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Modelling the Turtle Python library in CSP

Authors: MacConville, Dara; Farrell, Marie; Luckcuck, Matt; Monahan, Rosemary;

Modelling the Turtle Python library in CSP

Abstract

Software verification is an important tool in establishing the reliability of critical systems. One potential area of application is in the field of robotics, as robots take on more tasks in both day-to- day areas and highly specialised domains. Robots are usually given a plan to follow, if there are errors in this plan it will have negative consequences for the robot’s performance. The capability to check plans for errors in advance could prevent this. Python is a popular programming language in the robotics domain, through the use of the Robot Operating System (ROS) and various other libraries. Python’s Turtle package provides a simple robotic-style agent, which we formally model here using Communicating Sequential Processes (CSP). Our interactive toolchain CSP2Turtle with CSP model and Python components, enables Turtle plans to be verified in CSP before being executed in Python. This means that certain classes of errors can be avoided, and provides a starting point for more detailed verification of Turtle programs and more complex robotic systems. We illustrate our approach with examples of robot navigation and obstacle avoidance in a 2D grid-world.

Keywords

python, software verification, turtle

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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