prathgan / COASTL

Lightweight Python package for doing operations concerning Assume-Guarantee (A/G) Contracts and parsing, deriving constraints from, and solving Signal Temporal Logic. Built at DesCyPhy Lab, USC

COASTL (Contract Operations and Signal Temporal Logic)

Poster

Lightweight Python package for doing operations concerning A/G contracts in design-by-contract systems design. Also has functionality to read Signal Temporal Logic into operable structure and derive corresponding boolean and synthesis constraints. Developed at DesCyPhy Lab, USC.

Installation

Prerequisites

For the following prerequisites, if not already installed, a pip install should suffice:

• sympy
• numpy
• re

This package also requires a functioning installation of Gurobi, an optimization solver tool used heavily in coastl. Once you have installed Gurobi, navigate to the Gurobi <intstalldir> and execute python setup.py install.

Install coastl

1. download .zip file of this repository

2. navigate to directory where coastl setup.py file is located

3. pip install .

Use

For more, see the examples folder.

Signal Temporal Logic

Import functions:

from coastl import parse_stl, create_model_stl, synthesize_stl

Create tree from STL:

stl_tree = parse_stl("G[0,10]((x<=10)&&(~(x<=5)))")

Traverse tree and create model, adding constraints for all logic:

m = create_model_stl(stl_tree)

Optimize model and synthesize values for x:

m = synthesize_stl(m)

Get list of variables (type is Gurobi variables):

solved_vars = m.getVars()

Print variable names and values:

for var in solved_vars:
  print(var.VarName + ": " + str(var.X))

Contracts

Import Contract object, conjunction & composition operations

from coastl import Contract, conjunction, composition

Create two contracts in the format [vars, assumptions, guarantees]

c1 = Contract(["x"],"T","(x<=2)")
c2 = Contract(["x"],"T","~(x<=1)")

Saturate both contracts

c1.saturate()
c2.saturate()

If contracts in an operation are not already saturated, coastl will automatically saturate them.

Composition:

c3 = composition([c1, c2])
c3.synthesize(remove_log=True, console_log=False)
c3_solutions = c3.get_synthesized_vars()
print(c3_solutions)

Conjunction:

c3 = conjunction([c1, c2])
c3.synthesize(remove_log=True, console_log=False)
c3_solutions = c3.get_synthesized_vars()
print(c3_solutions)