Workshop on Designing Resilient Intelligent Systems for Testability and Reliability
Advances in machine learning combined with the sensor, actuator and microprocessor technologies has made it feasible to incorporate intelligence into software systems with the ability to control and adapt their behavior in real time. Designing intelligent systems, therefore, has become and will be a norm in the future. These systems are likely to be highly distributed across machine and network boundaries with the potential for any of their elements to adapt based on what a system learns from its environment.
Managing the complexity that comes with designing for intelligence will be a responsibility that will necessarily fall on the architects and developers who will have to consider ways to ensure that these systems are robust , resilient and reliable. Additionally, due to their dynamic behavior, it is also critical that these systems be easily tested for their functional correctness as they continue to evolve and adapt to their operational environment.
Expected outcomes from this workshop include but are not limited to:
- Design concepts and techniques for creating architectures of intelligent systems to be more testable and reliable
- Methods for using architectures of robust and resilient intelligent systems to produce test artifacts
- Architectural patterns or tactics for making intelligent systems more testable and reliable
- Analytics for making intelligent systems robust and resilient through early fault prediction
- New challenges, research problems, emerging trends and industrial case studies for designing robust intelligent systems