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In Software Engineering, reuse of artifacts is essential for high productivity. Di↵erent studies have shown that e cient reuse needs systematic planning and realization. Variability Management plays a key role in Software Product Line Engineering. We investigate code artifacts and variability models of a real-world Software Product Line over time in order to clarify whether code and variability model evolve congeneric. Furthermore, we suggest and test metrics that would allow detecting variability erosion in the code based on changes in the variability model.

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Variability Management (VM) is a key practice in the development of variant-rich systems. Over the years, attention has been paid to VM approaches adopted by traditional software product lines. The increasing demand for dynamic and highly configurable systems, however, calls for a closer look at the approaches used to develop these systems. We therefore conducted a survey with practitioners from organizations developing variant-rich systems in order to characterize the state of the practice. We also wanted to identify factors that might influence the adoption of specific VM approaches as well as the perception of problems/difficulties posed by those. We analyzed the answers of 31 respondents from thirteen countries and found that there is a correlation between the business domain and the adopted VM approaches. With regard to the problems/difficulties, the difficulty of assuring the quality of maintenance due to the explosion of dependencies was a major issue. This paper reports on relevant findings that could help companies to better understand their problems and researchers to design new/improved solutions

The embedded safety-critical system design and development industries are facing ever-increasing demands regarding the variety and flexibility of systems and devices from society. At a technical level, these demands result in more and more complex solutions that, at the same time, need to abide by stringent regulatory requirements and economic challenges, such as cost, performance and time to market