Conjecture and Inquiry: Quantifying Software Performance Requirements via Interactive Retrieval-Augmented Preference Elicitation
📰 ArXiv cs.AI
Learn to quantify software performance requirements using interactive retrieval-augmented preference elicitation, improving software engineering accuracy
Action Steps
- Formalize software performance requirements using natural language processing
- Apply interactive retrieval-augmented preference elicitation to quantify requirements
- Use IRAP to reduce uncertainty in human cognition and performance requirement interpretations
- Evaluate the effectiveness of IRAP in software engineering projects
- Integrate IRAP with existing software development methodologies
Who Needs to Know This
Software engineers and developers can benefit from this approach to reduce ambiguity in performance requirements, while researchers in AI and software engineering can explore new methods for preference elicitation
Key Insight
💡 Interactive retrieval-augmented preference elicitation can improve the accuracy of software performance requirements
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🚀 Quantify software performance requirements with IRAP! 🤖
Key Takeaways
Learn to quantify software performance requirements using interactive retrieval-augmented preference elicitation, improving software engineering accuracy
Full Article
Title: Conjecture and Inquiry: Quantifying Software Performance Requirements via Interactive Retrieval-Augmented Preference Elicitation
Abstract:
arXiv:2604.21380v1 Announce Type: cross Abstract: Since software performance requirements are documented in natural language, quantifying them into mathematical forms is essential for software engineering. Yet, the vagueness in performance requirements and uncertainty of human cognition have caused highly uncertain ambiguity in the interpretations, rendering their automated quantification an unaddressed and challenging problem. In this paper, we formalize the problem and propose IRAP, an approac
Abstract:
arXiv:2604.21380v1 Announce Type: cross Abstract: Since software performance requirements are documented in natural language, quantifying them into mathematical forms is essential for software engineering. Yet, the vagueness in performance requirements and uncertainty of human cognition have caused highly uncertain ambiguity in the interpretations, rendering their automated quantification an unaddressed and challenging problem. In this paper, we formalize the problem and propose IRAP, an approac
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