Does using Bazel help speed up continuous integration builds? DOI
Shenyu Zheng, Bram Adams, Ahmed E. Hassan

и другие.

Empirical Software Engineering, Год журнала: 2024, Номер 29(5)

Опубликована: Июль 19, 2024

Язык: Английский

An attempt to promote intelligent petroleum processing: a look at how different programming languages works with deep learning models for gasoline quality detection DOI Creative Commons

Abdullah H. Alzahawi,

Hayder Issa

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Май 21, 2024

Abstract The current study explores how several programming languages affect deep learning models for gasoline quality detection, highlighting the significance of choosing best appropriate language according to project needs. Featuring scientific computations using an integrated development environment Visual Studio Code (VS Code) tool. This work has reached multiple outcomes: Python is known its rapid and adaptability, which are well-suited exploring control techniques in petroleum products. Java recognized stability flexibility across many platforms, making it ideal large-scale deployments that require dependable performance refinery equipment. C/C++ lauded speed ability manage hardware resources effectively, essential real-time production settings, allowing quick analysis little delay processes. utilizes a architecture Java, C, Python, with frameworks such as aid model construction, goal creating flexible tools monitoring dynamic

Язык: Английский

Процитировано

0

Does using Bazel help speed up continuous integration builds? DOI
Shenyu Zheng, Bram Adams, Ahmed E. Hassan

и другие.

Empirical Software Engineering, Год журнала: 2024, Номер 29(5)

Опубликована: Июль 19, 2024

Язык: Английский

Процитировано

0