# SEER: Sustainability Enhanced Engineering of Software Requirements

arXiv: https://arxiv.org/abs/2510.08981 · HTML: https://mlsanity.com/paper/2510.08981/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 119 references that are in the map.
- First posted on arXiv 10 Oct 2025.

## Builds on (most cited first, 15 of 15)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities](https://mlsanity.com/paper/2507.06261/) (2025)
- [Multi-Agent Collaboration Mechanisms: A Survey of LLMs](https://mlsanity.com/paper/2501.06322/) (2025)
- [Chain-of-Verification Reduces Hallucination in Large Language Models](https://mlsanity.com/paper/2309.11495/) (2023)
- [Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG](https://mlsanity.com/paper/2501.09136/) (2025)
- [A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models](https://mlsanity.com/paper/2303.10420/) (2023)
- [Generative AI for Requirements Engineering: A Systematic Literature Review](https://mlsanity.com/paper/2409.06741/) (2024)
- [Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects](https://mlsanity.com/paper/2503.04783/) (2025)
- [RECOVER: Toward Requirements Generation from Stakeholders' Conversations](https://mlsanity.com/paper/2411.19552/) (2024)
- [Measuring Determinism in Large Language Models for Software Code Review](https://mlsanity.com/paper/2502.20747/) (2025)
- [TAPHSIR: Towards AnaPHoric Ambiguity Detection and ReSolution In Requirements](https://mlsanity.com/paper/2206.10227/) (2022)
- [Automated Non-Functional Requirements Generation in Software Engineering with Large Language Models: A Comparative Study](https://mlsanity.com/paper/2503.15248/) (2025)
- [The Sustainability Assessment Framework Toolkit: A Decade of Modeling Experience](https://mlsanity.com/paper/2405.01391/) (2024)
- [From Domain Documents to Requirements: Retrieval-Augmented Generation in the Space Industry](https://mlsanity.com/paper/2507.07689/) (2025)
- [Perspectives, Needs and Challenges for Sustainable Software Engineering Teams: A FinServ Case Study](https://mlsanity.com/paper/2509.12466/) (2025)

## Abstract (arXiv)

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.