Conjecture and Inquiry: Quantifying Software Performance Requirements via Interactive Retrieval-Augmented Preference Elicitation

arXiv cs.CL / 4/24/2026

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Key Points

The paper targets a core software engineering challenge: turning natural-language software performance requirements into mathematical formulations despite ambiguity and uncertainty in stakeholder interpretation.
It introduces IRAP, an interactive retrieval-augmented preference elicitation framework that converts requirements into mathematical functions while reducing stakeholder cognitive load.
IRAP explicitly leverages problem-specific knowledge to retrieve and reason about stakeholder preferences, and uses this to structure a progressive, interactive elicitation process.
Experiments on four real-world datasets against 10 state-of-the-art baselines show IRAP achieves consistent superiority, including reported up to 40x improvements with as few as five interaction rounds.
Overall, the work positions interactive retrieval-augmented preference elicitation as an effective way to operationalize performance requirements with improved precision and efficiency.

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 approach that quantifies performance requirements into mathematical functions via interactive retrieval-augmented preference elicitation. IRAP differs from the others in that it explicitly derives from problem-specific knowledge to retrieve and reason the preferences, which also guides the progressive interaction with stakeholders, while reducing the cognitive overhead. Experiment results against 10 state-of-the-art methods on four real-world datasets demonstrate the superiority of IRAP on all cases with up to 40x improvements under as few as five rounds of interactions.