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

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.

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Published
2024-11-26
DOI
https://doi.org/10.1109/candar64496.2024.00012
Primary Topic
Computational Physics and Python Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Katsumi Wasaki, Yuto Ogata, Yojiro Harie, Bishnu Prasad Gautam
Computational Physics and Python Applications
article

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

Katsumi Wasaki, Yuto Ogata, Yojiro Harie, Bishnu Prasad Gautam
article en

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.

Shinshu University (JP), Kanazawa Gakuin University (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 78%
Computational Physics and Python Applications
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CodoMo: Python Model Checking to Integrate Agile Verification Process of Computer Vision Systems — Katsumi Wasaki, Yuto Ogata, et al. · (2024) | TGRS Research Map | TGRS