Machine Learning and Configurable Systems | Zendy

Hugo Martin | Zendy; Juliana Alves Pereira | Zendy; Mathieu Acher | Zendy; Paul Temple | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Machine Learning and Configurable Systems

Author(s) -

Hugo Martin,

Juliana Alves Pereira,

Mathieu Acher,

Paul Temple

Publication year - 2019

Publication title -

hal (le centre pour la communication scientifique directe)

Language(s) - English

Resource type - Conference proceedings

ISBN - 978-1-4503-7138-4

DOI - 10.1145/3336294.3342383

Subject(s) - computer science , field (mathematics) , software engineering , product (mathematics) , software , artificial intelligence , programming language , geometry , mathematics , pure mathematics

The goal of this tutorial is to give an introduction to how machine learning can be used to support activities related to the engineering of configurable systems and software product lines. To the best of our knowledge, this is the first practical tutorial in this trending field. The tutorial is based on a systematic literature review and includes practical tasks (specialization, performance prediction) on real-world systems (VaryLaTeX, x264).

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research