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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Using psycho-physiological measures to assess task difficulty in software development
Organization Unit
Authors
  • Thomas Fritz
  • Andrew Begel
  • Sebastian Müller
  • Serap Yigit-Elliott
  • Manuela Züger
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
ISBN 978-1-4503-2756-5
Page Range 402 - 413
Event Title International Conference on Software Engineering (ICSE)
Event Type conference
Event Location Hyderabad
Event Start Date May 31 - 2014
Event End Date June 7 - 2014
Publisher ACM
Abstract Text Software developers make programming mistakes that cause serious bugs for their customers. Existing work to detect problematic software focuses mainly on post hoc identification of correlations between bug fixes and code. We propose a new approach to address this problem --- detect when software developers are experiencing difficulty while they work on their programming tasks, and stop them before they can introduce bugs into the code. In this paper, we investigate a novel approach to classify the difficulty of code comprehension tasks using data from psycho-physiological sensors. We present the results of a study we conducted with 15 professional programmers to see how well an eye-tracker, an electrodermal activity sensor, and an electroencephalography sensor could be used to predict whether developers would find a task to be difficult. We can predict nominal task difficulty (easy/difficult) for a new developer with 64.99% precision and 64.58% recall, and for a new task with 84.38% precision and 69.79% recall. We can improve the Naive Bayes classifier's performance if we trained it on just the eye-tracking data over the entire dataset, or by using a sliding window data collection schema with a 55 second time window. Our work brings the community closer to a viable and reliable measure of task difficulty that could power the next generation of programming support tools.
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Digital Object Identifier 10.1145/2568225.2568266
Other Identification Number merlin-id:9045
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Additional Information Proceedings of the 36th International Conference on Software Engineering