SEER: Sustainability Enhanced Engineering of Software Requirements

2025-10-09

AI Summary

Existing software sustainability assessments predominantly focus on design and implementation phases, lacking actionable, scalable methods for the requirements engineering phase and relying heavily on manual effort, thereby impeding practical adoption. Method: This paper introduces the first sustainability framework tailored to requirements engineering, comprising three stages—identification, assessment, and optimization—and advances sustainability evaluation to the earliest requirements elicitation stage. It innovatively integrates a large language model (Gemini 2.5) with agent-based Retrieval-Augmented Generation (RAG), enabling semantic-driven, automated identification and optimization of sustainability requirements grounded in a structured sustainability requirement taxonomy. Contribution/Results: Evaluated across four cross-domain industrial projects, the framework significantly improves sustainability coverage at the requirements stage, overcomes the implementation gap of high-level sustainability guidelines, and establishes a novel paradigm for embedding environmental, social, technical, and economic sustainability objectives early in the software lifecycle.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Planning, Routing, and Scheduling: Planning with Language Models

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• Responsible Web: Sustainability and climate impact of web technologies

Abstract

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.

Problem

• Addressing sustainability concerns in early software requirements engineering phase
• Identifying and evaluating sustainability requirements from a general taxonomy
• Optimizing system requirements that fail to meet sustainability criteria

Innovation

• Framework integrates sustainability into requirements engineering
• Uses large language models for reasoning capabilities
• Implements agentic RAG approach for requirement optimization