Add benchmark for our DTGBA SAT-minimization.
* bench/dtgbasat/: New directory. * bench/Makefile.am: New file. * configure.ac, README: Adjust.
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bench/dtgbasat/README
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bench/dtgbasat/README
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These are the benchmark for our submission to VMCAI'14.
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To reproduce, follow these instructions:
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1) Compile Spot and install if it is not already done.
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2) Compile Glucose from https://www.lri.fr/~simon/?page=glucose
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and make sure the 'glucose' binary is in your PATH.
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3) Compile ltl2dstar from http://www.ltl2dstar.de/ and
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make sure the 'ltl2dstar' binary is in your path.
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4) Compile DBAminimizer from
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http://www.react.uni-saarland.de/tools/dbaminimizer
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and define the path to minimize.py with
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% export DBA_MINIMIZER=$HOME/dbaminimizer/minimize.py
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5) Then make sure you are in this directory:
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% cd bench/dtgbasat/
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6) Classify the set of formulas with
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% ./prepare.sh
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This will read the formulas from file "formulas" and output a file
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"info.ltl", in which each formula is associated to a class (the ①,
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②, ②, and ④ of the paper), and a number of acceptance conditions
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(the "m" of the paper).
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7) Build a makefile to run all experiments
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% ./stats.sh
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8) You may optionally change the directory that contains temporary
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files with
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% export TMPDIR=someplace
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(These temporary files can be several GB large.)
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Note that runtime will be limited to 2h, but memory is not bounded.
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You should set such a limit with "ulimit" if you like. For instance
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% ulimit -v 41943040
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9) Actually run all experiments
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% make -j4 stat.mk
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This will build a CSV file called "all.log".
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10) You may generate LaTeX code for the tables with the scripts:
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- tabl.pl: Full data.
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- tabl1.pl, tabl2.pl, tabl3.pl, tabl4.pl: Partial tables as shown
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in the paper.
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All these script takes the CSV file all.log as first argument, and
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output LaTeX to their standard output.
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For more instruction about how to use ltl2tgba and dstar2tgba to
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compute minimal DTGBA or DTBA, please read doc/userdoc/satmin.html
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