The rapid expansion of software development has significant environmental, technical, social, and economic impacts. Achieving the United Nations Sustainable Development Goals by 2030 compels developers to adopt sustainable practices. Existing methods mostly offer high-level guidelines, which are time-consuming to implement and rely on team adaptability. Moreover, they focus on design or implementation, while sustainability assessment should start at the requirements engineering phase. In this paper, we introduce SEER, a framework which addresses sustainability concerns in the early software development phase. The framework operates in three stages: (i) it identifies sustainability requirements (SRs) relevant to a specific software product from a general taxonomy; (ii) it evaluates how sustainable system requirements are based on the identified SRs; and (iii) it optimizes system requirements that fail to satisfy any SR. The framework is implemented using the reasoning capabilities of large language models and the agentic RAG (Retrieval Augmented Generation) approach. SEER has been experimented on four software projects from different domains. Results generated using Gemini 2.5 reasoning model demonstrate the effectiveness of the proposed approach in accurately identifying a broad range of sustainability concerns across diverse domains.
翻译:软件开发的快速扩张对环境、技术、社会和经济产生了重大影响。实现联合国2030年可持续发展目标迫使开发者必须采用可持续的实践方法。现有方法大多提供高层级指导原则,这些原则实施耗时且依赖于团队的适应能力。此外,这些方法主要关注设计或实现阶段,而可持续性评估应从需求工程阶段开始。本文提出了SEER框架,旨在解决软件开发早期阶段的可持续性问题。该框架分三个阶段运行:(i) 从通用分类法中识别与特定软件产品相关的可持续性需求;(ii) 基于已识别的可持续性需求,评估系统需求的可持续性程度;(iii) 对未能满足任何可持续性需求的系统需求进行优化。该框架利用大语言模型的推理能力和智能体RAG方法实现。SEER已在四个不同领域的软件项目上进行了实验。使用Gemini 2.5推理模型生成的结果表明,该方法能有效准确地识别跨不同领域的广泛可持续性问题。