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Educating Future Software Architects in the Art and Science of Analysing Software Data.

  • We report the design and teaching experience of a Master-level seminar course on quantitative and empirical software engineering. The course combines elements of traditional literature seminars with active learning by scientific project work, in particular quantitative mixed-method analyses of open source systems. It also provides short introductions and refreshers to data mining and statistical analysis, and discusses the nature and practice of scientific knowledge inference. Student presentations of published research, augmented by summary reports, bridge to standard seminars. We discuss our educational goals and the course structure derived from them. We review research questions addressed by students in mini research reports, and analyse them as tokens on how junior-level software engineers perceive the potential of empirical software engineering research. We assess challenges faced, and discuss possible solutions.

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Metadaten
Author:Wolfgang MauererORCiDGND, Stefanie ScherzingerORCiD
URL / DOI:http://ceur-ws.org/Vol-2531/paper10.pdf
Parent Title (English):SEUH 2020: Software Engineering im Unterricht der Hochschulen, Tagungsband des 17. Workshops "Software Engineering im Unterricht der Hochschulen", Innsbruck, Österreich, 26. - 27.02.2020
Publisher:RWTH Aachen
Editor:Stephan Krusche, Stefan Wagner
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2020
Release Date:2022/04/11
First Page:56
Last Page:60
Andere Schriftenreihe:CEUR workshop proceedings ; 2531
Institutes:Fakultät Informatik und Mathematik
Fakultät Informatik und Mathematik / Labor für Digitalisierung (LFD)
Begutachtungsstatus:peer-reviewed
research focus:Digitalisierung
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International