Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-3483
Authors: Vetrò, Antonio
Ognawala, Saahil
Méndez Fernández, Daniel
Wagner, Stefan
Title: Fast feedback cycles in empirical software engineering research
Issue Date: 2015
metadata.ubs.publikation.typ: Konferenzbeitrag
metadata.ubs.publikation.source: 37th International Conference on Software Engineering (ICSE'15)
URI: http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-99159
http://elib.uni-stuttgart.de/handle/11682/3500
http://dx.doi.org/10.18419/opus-3483
metadata.ubs.bemerkung.extern: This is the authors' version of the work. Copyright is held by IEEE.
Abstract: Background/Context: Gathering empirical knowledge is a time consuming task and the results from empirical studies often are soon outdated by new technological solutions. As a result, the impact of empirical results on software engineering practice is often not guaranteed. Objective/Aim: In this paper, we summarize the ongoing discussion on "Empirical Software Engineering 2.0" as a way to improve the impact of empirical results on industrial practices. We propose a way to combine data mining and analysis with domain knowledge to enable fast feedback cycles in empirical software engineering research. Method: We identify the key concepts on gathering fast feedback in empirical software engineering by following an experience-based line of reasoning by argument. Based on the identified key concepts, we design and execute a small proof of concept with a company to demonstrate potential benefits of the approach. Results: In our example, we observed that a simple double feedback mechanism notably increased the precision of the data analysis and improved the quality of the knowledge gathered. Conclusion: Our results serve as a basis to foster discussion and collaboration within the research community for a development of the idea.
Appears in Collections:05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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