SoK: Machine Learning for Continuous Integration

04/06/2023
by   Ali Kazemi Arani, et al.
0

Continuous Integration (CI) has become a well-established software development practice for automatically and continuously integrating code changes during software development. An increasing number of Machine Learning (ML) based approaches for automation of CI phases are being reported in the literature. It is timely and relevant to provide a Systemization of Knowledge (SoK) of ML-based approaches for CI phases. This paper reports an SoK of different aspects of the use of ML for CI. Our systematic analysis also highlights the deficiencies of the existing ML-based solutions that can be improved for advancing the state-of-the-art.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/28/2023

MLSMM: Machine Learning Security Maturity Model

Assessing the maturity of security practices during the development of M...
research
01/23/2020

Machine Learning and value generation in Software Development: a survey

Machine Learning (ML) has become a ubiquitous tool for predicting and cl...
research
03/11/2021

Linnaeus: A highly reusable and adaptable ML based log classification pipeline

Logs are a common way to record detailed run-time information in softwar...
research
11/06/2022

Cementron: Machine Learning the Constituent Phases in Cement Clinker from Optical Images

Cement is the most used construction material. The performance of cement...
research
05/22/2023

Systematic Literature Review on Application of Machine Learning in Continuous Integration

This research conducted a systematic review of the literature on machine...
research
10/01/2018

SmartChoices: Hybridizing Programming and Machine Learning

We present SmartChoices, an approach to making machine learning (ML) a f...
research
08/05/2018

Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262

The use of machine learning (ML) is on the rise in many sectors of softw...

Please sign up or login with your details

Forgot password? Click here to reset