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SURF: summarizer of user reviews feedback


Di Sorbo, Andrea; Panichella, Sebastiano; Alexandru, Carol V; Visaggio, Corrado Aaron; Canfora, Gerardo (2017). SURF: summarizer of user reviews feedback. In: 39th IEEE/ACM International Conference on Software Engineering Companion, Buenos Aires, Argentina, 20 May 2017 - 28 May 2017. Institute of Electrical and Electronics Engineers, 55-58.

Abstract

Continuous Delivery (CD) enables mobile developers to release small, high quality chunks of working software in a rapid manner. However, faster delivery and a higher software quality do neither guarantee user satisfaction nor positive business outcomes. Previous work demonstrates that app reviews may contain crucial information that can guide developer’s software maintenance efforts to obtain higher customer satisfaction. However, previous work also proves the difficulties encountered by developers in manually analyzing this rich source of data, namely (i) the huge amount of reviews an app may receive on a daily basis and (ii) the unstructured nature of their content. In this paper, we propose SURF (Summarizer of User Reviews Feedback), a tool able to (i) analyze and classify the information contained in app reviews and (ii) distill actionable change tasks for improving mobile applications. Specifically, SURF performs a systematic summarization of thousands of user reviews through the generation of an interactive, structured and condensed agenda of recommended software changes. An end-to-end evaluation of SURF, involving 2622 reviews related to 12 different mobile applications, demonstrates the high accuracy of SURF in summarizing user reviews content. In evaluating our approach we also involve the original developers of some apps, who confirm the practical usefulness of the software change recommendations made by SURF.
Demo URL: https://youtu.be/Yf-U5ylJXvo
Demo webpage: http://www.ifi.uzh.ch/en/seal/people/panichella/tools/SURFTool.html

Abstract

Continuous Delivery (CD) enables mobile developers to release small, high quality chunks of working software in a rapid manner. However, faster delivery and a higher software quality do neither guarantee user satisfaction nor positive business outcomes. Previous work demonstrates that app reviews may contain crucial information that can guide developer’s software maintenance efforts to obtain higher customer satisfaction. However, previous work also proves the difficulties encountered by developers in manually analyzing this rich source of data, namely (i) the huge amount of reviews an app may receive on a daily basis and (ii) the unstructured nature of their content. In this paper, we propose SURF (Summarizer of User Reviews Feedback), a tool able to (i) analyze and classify the information contained in app reviews and (ii) distill actionable change tasks for improving mobile applications. Specifically, SURF performs a systematic summarization of thousands of user reviews through the generation of an interactive, structured and condensed agenda of recommended software changes. An end-to-end evaluation of SURF, involving 2622 reviews related to 12 different mobile applications, demonstrates the high accuracy of SURF in summarizing user reviews content. In evaluating our approach we also involve the original developers of some apps, who confirm the practical usefulness of the software change recommendations made by SURF.
Demo URL: https://youtu.be/Yf-U5ylJXvo
Demo webpage: http://www.ifi.uzh.ch/en/seal/people/panichella/tools/SURFTool.html

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Software
Physical Sciences > Safety, Risk, Reliability and Quality
Language:English
Event End Date:28 May 2017
Deposited On:15 Feb 2017 13:13
Last Modified:30 Jan 2022 06:59
Publisher:Institute of Electrical and Electronics Engineers
Series Name:Proceedings of the International Conference on Software Engineering Companion
Number:39
ISBN:978-1-5386-1589-8
Additional Information:© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/ICSE-C.2017.5
Related URLs:http://icse2017.gatech.edu/ (Organisation)
Other Identification Number:merlin-id:14547