Abstract
Scientific research addressing the relation between software and sustainability is slowly maturing in two focus areas, related to ‘sustainable software’ and ‘software for sustainability’. The first is better understood and may include research foci like energy efficient software and software maintainability. It most-frequently covers ‘technical’ concerns. The second, ‘software for sustainability’, is much broader in both scope and potential impact, as it entails how software can contribute to sustainability goals in any sector or application domain. Next to the technical concerns, it may also cover economic, social, and environmental sustainability. Differently from researchers, practitioners are often not aware or well-trained in all four types of software sustainability concerns. To address this need, in previous work we have defined the Sustainability-Quality Assessment Framework (SAF) and assessed its viability via the analysis of a series of software projects. Nevertheless, it was never used by practitioners themselves, hence triggering the question: What can we learn from the use of SAF in practice? To answer this question, we report the results of practitioners applying the SAF to four industrial cases. The results show that the SAF helps practitioners in (1) creating a sustainability mindset in their practices, (2) uncovering the relevant sustainability-quality concerns for the software project at hand, and (3) reasoning about the inter-dependencies and trade-offs of such concerns as well as the related short- and long-term implications. Next to improvements for the SAF, the main lesson for us as researchers is the missing explicit link between the SAF and the (technical) architecture design.
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Notes
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SAF Toolkit, or Toolkit for short.
- 2.
- 3.
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7 Appendix: Custom Quality Attributes Definitions
7 Appendix: Custom Quality Attributes Definitions
CP1-1 (Efficiency): “Resources expended in relation to the accuracy, completeness and also less cost/time/human resources to conduct the research”
CP1-2 (Economic Risk Mitigation): “Mitigates risk to financial and economy for national/local level”
CP3-1 (Flexibility): “The system can be used in contexts beyond those initially specified in the requirements, such as controlling different assets”
CP3-2 (Time Behaviour): “Response, processing times and throughput rates of a system, when performing its functions, is real-time”
CP3-3 (Trust): “Users have confidence that a product or system will behave as intended.”
CP3-4 (User Error Protection): “System protects users against making errors by being as intuitive as possible”
CP4-1 (Effectiveness): “Complies data quality requirements both in input and output”
CP4-2 (Confidentiality): “The system ensures that data are accessible only to those authorized to have access. Additionally, data should not be used for negative reporting, but only for improving efficiency.” Note: This QA was re-defined in Project P4 but not included in the corresponding DM.
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Lago, P. et al. (2021). Designing for Sustainability: Lessons Learned from Four Industrial Projects. In: Kamilaris, A., Wohlgemuth, V., Karatzas, K., Athanasiadis, I.N. (eds) Advances and New Trends in Environmental Informatics. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-030-61969-5_1
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