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Gathering empirical knowledge is a time consuming task and the results from empirical studies often are soon outdated by new technological solutions.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 indus- trial practices. We propose a way to combine data mining and analysis with domain knowledge to enable fast feedback cycles between researchers and practitioners. 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 discus- sion and collaboration within the research community for a development of the idea.

Fast Feedback Cycles in Empirical Software Engineering Research / Vetro', Antonio; Ognawala, S.; Mendez Fernandez, D.; Wagner, S.. - ELETTRONICO. - (2015), pp. 583-586. (Intervento presentato al convegno 37th International Conference on Software Engineering tenutosi a Florence nel 16-24 May 2015) [10.1109/ICSE.2015.198].

Fast Feedback Cycles in Empirical Software Engineering Research

VETRO', ANTONIO;
2015

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Gathering empirical knowledge is a time consuming task and the results from empirical studies often are soon outdated by new technological solutions.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 indus- trial practices. We propose a way to combine data mining and analysis with domain knowledge to enable fast feedback cycles between researchers and practitioners. 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 discus- sion and collaboration within the research community for a development of the idea.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2587982
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