Developer Views on Software Carbon Footprint and Its Potential for Automated Reduction
Paper in proceeding, 2023
In this study, we have conducted interviews and a survey (a) to explore developers’ existing opinions, knowledge, and practices with regard to carbon footprint and energy consumption, and (b), to identify the requirements that automated reduction tools must meet to ensure adoption. Our findings offer a foundation for future research on practices, guidelines, and automated tools that address software carbon footprint.
Genetic Improvement
Genetic Programming
Carbon Footprint
Energy Consumption
Sustainability
Author
Haozhou Lyu
Student at Chalmers
Gregory Gay
University of Gothenburg
Maiko Sakamoto
University of Tokyo
Search-Based Software Engineering. SSBSE 2023. Lecture Notes in Computer Science, vol 14415
Vol. 14415 LNC 35-51
San Francisco, USA,
Subject Categories
Software Engineering
DOI
10.1007/978-3-031-48796-5_3