PyTLQ is an original Python package for solving temporal logic queries, as defined by Chan [1] and corrected/extended by Samer and Veith [2, 3].
Temporal logic query solving is an extension of model checking whose main aim
is to understand a model as opposed to merely verifying its correctness. A
temporal logic query basically consists of a temporal logic formula where
some subformulas are replaced by the special symbol ? representing a "hole"
in the formula. The query solving problem then consists of finding the right
subformula to fill the hole(s) and make the initial formula satisfied in the
considered modeled system.
PyTLQ can therefore be seen as an extension of the PyNuSMV model-checking library [4]. Within this framework, it uses the BDD-based model checking functionalities of the latter to efficiently implement temporal logic queries.
- PyNuSMV - http://lvl.info.ucl.ac.be/Tools/PyNuSMV
- PyParsing - http://pyparsing.wikispaces.com
- Click - http://click.pocoo.org
Remark. Make sure you are using Python 3 before installing PyTLQ.
$ pip install https://github.com/sthibert/PyTLQ/zipball/master
Note that PyParsing and Click are automatically installed with PyTLQ, but PyNuSMV must be manually installed before using PyTLQ.
PyTLQ is meant to be called from the command line. The usage is:
$ pytlq <model_path> <query> [--order <order_path>]
<model_path>represents the path to the SMV model you want to analyse.<query>represents your CTL query as a string (see Documentation for the syntax of the input language).<order_path>is an optional argument that allows you to provide an order file (.ord) to PyTLQ, in order to compute the considered SMV model efficiently.
This command computes the unique set of solution states that represents an
exact solution to query in the system defined in model_path (if there is
one). Then, you have the choice of projecting the solution on a subset of the
variables of the system, simplifying the solution thanks to an approximate
conjunctive decomposition, or you can quit PyTLQ.
To display the usage instructions, just enter:
$ pytlq --help
The full documentation can be found on:
doc/html/index.html
PyTLQ is licensed under the GNU Lesser General Public License version 2.1. File LICENSE.txt contains a copy of the license.
[1] Chan, William. "Temporal-Logic Queries." Computer Aided Verification. Springer Berlin Heidelberg, 2000.
[2] Samer, Marko, and Helmut Veith. "Validity of CTL Queries Revisited." Computer Science Logic. Springer Berlin Heidelberg, 2003.
[3] Samer, Marko, and Helmut Veith. "Deterministic CTL Query Solving." Temporal Representation and Reasoning, 2005. TIME 2005. 12th International Symposium on. IEEE, 2005.
[4] Busard, Simon, and Charles Pecheur. "PyNuSMV: NuSMV as a Python Library." NASA Formal Methods. Springer Berlin Heidelberg, 2013.