Agile Software Development

Peter Wlodarczak (University of Southern Queensland, Toowoomba, Australia)

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English

Auerbach
08 December 2023

Project management; Agile programming; Software Engineering

Series: IT Pro Practice Notes

Agile Software Development is an introduction to agile software development methods. Agile methods try to diminish complexity, increase transparency, and reach a deployable product in a shorter time frame. Agile methods use an iterative and incremental approach to minimize risks and to avoid maldevelopment. The book gives a short introduction to agile methods and agile software development principles. It serves as a study book and as a reference manual. Based on the official Scrum Guide, the book also covers other topics such as best practices for agile software development and agile testing. It targets practitioners who want to start with agile software development, as well as developers or project managers who already use agile methodologies. The book can be read from the beginning, but each chapter has been written in a way so it can be read individually.

By: Peter Wlodarczak (University of Southern Queensland Toowoomba Australia)
Imprint: Auerbach
Country of Publication: United Kingdom
Dimensions: Height: 216mm, Width: 138mm,
Weight: 320g
ISBN: 9781032294643
ISBN 10: 1032294647
Series: IT Pro Practice Notes
Pages: 84
Publication Date: 08 December 2023
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

1. Introduction 2. Classical Model 3. Agile Methods 4. Scrum 5. Best Practices for the Dev Team 6. Testing 7. Appendix

Peter Wlodarczak is an IT consultant in Data Analytics and Machine Learning. Born in Basel, Switzerland, he holds a Master's degree and a PhD from the University of Southern Queensland, Australia. He has many years of experience in large software engineering and data analysis projects. He has published more than 20 papers and book chapters in this area and has presented his work in many conferences. His research interests include, among others, Machine Learning, eHealth, and Bio Computing.