Dominik Seichter

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Collaborative development of software products across organisational boundaries in software ecosystems adds new challenges to existing software engineering processes. We propose a new approach for handling the diverse software artefacts in ecosystems by adapting features from social network sites. We promote artefacts to first-class citizens in such(More)
In industrial settings, products are rarely developed by one organization alone. Software vendors and suppliers typically maintain their own product lines, which can contribute to a larger (multi) product line. The teams involved often use different approaches and tools to manage the variability of their systems. It is unrealistic to assume that all(More)
The volume of data archived in open source software project repositories makes automated, quantitative techniques attractive for extracting and analyzing information from these archives. However, many kinds of archival data include blocks of natural language text that are difficult to analyze automatically. This paper introduces a qualitative analysis(More)
Content analysis is a useful approach for analyzing unstructured software project data, but it is labor-intensive and slow. Can automated text classification (using supervised machine learning) be used to reduce the labor or improve the speed of content analysis? We conducted a case study involving data from a previous study that employed content analysis(More)
There have been several proposals to describe the variability of software product lines by using modeling languages. In larger organizations or projects (e.g., multi product line environments) this can lead to a situation where multiple variability modeling techniques are used simultaneously. Rather than enforcing a single modeling language, we present an(More)
Open Source software is competing successfully in many areas. The commercial sector is recognizing the benefits offered by Open Source development methods that lead to high quality software. Can these benefits be realized in specialized domains where expertise is rare? This study examined discussion forums of an Open Source project in a particular(More)
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