Artifact of Dynamic Agent Generation for Self-Adaptive Root Cause Analysis

Key Points

• The central aim is to develop a dynamic agent generation method to enhance root cause analysis in self-adaptive systems.
• Developed an algorithm for dynamic agent generation.
• Implemented the method in self-adaptive systems.
• Analyzed its effectiveness in identifying root causes of system failures.
• Improved accuracy of root cause identification by 30% compared to traditional methods.
• Reduced analysis time by 50% using the dynamic agents.
• Enhanced adaptability of the system in varied operational conditions.