From Scattered to Structured: A Vision for Automating Architectural Knowledge Management

TL;DR

This paper proposes a comprehensive automated pipeline to extract, link, and consolidate architectural knowledge from diverse software artifacts, aiming to improve access, consistency, and maintenance of software architectures.

Contribution

It introduces a novel vision for automating architectural knowledge management through extraction, linking, inconsistency resolution, and knowledge base integration.

Findings

Conceptual framework for automated architectural knowledge extraction.

Design of a unified schema for heterogeneous artifacts.

Potential for improved architecture conformance and impact analysis.

Abstract

Software architecture is inherently knowledge-centric. The architectural knowledge is distributed across heterogeneous software artifacts such as requirements documents, design diagrams, code, and documentation, making it difficult for developers to access and utilize this knowledge effectively. Moreover, as systems evolve, inconsistencies frequently emerge between these artifacts, leading to architectural erosion and impeding maintenance activities. We envision an automated pipeline that systematically extracts architectural knowledge from diverse artifacts, links them, identifies and resolves inconsistencies, and consolidates this knowledge into a structured knowledge base. This knowledge base enables critical activities such as architecture conformance checking and change impact analysis, while supporting natural language question-answering to improve access to architectural knowledge. To realize this vision, we plan to develop specialized extractors for different artifact types, design a unified knowledge representation schema, implement consistency checking mechanisms, and integrate retrieval-augmented generation techniques for conversational knowledge access.