CodoMo: Python Model Checking to Integrate Agile Verification Process of Computer Vision Systems

TL;DR

CodoMo is a Python tool that automates model generation from code to enable efficient, agile verification of computer vision systems using model checking techniques.

Contribution

It introduces an automated Python code to model generator that bridges traditional model checking with agile development practices.

Findings

Successfully verified a Tello Drone gesture-based image processing system

Automated model generation improves verification efficiency

Integrating PyExZ3 with Kripke structure generation enhances performance

Abstract

Model checking is a fundamental technique for verifying finite state concurrent systems. Traditionally, model designs were initially created to facilitate the application of model checking. This process, representative of Model Driven Development (MDD), involves generating an equivalent code from a given model which is verified before implementation begins. However, this approach is considerably slower compared to agile development methods and lacks flexibility in terms of expandability and refactoring. We have proposed "CodoMo: Python Code to Model Generator for pyModelChecking." This tool automates the transformation of a Python code by an AST static analyzer and a concolic testing tool into intermediate models suitable for verification with pyModelChecking, bridging the gap between traditional model checking and agile methodologies. Additionally, we have implemented a multiprocess approach that integrates the execution of PyExZ3 with the generation of Kripke structures achieving greater work efficiency. By employing CodoMo, we successfully verified a Tello Drone programming with gesture-based image processing interfaces, showcasing the tool's powerful capability to enhance verification processes while maintaining the agility required for today's fast-paced development cycles.