From Requirements to Architecture: An AI-Based Journey to Semi-Automatically Generate Software Architectures

TL;DR

This paper proposes a semi-automatic AI-driven method to generate and evaluate multiple software architecture candidates from requirements, aiming to improve decision-making and reduce manual effort in architecture design.

Contribution

It introduces a novel approach combining AI techniques and large language models to generate and assess software architectures from requirements, enhancing efficiency and quality.

Findings

Potential for automated architecture generation from requirements

Enables trade-off analysis of multiple architecture candidates

Aims to improve quality and efficiency of architecture design

Abstract

Designing domain models and software architectures represents a significant challenge in software development, as the resulting architectures play a vital role in fulfilling the system's quality of service. Due to time pressure, architects often model only one architecture based on their known limited domain understanding, patterns, and experience instead of thoroughly analyzing the domain and evaluating multiple candidates, selecting the best fitting. Existing approaches try to generate domain models based on requirements, but still require time-consuming manual effort to achieve good results. Therefore, in this vision paper, we propose a method to generate software architecture candidates semi-automatically based on requirements using artificial intelligence techniques. We further envision an automatic evaluation and trade-off analysis of the generated architecture candidates using, e.g., the architecture trade-off analysis method combined with large language models and quantitative analyses. To evaluate this approach, we aim to analyze the quality of the generated architecture models and the efficiency and effectiveness of our proposed process by conducting qualitative studies.