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MinLB

Requirements

Directory Structure

  • compute_dlp.py, propagator.py, compute_independent_support.py and prepare_td.py : useful scripts
  • decomposition.py: script to run ProjEnum
  • hashCount: Static binary of HashCount
  • td and flow_cutter_pace17: tools for computing tree decomposition and cut

Benchmarks

The benchmarks can be found here.

Quick Run Proj-Enum

Install clingo in your system ProjEnumInput folder contains input instances in ProjEnum input format. First unzip:

unzip ProjEnumInput.zip

Run ProjEnum on input mcctrack1_002.mcc2020_cnf:

cp ProjEnumInput/cut_mcctrack1_002.mcc2020_cnf .
python decomposition.py -i cut_mcctrack1_002.mcc2020_cnf -c 1

Quick Run HashCounter

Make sure that hashcounter is executable in your machine or run chmod +x hashcounter

HashCounterInput folder contains input instances in HashCounter input format. First unzip:

unzip HashCounterInput.zip

Run HashCounter on input mcctrack1_002.mcc2020_cnf (chmod +x hashcounter if hashcounter is not executable):

cp HashCounterInput/dlp_mcctrack1_002.mcc2020_cnf HashCounterInput/IS_dlp_mcctrack1_002.mcc2020_cnf .
./hashcounter --useind IS_dlp_mcctrack1_002.mcc2020_cnf --asp dlp_mcctrack1_002.mcc2020_cnf

Run HashCount Step-by-Step

Install clingo in your system

chmod +x hashcounter if hashcounter is not executable

The command to run HashCount on model counting benchmark:

python run_hashcount_on_modelcounting.py -i mccmc2021_track1_058.cnf

The command to run HashCount on item mining benchmark:

python run_hashcount_on_itemmining.py -i vote.cnf

Run Proj-Enum Step-by-Step

Install clingo in your system

Make sure that td and flow_cutter_pace17 are executable in your machine (run chmod +x td flow_cutter_pace17)

Proj-Enum runs a tree decomposer for 100s to compute a cut of the Boolean formula. The command to run ProjEnum on model counting benchmark:

python run_projenum_on_modelcounting.py -i mccmc2021_track1_058.cnf

The command to run ProjEnum on item mining benchmark:

python run_projenum_on_itemmining.py -i vote.cnf

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On Lower Bounding Minimal Model Count

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