Artificial Intelligence for Better Software Engineering Practice
Artificial Intelligence Applications for Improved Software Engineering Development: New Prospects brings together a wide-ranging set of chapters on how AI techniques can support real software engineering work. The emphasis is practical: estimation, requirements, design, testing, and maintenance all receive attention, with methods such as Bayesian networks, neural networks, knowledge engineering, and computational intelligence used as the tools of discussion.
Edited by Farid Meziane and Sunil Vadera, this volume offers a clear snapshot of the state of AI in software engineering at the time of publication. Rather than treating AI as a single solution, it shows how different techniques fit different stages of the development lifecycle and why uncertainty, evolving requirements, and limited data make software work such a strong candidate for intelligent approaches.
What the Book Covers
- Project management and cost estimation with Bayesian and optimization-based approaches
- Requirements engineering and specification, including scenario analysis and review support
- Software design and implementation through intelligent assistants and decision support
- Testing and maintenance with AI-informed analysis and rule mining
A Useful Reference for AI and Software Engineering Readers
The chapter-based structure makes the book easy to browse by topic, while the editorial focus gives it a coherent thread: using AI to make software development more informed, more adaptable, and more effective. It suits readers who want a research-oriented overview of the field as well as those looking for ideas that connect AI methods to everyday software engineering challenges.
If you are building a library around software engineering, intelligent systems, or applied AI, this is a strong cross-disciplinary title to have on hand.
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