Not logged in.

Quick Search - Contribution

Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title ARdoc: App Reviews Development Oriented Classifier
Organization Unit
Authors
  • Sebastiano Panichella
  • Andrea Di Sorbo
  • Emitza Guzman
  • Corrado Aaron Visaggio
  • Gerardo Canfora
  • Harald Gall
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Event Title 24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering
Event Type conference
Event Location Seattle
Event Start Date November 13 - 2016
Event End Date November 18 - 2016
Place of Publication Seattle
Publisher ACM
Abstract Text Google Play, Apple App Store and Windows Phone Store are well known distribution platforms where users can download mobile apps, rate them and write review comments about the apps they are using. Previous research studies demonstrated that these reviews contain important information to help developers improve their apps. However, analyzing reviews is challenging due to the large amount of reviews posted every day, the unstructured nature of reviews and its varying quality. In this demo we present ARdoc, a tool which combines three techniques: (1) Natural Language Parsing (NLP), (2) Text Analysis (TA) and (3) Sentiment Analysis (SA) to automatically classify useful feedback contained in app reviews important for performing software maintenance and evolution tasks. Our quantitative and qualitative analysis (involving mobile professional developers) demonstrate that ARdoc correctly classi�es feedback useful for maintenance perspectives in user reviews with high precision (ranging between 84% and 89%), recall (ranging between 84% and 89%), and an F-Measure (ranging between 84% and 89%). While evaluating our tool we also found that ARdoc substantially helps to extract important maintenance tasks for real world applications. Demo URL: https://youtu.be/Baf18V6sN8E Demo Web Page: http://www.ifi.uzh.ch/seal/people/panichella/tools/ARdoc.html
Related URLs
Digital Object Identifier 10.1145/2950290.2983938
Other Identification Number merlin-id:13544
PDF File Download from ZORA
Export BibTeX
EP3 XML (ZORA)