Reproducing and Improving the BugsInPy Dataset.

Faustino Aguilar,Samuel Grayson,Darko Marinov

2023 IEEE 23rd International Working Conference on Source Code Analysis and Manipulation (SCAM)(2023)

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Abstract
We assess the reproducibility of the BugsInPy dataset less than three years after its original publication. The bug dataset provides some information about the software environment in which the code should be run, but this information can be incomplete or can decay into something uninstallable over time. We rectify as many of these problems as we can and redesign the original dataset to be more easily reusable and reproducible by future research projects. Based on our experience, we offer suggestions to authors of Python artifacts to improve their reproducibility.
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Key words
reproducibility,bug database,BugsInPy,Python,package managers,Pip,Conda,containers,Docker
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