Work

A Literature Review of Using Machine Learning in Software Development Life Cycle Stages

Year: 2021

Type: article

Abstract: The software engineering community is rapidly adopting machine learning for transitioning modern-day software towards highly intelligent and self-learning systems. However, the software engineering community is still discovering new ways how machine learning can offer help for various software development life cycle stages. In this article, we present a study on the use of machine learning across various software development life cycle stages. The overall aim of this article is to investigate the relationship between software development life cycle stages, and machine learning tools, techniques, and types. We attempt a holistic investigation in part to answer the question of whether machine learning favors certain stages and/or certain techniques.

Source: IEEE Access

DOI: 10.1109/access.2021.3119746

Authors: Saad Shafiq, Atif Mashkoor, Christoph Mayr-Dorn, Alexander Egyed

Institutions: Johannes Kepler University of Linz, Software Competence Center Hagenberg (Austria)

Language: English

Topic: Software Engineering Research

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,750

OpenAlex ID: W3205483668