Testing in the Evolving World of DL Systems:Insights from Python GitHub Projects

Qurban Ali; Oliviero Riganelli; Leonardo Mariani

doi:10.1109/QRS62785.2024.00013

Testing in the Evolving World of DL Systems:Insights from Python GitHub Projects

Software Engineering 2024-10-24 v1

Authors: Qurban Ali , Oliviero Riganelli , Leonardo Mariani

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Abstract

In the ever-evolving field of Deep Learning (DL), ensuring project quality and reliability remains a crucial challenge. This research investigates testing practices within DL projects in GitHub. It quantifies the adoption of testing methodologies, focusing on aspects like test automation, the types of tests (e.g., unit, integration, and system), test suite growth rate, and evolution of testing practices across different project versions. We analyze a subset of 300 carefully selected repositories based on quantitative and qualitative criteria. This study reports insights on the prevalence of testing practices in DL projects within the open-source community.

Keywords

software engineering software testing software library

Cite

@article{arxiv.2405.19976,
  title  = {Testing in the Evolving World of DL Systems:Insights from Python GitHub Projects},
  author = {Qurban Ali and Oliviero Riganelli and Leonardo Mariani},
  journal= {arXiv preprint arXiv:2405.19976},
  year   = {2024}
}

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11 pages, 3 figures, The 24th IEEE International Conference on Software Quality, Reliability, and Security (QRS) 2024

Testing in the Evolving World of DL Systems:Insights from Python GitHub Projects

Abstract

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