Fast feedback cycles in empirical software engineering research
Antonio Vetrò, Saahil Ognawala, Daniel Méndez, Stefan Wagner · mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) · 2015
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Gathering empirical knowledge is a time consuming task and the results from empirical studies often are soon outdated by new technological solutions.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