The goal of this workshop is to foster the integration between SE and AI communities to improve research results, teaching and mentoring, and ultimately industrial practice.
Topics of interest include but are not limited to:
AI techniques and approaches for:
optimization, transformation and configuration management
software reuse, evolution, maintenance and refactoring
mining software repositories and categorization
reverse engineering and program comprehension
concurrent/parallel software development and maintenance
ontology and other semantic aspects in software engineering
business process management and business rules
aspect mining and pattern mining
cost analysis and risk assessment in software projects
model-driven development, domain modeling and software language engineering (e.g., DSL)
rapid prototyping
Software Modeling techniques for explainable AI
Tools for combining AI and SE
Quantum artificial intelligence for software engineering
Industrial Case Studies in SE Intelligence
Benchmarks for SE Intelligence
Intelligent Software Bots
Intelligent agent-based software engineering
Object-oriented and aspect-oriented approaches to implement and validate AI techniques and systems
Formal methods for AI techniques
AI for emerging paradigms and systems (e.g., big data, cloud computing and Internet of Things)
Software for knowledge acquisition and representation
Software metrics applied to AI techniques
Intelligent Search engines
User Interfaces