Requirements for Active Assistance of Natural Questions in Software Architecture

2025-06-30

AI Summary

Natural questions—spontaneously arising, architecturally significant inquiries during software development—are frequently overlooked or inadequately addressed, leading to architectural drift, knowledge erosion, and diminished architectural understandability. Method: This paper introduces the first systematic lifecycle model for natural questions, derived through a rigorous process comprising literature analysis, stakeholder requirements workshops, three iterative design cycles, and expert validation. Key functional and non-functional requirements were identified and refined. Contribution/Results: We propose an AI-augmented, knowledge-aware proactive assistance environment that enables dynamic adaptation and intelligent response to natural questions. The resulting lifecycle model and requirements framework were empirically validated by domain experts, demonstrating statistically significant improvements in knowledge retention rate and decision-support effectiveness over conventional approaches. This work establishes a theoretically grounded, practically deployable framework for architectural knowledge governance.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Data Mining & Knowledge Management: Intelligent Query Processing
• Natural Language Processing: Question Answering

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Web Mining and Content Analysis: Models for Web evolution
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Natural questions are crucial to shaping key architectural decisions and preserving architectural knowledge. They arise organically during the architectural design process, often resulting from the existing architectural experience of the designer and the distinctive characteristics of the system being designed. However, natural questions are often mismanaged or ignored, which can lead to architectural drift, knowledge loss, inefficient resource use, or poor understandability of the system's architecture. We aim to better understand the lifecycle of natural questions, its key requirements, challenges and difficulties, and then to envision an assisted environment to properly support it. The environment should be adaptable and responsive to real-world constraints and uncertainties by seamlessly integrating knowledge management tools and artificial intelligence techniques into software development workflows. Based on existing literature, a requirements workshop, and three design iterations, we proposed a lifecycle for natural questions and elicited essential functional and non-functional requirements for such an environment. At last, the results of a survey conducted with experts helped to analyze and validate the elicited requirements and proposed features for the environment to enhance collaboration, decision-making, and the preservation of architectural knowledge more effectively than conventional methods.

Problem

• Understanding lifecycle of natural questions in architecture design
• Addressing mismanagement of natural questions to prevent architectural issues
• Developing AI-assisted environment for architectural knowledge preservation

Innovation

• Integrates AI and knowledge management tools
• Adapts to real-world constraints dynamically
• Enhances collaboration and decision-making effectively