Kalech M., Abreu R., Last M. (Eds.) Artificial Intelligence Methods For Software Engineering

World Scientific, 2021. — 457 p. — ISBN: 978-981-123-991-5.Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE). 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.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
Agents are More Complex: Initial Empirical Findings
AI for Software Development
5. 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-based Spreadsheet Debugging
Artificial Intelligence Methods for Software Debugging