Fast Feedback Cycles in Empirical Software Engineering Research

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Gathering empirical knowledge is a time consuming task and the results from empirical studies often are soon outdated by new technological solutions.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

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Gathering empirical knowledge is a time consuming task and the results from empirical studies often are soon outdated by new technological solutions.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

Empirical practice in software engineering

Experimental software engineering has been defined as the scientific approach to systematically evaluating software technologies by referring to predefined hypotheses using sound empirical methods. The purpose of this chapter is to give an overview of the history, current practice, and future of empirical practice in Software Engineering. In particular, based on what we have learned from 20 years of research in empirical software engineering, we describe the empirical approach we are currently using in terms of a scientific approach to applied research and as a means for systematic evaluation