DECA: Development Emails Content Analyzer

Author email: disorbo@unisannio.it,
Tool name: DECA
Description: Written development discussions occurring over different communication means (e.g. issue trackers, development mailing lists, or IRC chats) represent a precious source of information for developers, as well as for researchers interested to build recommender systems. Such discussions contain text having different purposes, e.g. discussing feature requests, bugs to fix etc. In this context, the manual classification or filtering of such discussions in according to their purpose would be a daunting and time-consuming task. In this demo we present DECA (Development Emails Content Analyzer), a tool which uses Natural Language Parsing to classify the content of development emails according to their purpose, identifying email fragments that can be used for specific maintenance tasks. We applied DECA on the discussions occurring on the development mailing lists related to Qt and Ubuntu projects. The results highlight a high precision (90%) and recall (70%) of DECA in classifying email content providing useful information to developers interested in accomplishing specific development tasks.
Bibtex: "@inproceedings{di2016deca, title={DECA: development emails content analyzer}, author={Di Sorbo, Andrea and Panichella, Sebastiano and Visaggio, Corrado A and Di Penta, Massimiliano and Canfora, Gerardo and Gall, Harald}, booktitle={2016 IEEE/ACM 38th International Conference on Software Engineering Companion (ICSE-C)}, pages={641--644}, year={2016}, organization={IEEE} }"
Link to public pdf: https://dl.acm.org/citation.cfm?id=2889170
Link to tool webpage: http://www.ifi.uzh.ch/en/seal/people/panichella/tools/DECA.html
Link to demo: https://youtu.be/FmwBuBaW6Sk
Category: None
Tags: distribution, and enhancement, maintenance
Year and Conference: 2017, ICSE
Terms of use