative Factors (A-DECOR) algorithm, and the Connected-Component Detection of Commutative Factors (CC-DECOR) algorithm, which have been presented in the paper "On the Detection of Commutative Factors in Factor Graphs: Necessary and Sufficient Conditions".

Our implementation uses the Julia programming language.

Computing Infrastructure and Required Software Packages

All experiments were conducted using Julia version 1.11.2 together with the following packages:

• BenchmarkTools v1.6.0
• CSV v0.10.15
• Clustering v0.15.8
• Combinatorics v1.0.2
• DataFrames v1.7.0
• DataStructures v0.18.22
• Distributions v0.25.116
• Multisets v0.4.5
• OrderedCollections v1.8.0
• StatsBase v0.33.21

Instance Generation

Run julia generate.jl in the src/ directory to generate the input instances for the experiments. The input instances are then written into the data/ directory (which is automatically created).

Running the Experiments

After the instances have been generated, the experiments can be started by running julia run_eval.jl in the src/ directory. All results are written into the results/ directory.

To create the plots, run julia prepare_plot.jl in the results/ directory and afterwards execute the R script plot.r (also in the results/ directory). The R script will then create a bunch of .tex files in the results/ directory containing the plots of the experiments. To generate the plots as .pdf files instead, set use_tikz = FALSE in line 5 of plot.r before executing the R script plot.r.