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

Title:
Testing in the Evolving World of DL Systems:Insights from Python GitHub Projects
Authors:
Ali, Qurban, Riganelli, Oliviero, Mariani, Leonardo
Publisher Information:
2024-05-30
Document Type:
E-Ressource Electronic Resource
Index Terms:
Computer Science - Software Engineering, text
DOI:
10.1109.QRS62785.2024.00013
URL:
http://arxiv.org/abs/2405.19976
Availability:
Open access content. Open access content
Other Numbers:
COO oai:arXiv.org:2405.19976
doi:10.1109/QRS62785.2024.00013
1438562759
Contributing Source:
CORNELL UNIV
From OAIster®, provided by the OCLC Cooperative.
Accession Number:
edsoai.on1438562759
Database:
OAIster

Weitere Informationen

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