The field of safety-critical systems and AI-enabled technologies is rapidly evolving, with a growing focus on integrating agile methods, human-centered requirements engineering, and formal verification techniques. Recent research has explored the application of agile frameworks in aerospace software development, highlighting the potential for improved efficiency and compliance with regulatory standards. Additionally, there is a increasing emphasis on human-centered requirements engineering, recognizing the importance of social responsibility and usability in critical systems. The development of AI-enabled systems, particularly in autonomous vehicles and robotic missions, also poses new challenges and opportunities for requirements engineering and formal verification. Noteworthy papers in this area include 'CertiA360: Enhance Compliance Agility in Aerospace Software Development' and 'Towards Requirements Engineering for GenAI-Enabled Software: Bridging Responsibility Gaps through Human Oversight Requirements', which propose innovative solutions for automating compliance and addressing responsibility gaps in GenAI-enabled systems.
Advancements in Safety-Critical Systems and AI-Enabled Technologies
Sources
CertiA360: Enhance Compliance Agility in Aerospace Software Development
A Comparative Evaluation of Prominent Methods in Autonomous Vehicle Certification
Human-Centred Requirements Engineering for Critical Systems: Insights from Disaster Early Warning Applications
Towards Requirements Engineering for GenAI-Enabled Software: Bridging Responsibility Gaps through Human Oversight Requirements
Ontology-Driven Model-to-Model Transformation of Workflow Specifications
Final Happiness: What Intelligent User Interfaces Can Do for the lonely Dying
A Practical Implementation of Customized Scrum-Based Agile Framework in Aerospace Software Development Under DO-178C Constraints
Towards A Catalogue of Requirement Patterns for Space Robotic Missions
FHIRconnect: Towards a seamless integration of openEHR and FHIR
Behavior Trees vs Executable Ontologies: a Comparative Analysis of Robot Control Paradigms
From Machine Learning Documentation to Requirements: Bridging Processes with Requirements Languages
RE for AI in Practice: Managing Data Annotation Requirements for AI Autonomous Driving Systems
Data Annotation Quality Problems in AI-Enabled Perception System Development