spot/bench/stutter
Thibaud Michaud ad3ea61ac2 Adding README in bench/stutter/.
* bench/stutter/README: Document stutter-invariance benchmarks.
2014-11-26 10:38:32 +01:00
..
Makefile.am Adding tgba-based stutter-invariance checking 2014-11-14 11:11:39 +01:00
README Adding README in bench/stutter/. 2014-11-26 10:38:32 +01:00
stutter.ipynb Adding ipython notebook to visualize stutter-invariance benchmarks. 2014-11-26 10:38:32 +01:00
stutter_bench.sh Adding ipython notebook to visualize stutter-invariance benchmarks. 2014-11-26 10:38:32 +01:00
stutter_invariance_formulas.cc stutter check: cleanup and add test cases 2014-11-14 11:11:39 +01:00
stutter_invariance_randomgraph.cc export a create_atomic_prop_set() function 2014-11-26 10:37:40 +01:00

This benchmark measures the performance of different algorithms to check
if a büchi automaton has the stutter-invariance property. If the
benchmark is run on formulas, the translation time is not included in
the measured time.

You can specify which formulas are to be used for the benchmarks by
running:

  % ./stutter_invariance_formulas -F FILE > bench_formulas.csv

Where FILE is a file containing a list of formulas (see
./stutter_invariance_formulas --help for other input options).

Or use the script which will call this executable on random formulas
ranging from 1 to 4 atomic propositions:

  % ./stutter_bench.sh

This will create the file bench_formulas.csv.

Alternatively, the algorithms can be measured on random complete
deterministic automata with:

  % ./stutter_invariance_randomgraph > bench_randgraph.csv

Assuming ipython is installed, the csv files can be visualized using the
provided ipython notebook. Run:

  % ipython notebook --matplotlib

in this directory, and open stutter.ipynb.