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Improving LLM-assisted code generation through the use of architectural documents and implementation plans
Conference proceeding   Open access

Improving LLM-assisted code generation through the use of architectural documents and implementation plans

Humberto Cervantes, Rick Kazman and Yuanfang Cai
Proceedings of the 3rd International Workshop on Designing Software, pp 23-30
28 Jun 2026
DOI: https://doi.org/10.1145/3786152.3788588
Featured in Collection :   Research Supported by Drexel Libraries' OA Programs
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https://doi.org/10.1145/3786152.3788588View
Published, Version of Record (VoR) Open Access via Drexel Libraries Read and Publish Program 2026 Open CC BY V4.0

Abstract

Software and its engineering -- Automatic programming
In this paper, we investigate LLM-assisted code generation using architectural documentation as a first-class input. Building on prior work that guides LLMs through Attribute-Driven Design (ADD), we propose a workflow in which the LLM synthesizes an implementation plan from requirements and an architecture document, and then generates code with human oversight. Using a ReAct-style agent as a case study, we perform three experiments and evaluate architectural conformance and functional correctness of a primary use case. In addition we capture size and modularity metrics using the DV8 tool. Our results show that incorporating architectural documentation substantially improves conformance and that adding an explicit implementation plan further enhances functional correctness and modularity.

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