Toward a Sustainable Software Architecture Community: Evaluating ICSA's Environmental Impact
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arXiv
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| Format: | Preprint |
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2026
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| author | Moghaddam, Mahyar T. Alipour, Mina Worm, Torben Kjærgaard, Mikkel Baun |
| author_facet | Moghaddam, Mahyar T. Alipour, Mina Worm, Torben Kjærgaard, Mikkel Baun |
| contents | Generative AI (GenAI) tools are increasingly integrated into software architecture research, yet the environmental impact of their computational usage remains largely undocumented. This study presents the first systematic audit of the carbon footprint of both the digital footprint from GenAI usage in research papers, and the traditional footprint from conference activities within the context of the IEEE International Conference on Software Architecture (ICSA). We report two separate carbon inventories relevant to the software architecture research community: i) an exploratory estimate of the footprint of GenAI inference usage associated with accepted papers within a research-artifact boundary, and ii) the conference attendance and operations footprint of ICSA 2025 (travel, accommodation, catering, venue energy, and materials) within the conference time boundary. These two inventories, with different system boundaries and completeness, support transparency and community reflection. We discuss implications for sustainable software architecture, including recommendations for transparency, greener conference planning, and improved energy efficiency in GenAI operations. Our work supports a more climate-conscious research culture within the ICSA community and beyond |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_04096 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Toward a Sustainable Software Architecture Community: Evaluating ICSA's Environmental Impact Moghaddam, Mahyar T. Alipour, Mina Worm, Torben Kjærgaard, Mikkel Baun Software Engineering Artificial Intelligence Generative AI (GenAI) tools are increasingly integrated into software architecture research, yet the environmental impact of their computational usage remains largely undocumented. This study presents the first systematic audit of the carbon footprint of both the digital footprint from GenAI usage in research papers, and the traditional footprint from conference activities within the context of the IEEE International Conference on Software Architecture (ICSA). We report two separate carbon inventories relevant to the software architecture research community: i) an exploratory estimate of the footprint of GenAI inference usage associated with accepted papers within a research-artifact boundary, and ii) the conference attendance and operations footprint of ICSA 2025 (travel, accommodation, catering, venue energy, and materials) within the conference time boundary. These two inventories, with different system boundaries and completeness, support transparency and community reflection. We discuss implications for sustainable software architecture, including recommendations for transparency, greener conference planning, and improved energy efficiency in GenAI operations. Our work supports a more climate-conscious research culture within the ICSA community and beyond |
| title | Toward a Sustainable Software Architecture Community: Evaluating ICSA's Environmental Impact |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2604.04096 |