Over the years, various thinking frameworks have been developed to address sustainability as a quality property of software-intensive systems. Notwithstanding, which quality concerns should be selected in practice that have a significant impact on sustainability remains a challenge.In this experience report, we propose the notion of variability features, i.e., specific software features which are implemented in a number of possible alternative variants, each with a potentially different impact on sustainability. We extended sustainability decision maps to incorporate these variability features into an already existing thinking framework. Our findings were derived from a qualitative case study and evaluated in an industrial context. Data was collected by analysing a real-world application and conducting working sessions together with expert interviews.The variability features allowed us to identify and evaluate alternative usage scenarios of one real-world software-intensive system, enabling data-driven sustainability choices and suggestions for professional practices. By providing concrete measurements, we can support software architects at design time, and decision makers towards achieving sustainability goals.
Variability Features: Extending Sustainability Decision Maps via an Industrial Case Study / Funke M.; Lago P.; Verdecchia R.. - ELETTRONICO. - (2023), pp. 54-60. (Intervento presentato al convegno 20th IEEE International Conference on Software Architecture Companion, ICSA-C 2023 tenutosi a ita nel 2023) [10.1109/ICSA-C57050.2023.00024].
Variability Features: Extending Sustainability Decision Maps via an Industrial Case Study
Verdecchia R.
2023
Abstract
Over the years, various thinking frameworks have been developed to address sustainability as a quality property of software-intensive systems. Notwithstanding, which quality concerns should be selected in practice that have a significant impact on sustainability remains a challenge.In this experience report, we propose the notion of variability features, i.e., specific software features which are implemented in a number of possible alternative variants, each with a potentially different impact on sustainability. We extended sustainability decision maps to incorporate these variability features into an already existing thinking framework. Our findings were derived from a qualitative case study and evaluated in an industrial context. Data was collected by analysing a real-world application and conducting working sessions together with expert interviews.The variability features allowed us to identify and evaluate alternative usage scenarios of one real-world software-intensive system, enabling data-driven sustainability choices and suggestions for professional practices. By providing concrete measurements, we can support software architects at design time, and decision makers towards achieving sustainability goals.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.