Practical Feasibility of Sustainable Software Engineering Tools and Techniques

Abstract

While Sustainable Software Engineering (SSE) tools are widely studied in academia, their practical feasibility in industrial workflows, particularly in regulated environments, remains poorly understood. This study investigates how software practitioners perceive the feasibility of existing SSE tools and techniques, and examines the technical, organizational, and cultural factors shaping their adoption in practice. We identified prominent categories of SSE tools targeting energy consumption, green refactoring, and workload management, and evaluated them along three practitioner-relevant dimensions: installation, input requirements, and output formats. These were presented through an interactive web application and explored in workshops with 16 practitioners from a regulated financial-sector organization, followed by a survey of 27 software practitioners. Our findings suggest that the practitioners strongly favored tools that integrate into existing IDEs or pipelines, require minimal and locally scoped data access, and provide interpretable, actionable outputs such as dashboards or automated refactoring suggestions. In regulated settings, compliance requirements, approval processes, and time constraints significantly shaped feasibility perceptions. Our contribution lies in providing empirical evidence of these preferences alongside other factors that affect regulated industrial contexts. The findings offer actionable guidance for designing SSE tools that better align with real-world development workflows and organizational constraints.

Figures (6)

• Figure 1: Mixed-methods research design and flow, starting with ① a literature review to identify SSE tool categories (energy consumption, green refactoring, and workload management). ② A custom web application was used during ③ the workshop and ④ the survey. We conducted thematic and statistical analyses on workshop and survey data, respectively.
• Figure 2: UI screen: Tools
• Figure 3: Left: Packaged Tool installation example for Green Refactoring. Right: Explanations of Time-Based Profiling technique to measure energy consumption.
• Figure 4: Violin plots showing feasibility ratings (1–10) for different installation methods. The colored regions indicate the distribution and density of responses. Each dot represents an individual participant's rating. IDE plugins received the highest feasibility ratings in both datasets, while manual builds and hardware devices were consistently rated lowest.
• Figure 5: Violin plots showing feasibility ratings for different input data types. Workshop participants favored access to individual code files. Survey respondents rated full codebase access as most feasible and then individual code files.