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Analysis of Online Discussions in Support of Requirements Discovery

Feedback about software applications and services that end-
users express through web-based communication platforms represents
an invaluable knowledge source for diverse software engineering tasks,
including requirements elicitation. Research work on automated analysis
of textual messages in app store reviews, open source software (OSS)
mailing-lists and user forums has been rapidly increasing in the last five
years. NLP techniques are applied to filter out irrelevant data, text min-
ing and automated classification techniques are then used to classify
messages into different categories, such as bug report and feature re-
quest. Our research focuses on online discussions that take place in user
forums and OSS mailing-lists, and aims at providing automated analysis
techniques to discover contained requirements. We present
a speech-acts based analysis technique, and experimentally evaluate it
on a dataset taken from a widely used OSS project.

A zip archive containing the dataset and ARFF files for training models in Weka is available for download.

Research topics: