Includes bibliographical references and index.

Preface -- AI for software design. Interweaving ai and behavioral programming towards better programming environments -- AI techniques for software requirements prioritization -- Agent-based software programming. Social commitments for engineering interaction in distributed systems -- Intelligent agents are more complex: initial empirical findings -- AI for software development. Sequence-to-sequence learning for automated software artifact generation -- Machine learning to support code reviews in continuous integration -- Software fusion: deep design learning with deterministic Laplacian verification -- Using artificial intelligence for auto-generating software for cyber-physical applications -- AI for software testing. On the application of machine learning in software testing -- Creating test oracles using machine learning techniques -- Intelligent risk based analysis methodology -- A qualitative reasoning model for software testing, based on combinatorial geometry -- AI for software debugging. AI-based spreadsheet debugging -- Artificial intelligence methods for software debugging -- Index.

"Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges." "This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc)." "All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering."-- Publisher's website.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat reader.