Paper Info
Title
Fast feedback cycles in empirical software engineering research
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Gathering empirical knowledge is a time consuming task and the results from empirical studies often are soon outdated by new technological solutions.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.
Year
DOI
Venue
2015
10.1109/ICSE.2015.198
ICSE
Keywords
Field
DocType
Empirical methods, Research methods, Data mining, Knowledge transfer
Data science,Software Engineering Process Group,Software analytics,Systems engineering,Feature-oriented domain analysis,Computer science,Empirical process (process control model),Software construction,Software development,Empirical research,Social software engineering
Conference
Volume
ISSN
ISBN
2
0270-5257
978-1-4799-1934-5
Citations 
PageRank 
References 
3
0.48
14
Authors
4
Name
Order
Citations
PageRank
Antonio Vetro1222.79
Saahil Ognawala2224.05
Daniel Méndez Fernández331234.66
Stefan Wagner474855.74