Integration of Machine Learning Algorithms in Agile Software Development Processes: a Comparative Study

EasyChair Preprint 12854

Abstract

This research paper explores the integration of machine learning (ML) algorithms within agile software development processes. Agile methodologies have gained widespread adoption due to their flexibility and adaptability to changing requirements in software development projects. Meanwhile, machine learning techniques have demonstrated significant advancements in various domains, offering opportunities for enhancing software development practices. This paper presents a comparative study examining different approaches to integrating ML algorithms in agile processes, evaluating their effectiveness, challenges, and potential benefits. Through a comprehensive analysis of existing literature and case studies, this paper aims to provide insights into the synergies between ML and agile methodologies, highlighting best practices and areas for future research.

Keyphrases: Agile Software Development, Integration, Software Development Lifecycle SDLC, machine learning

@booklet{EasyChair:12854,
  author    = {Wahaj Ahmed and Hiromi Morita},
  title     = {Integration of Machine Learning Algorithms in Agile Software Development Processes: a Comparative Study},
  howpublished = {EasyChair Preprint 12854},
  year      = {EasyChair, 2024}}