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Context: The daily work of software architects relies not only on technical expertise, but also on architecture knowledge (AK), which entails the architecture design itself together with the taken decisions and assumptions that provide the rationale for the chosen software solution. However, there is a pressing need to also incorporate sustainability aspects into the complete AK process, i.e., capturing decisions and the design towards software systems that are environmentally, economically, and socially balanced in the long term. Objective: The goal of this study is twofold. First, we aim to provide the fundamental concepts currently used in industry practices to represent and communicate AK. Second, building on this understanding and uncovered insights, we want to explore where sustainability can be applied in such daily practice and how sustainability can be addressed in the existing AK process. Method: We present an empirical study, using the same qualitative research methods applied in two independent industrial contexts. In total, the study encompasses a questionnaire survey with 49 participants, semi-structured interviews with 27 practitioners, and two focus groups. Results: Based on the insights gained from combining our findings, we (i) provide a map of applied concepts for communicating and representing AK in two large enterprises, (ii) present a set of tangible recommendations, and (iii) introduce an approach consisting of an action plan for carving sustainability into current software architecture practice and a reusable methodology applicable to other domains and companies. Conclusion: This paper extends our previous work by adding empirical investigations, and by refining as well as extending the results; this leads to a more comprehensive discussion of the implications for the future of software architecture practice.

Integrating (and evaluating) energy efficiency tactics into daily industrial practice is challenging. This paper addresses the experimental evaluation of energy efficiency tactics in industrial contexts. Based on different real-world scenarios, we assess five energy efficiency tactics for cloud-based software through individual experiments conducted across two companies. The results of the experiments show significant improvements in energy efficiency for three tactics, with two others showing enhanced efficiency albeit without statistical significance. In addition to the experiments, we draw lessons learned and practical insights into utilizing tactics in industrial contexts. Our results could guide practitioners in selecting and applying the most suitable tactic for their individual context. By linking tactics that emerged in the literature with evidence-based measures, we help including sustainability in software architecture design decision making.

In the past decade, research on measuring and assessing the environmental impact of software has gained significant momentum in science and industry. However, due to the large number of research groups, measurement setups, procedure models, tools, and general novelty of the research area, a comprehensive research framework has yet to be created. The literature documents several approaches from researchers and practitioners who have developed individual methods and models, along with more general ideas like the integration of software sustainability in the context of the UN Sustainable Development Goals, or science communication approaches to make the resource cost of software transparent to society. However, a reference measurement model for the energy and resource consumption of software is still missing. In this article, we jointly develop the Green Software Measurement Model (GSMM), in which we bring together the core ideas of the measurement models, setups, and methods of over 10 research groups in four countries who have done pioneering work in assessing the environmental impact of software. We briefly describe the different methods and models used by these research groups, derive the components of the GSMM from them, and then we discuss and evaluate the resulting reference model. By categorizing the existing measurement models and procedures and by providing guidelines for assimilating and tailoring existing methods, we expect this work to aid new researchers and practitioners who want to conduct measurements for their individual use cases.