SEFeb 17, 2021

Selecting Features for the Next Release in a System of Systems Context

arXiv:2102.09063v2
AI Analysis

This addresses the complex decision-making problem for feature selection in smart city projects, which are incremental socio-technical systems.

The paper tackles the challenge of selecting features for software releases in smart city systems of systems by applying the multi-objective next release problem (MONRP) and proposes a technique using the scenario modeling language for Kotlin (SMLK) for feature modeling and validation, demonstrated with a proof-of-concept implementation.

Smart Cities are developing in parallel with the global trend towards urbanization. The ultimate goal of Smart City projects is to deliver a positive impact for the citizens and the socio-economic and ecological environment. This involves the challenge to derive concrete requirements for (technical) projects from overarching concepts like Quality of Life (QoL) and Subjective Well-Being (SWB). Linking long-term, impact oriented goals with project outputs and outcomes is a complex problem. Decision making on requirements and resulting features of single Smart City projects (or systems) is even more complex since cities are not like monolithic, hierarchical and well structured systems. Nevertheless, systems engineering provides concepts which support decision making in such situations. Complex socio-technical systems such as smart cities can be characterized as systems of systems (SoS). A SoS is composed of independently developed systems that nevertheless provide a higher-level integrated functionality. To add new functionality to a SoS, either existing systems must be extended or new systems must be developed and integrated. In both cases, the extension of functionality is usually done in small increments and structured via software releases. However, the decision which features to include in the next release is complex and difficult to manage when done manually. To address this, we make use of the multi-objective next release problem (MONRP) to search for an optimal set of features for a software release in a SoS context. In order to refine the search in an early planning phase, we propose a technique to model and validate the features using the scenario modeling language for Kotlin (SMLK). This is demonstrated with a proof-of-concept implementation.

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