DocumentCode
2441448
Title
Automatically detecting developer activities and problems in software development work
Author
Roehm, Tobias ; Maalej, Walid
Author_Institution
Tech. Univ. Munchen, Munich, Germany
fYear
2012
fDate
2-9 June 2012
Firstpage
1261
Lastpage
1264
Abstract
Detecting the current activity of developers and problems they are facing is a prerequisite for a context-aware assistance and for capturing developers´ experiences during their work. We present an approach to detect the current activity of software developers and if they are facing a problem. By observing developer actions like changing code or searching the web, we detect whether developers are locating the cause of a problem, searching for a solution, or applying a solution. We model development work as recurring problem solution cycle, detect developer´s actions by instrumenting the IDE, translate developer actions to observations using ontologies, and infer developer activities by using Hidden Markov Models. In a preliminary evaluation, our approach was able to correctly detect 72% of all activities. However, a broader more reliable evaluation is still needed.
Keywords
hidden Markov models; ontologies (artificial intelligence); software engineering; ubiquitous computing; Hidden Markov Models; Web searching; automatically detecting developer activities; automatically detecting developer problems; context-aware assistance; ontologies; recurring problem solution cycle; software development work; Context; Hidden Markov models; Ontologies; Search problems; Software; Software engineering; Switches; activity detection; context-aware software engineering; machine learning; ontologies; task management;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering (ICSE), 2012 34th International Conference on
Conference_Location
Zurich
ISSN
0270-5257
Print_ISBN
978-1-4673-1066-6
Electronic_ISBN
0270-5257
Type
conf
DOI
10.1109/ICSE.2012.6227104
Filename
6227104
Link To Document