Software Engineering for Intelligent Systems

Dear Colleagues,

Despite their novelty, AI systems are just software systems. Therefore, they need requirements engineering, architecture, testing, deployment and maintenance. On the other hand, they introduce new challenges due to training data dependency, non-determinism and erratic behaviour, which classical SE methods were are meant to deal with. Consequently, SE needs to be extended by new methods to handle learning-based components. We are looking for papers addressing those issues, in particular, the following:

• Requirements engineering concerning data and performance, goal oriented and scenario-oriented requirements, etc.
• Novel architectural patterns, software modules, and concepts of ML components.
• Methods ensuring modularity, interface design, versioning, and traceability.
• Feature engineering, clean code practices, design patterns, and reproducibility.
• Comparison of traditional software tests versus AI system tests (statistical testing, robustness, bias and fairness testing), and hybrid approaches to testing.
• Software development models and graphical methods for AI systems.
• etc.

Dr. Piotr Kosiuczenko
Guest Editor

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