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Analysis of Online Discussions in Support of Requirements Discovery

  • Itzel Morales-Ramirez
  • Fitsum Meshesha Kifetew
  • Anna Perini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10253)

Abstract

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 mining and automated classification techniques are then used to classify messages into different categories, such as bug report and feature request. 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. In this paper, we present a speech-acts based analysis technique, and experimentally evaluate it on a dataset taken from a widely used OSS project.

Keywords

Requirements engineering Linguistic analysis Sentiment analysis Automated classification techniques Speech-acts 

Notes

Acknowledgement

We thank Rob Weir for providing the OpenOffice dataset. This work is a result of the SUPERSEDE project, funded by the H2020 EU Framework Programme under agreement number 644018. The first author is partially funded by INFOTEC under the project “081-022-00-FORTALECIMIENTO E INVERSIÓN”.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Itzel Morales-Ramirez
    • 1
  • Fitsum Meshesha Kifetew
    • 2
  • Anna Perini
    • 2
  1. 1.INFOTECTlalpan, Mexico CityMexico
  2. 2.Software Engineering Research UnitFondazione Bruno KesslerTrentoItaly

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