Optimising the software development process with artificial intelligence

Contributor(s):

Material type: Text

TextSeries: Natural Computing Series (NCS)Publication details: Springer Singapore 2023Description: xvi, 344 pISBN:

9789811999475

Subject(s):

DDC classification:

006.3 ROM

Summary: This book offers a practical introduction to the use of artificial intelligence (AI) techniques to improve and optimise the various phases of the software development process, from the initial project planning to the latest deployment. All chapters were written by leading experts in the field and include practical and reproducible examples. Following the introductory chapter, Chapters 2-9 respectively apply AI techniques to the classic phases of the software development process: project management, requirement engineering, analysis and design, coding, cloud deployment, unit and system testing, and maintenance. Subsequently, Chapters 10 and 11 provide foundational tutorials on the AI techniques used in the preceding chapters: metaheuristics and machine learning. Given its scope and focus, the book represents a valuable resource for researchers, practitioners and students with a basic grasp of software engineering. (https://link.springer.com/book/10.1007/978-981-19-9948-2)

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Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks		1	Available		008524

Table of contents:
Front Matter
Pages i-xvi
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Introduction
José Raúl Romero, Inmaculada Medina-Bulo, Francisco Chicano
Pages 1-16
Planning and Analysis
Front Matter
Pages 17-17
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Artificial Intelligence in Software Project Management
Liyan Song, Leandro L. Minku
Pages 19-65
Requirements Engineering
Fitsum Kifetew, Anna Perini, Angelo Susi
Pages 67-91
Leveraging Artificial Intelligence for Model-based Software Analysis and Design
Antonio Garmendia, Dominik Bork, Martin Eisenberg, Thiago Ferreira, Marouane Kessentini, Manuel Wimmer
Pages 93-117
Development and Deployment
Front Matter
Pages 119-119
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Statistical Models and Machine Learning to Advance Code Completion: Are We There Yet?
Tien N. Nguyen
Pages 121-153
Cloud Development and Deployment
José Antonio Parejo, Ana Belén Sánchez
Pages 155-176
Testing and Maintenance
Front Matter
Pages 177-177
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Automated Support for Unit Test Generation
Afonso Fontes, Gregory Gay, Francisco Gomes de Oliveira Neto, Robert Feldt
Pages 179-219
Artificial Intelligence Techniques in System Testing
Michael Felderer, Eduard Paul Enoiu, Sahar Tahvili
Pages 221-240
Intelligent Software Maintenance
Foutse Khomh, Mohammad Masudur Rahman, Antoine Barbez
Pages 241-275
AI Techniques from Scratch
Front Matter
Pages 277-277
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Metaheuristics in a Nutshell
Javier Ferrer, Pedro Delgado-Pérez
Pages 279-307
Foundations of Machine Learning for Software Engineering
Aurora Ramírez, Breno Miranda
Pages 309-344
[https://link.springer.com/book/10.1007/978-981-19-9948-2]

This book offers a practical introduction to the use of artificial intelligence (AI) techniques to improve and optimise the various phases of the software development process, from the initial project planning to the latest deployment. All chapters were written by leading experts in the field and include practical and reproducible examples.
Following the introductory chapter, Chapters 2-9 respectively apply AI techniques to the classic phases of the software development process: project management, requirement engineering, analysis and design, coding, cloud deployment, unit and system testing, and maintenance. Subsequently, Chapters 10 and 11 provide foundational tutorials on the AI techniques used in the preceding chapters: metaheuristics and machine learning. Given its scope and focus, the book represents a valuable resource for researchers, practitioners and students with a basic grasp of software engineering.

(https://link.springer.com/book/10.1007/978-981-19-9948-2)

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