Experimental Research on a Continuous Integrating pipeline with a Machine Learning approach : Master Thesis done in collaboration with Electronic Arts

Experimental Research on a Continuous Integrating pipeline with a Machine Learning approach : Master Thesis done in collaboration with Electronic Arts

Time-consuming code builds within the Continuous Integration pipeline is a common problem in today’s software industry. With fast-evolving trends and technologies, Machine Learning has become a more popular approach to tackle and solve real problems within the software industry. It has been shown to...

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Bibliographic Details
Main Author: Sigurdardóttir, Sigrún Arna
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2021
Subjects:
Machine Learning
Continuous Integration
Builds
Prediction
dataset
Code Change
Data Analysis
Maskininlärning
Kontinuerlig Integration
Byggnader
Förutsägelse
Datamängd
Kodändring
Dataanalys
Software Engineering
Programvaruteknik
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303158

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303158

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