Sustainability is one of the most critical issues today. Thus, the unsustainable consumption of resources, such as raw materials, CO2 emissions, and the Linear Economy needs to be changed. One framework for a more sustainable economy is the Circular Economy. Although the concept of the Circular Economy has been around since the 1990s, yet we are still far from enabling a Circular Economy. Therefore, a turnaround to the current linear economy as well as a change in society is necessary. In this paper, we get down to the essence of the status quo in the Circular Economy, identify the main barriers, such as lack of information, unsustainable economic models, ignorance, missing incentives, and propose software-driven solutions to tackle these challenges. Our solution extends the service description language by introducing the sustainability impact factor. The goal is to motivate end-users towards a more sustainable behavior without making massive restrictions on their lives.

No abstract

A well-structured, modular software architecture is known to support comprehensibility, maintainability and extensibility of a software system. To achieve this goal the software system is divided into components in such a way that its component structure is optimized regarding cohesion and coupling. But with increasing size and complexity identifying and evaluating a component structure can be rarely accomplished by humans manually.To support this task, we developed an approach using Spectral Clustering from the field of neural computation. Based on the different dependencies between software elements, our approach automatically forms a component structure of the analyzed software system. In a case study we demonstrate this approach on a software system of manually manageable size and complexity. The results are compared to the component structure skilled software architects manually formed. In most cases both variants, manually as well as automated, provide similar component structures. For this reason, the presented approach seems to be suitable for systems which are not manageable by hand.

The rapidly growing number of software-based features in the automotive domain as well as the special requirements in this domain ask for dedicated engineering approaches, models, and processes. Nowadays, software development in the automotive sector is generally developed as product line development, in which major parts of the software are kept adaptable in order to enable reusability of the software in different vehicle variants. In addition, reuse also plays an important role in the development of new vehicle generations in order to reduce development costs. Today, a high number of methods and techniques exist to support the product line driven development of software in the automotive sector. However, these approaches generally consider only partial aspects of development. In this paper, we present an in-depth literature study based on a conceptual model of artifacts and activities for the managed evolution of automotive software product line architectures. We are interested in the coverage of the particular aspects of the conceptual model and, thus, the fields covered in current research and research gaps, respectively. Furthermore, we aim to identify the methods and techniques used to implement automotive software product lines in general, and their usage scope in particular. As a result, this in-depth review reveals that none of the studies represent a holistic approach for the managed evolution of automotive software product lines. In addition, approaches from agile software development are of growing interest in this field.

No abstract