Sustainability-Centric Software Development: A Quantitative Framework for the SDLC

Abstract

Although software systems increasingly shape energy consumption, economic output, and societal welfare, most development methods still prioritise schedule, cost, and functionality. This paper presents an approach to software development that prioritises sustainability by embedding environmental, economic, and social objectives into the SDLC from the very beginning. The framework represents sustainability as a set of quantifiable variables that are combined into a Global Sustainability Index (GSI). These metrics include operational energy and carbon footprint, total cost of ownership (TCO), maintainability index, defect density, and a normalised Social Impact Score (SIS). An empirical measurement architecture gathers runtime and process data for continuous improvement, while phase-level “sustainability budgets” direct trade-offs across requirements, design, implementation, testing, and operation. The framework is evaluated in a repeated-measures industrial study of six production software systems (758 KLOC in total, 58 engineers, six application domains), in which every system is observed over four counterbalanced release cycles governed respectively by the proposed framework and by three established approaches: GREENSOFT, GreenSDLC, and the Sustainability Quality Model (SQM). The proposed framework attains the highest GSI (0.86 ± 0.03), a statistically significant improvement of 10–19% over the competing frameworks (paired t-tests, all Holm-adjusted p < 0.002, Cohen’s dz > 2.5). Relative to current models, energy usage and carbon emissions are cut by 10–20%, and they are decreased by approximately 30% when compared to a no-framework baseline. Normalised maintainability and defect density both improve over a five-year timeframe, and total cost of ownership drops 4–9%. Consistently higher levels of social impact and stakeholder satisfaction are observed, particularly for user groups who are marginalised. Ninety-five percent confidence intervals and effect sizes are reported for every headline comparison, and the principal limitations of the framework are stated explicitly together with mitigation strategies. These results show that all three dimensions can be improved with explicit quantitative sustainability integration without a rise in long-term costs.