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Gathering empirical knowledge is a time consuming task and the results from empirical studies often are soon outdated by new technological solutions.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

Combining Data Analytics with Team Feedback to Improve the Estimation Process in Agile Software Development

“…Concerning the latter one, we usually obtained it by bringing the analysis results printout to discussion with the product owners. For Project 1, the feedback was collected differently: the whole team participated and the results were continuously displayed on a wall in a common space, so that each team member was able to add his/her own ideas and observations at any time: this was intended as a simulation of the approach described in [22]. We could not apply the same strategy to the other projects because not all team members were located in Munich: however all product owners were there, so it was possible to gather their comments.…”

“…Estimation meeting -part 1 Each estimation meeting should take place in front of the estimation wall with a computer screen visible to all team members: according to the vision of the fast feedback cycles [22], practitioners should rely on the use of data (interactive) visualisations for their activities. Therefore the team can use the computer to access the original user story in JIRA and for its discussion (e.g.,to estimate user story is necessary to examine the current status of the product increment).…”

Empirical software engineering: From discipline to interdiscipline

“…What are their responsibilities and their levels of expertise? A further problem, finally, consists of that knowledge acquisition in software engineering is yet not always in tune with the pace of changes in our cases under investigation (e.g., industrial practices) [33].…”

Case studies in industry

“…For example, we need to be able to show them that a new code analysis technique, we want to investigate, has the potential to help them find defects faster. Finally, we also learnt that providing feedback early on and giving them quick results (such as in an iterative approach), helps to keep the participants interested and improves the results [14]. This also means that we have to be opportunistic in the subject and the case selection.…”