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Tue 11 Oct 2022 14:40 - 15:00 at Gold A - Technical Session 8 - Mobile Apps II Chair(s): Wei Yang

The proliferation of mobile applications (app) over the past decade has imposed unprecedented challenges on end-users privacy. Apps constantly demand access to sensitive user information in exchange for more personalized services. These -mostly unjustified- data collection tactics have raised major concerns among mobile app users. These concerns are commonly expressed in mobile app reviews. However, privacy concerns are typically overshadowed by more generic categories of user feedback, often related to app reliability and usability. This makes extracting these concerns manually, or even using automated methods, a challenging task. To address these challenges, in this paper, we propose an effective unsupervised approach for summarizing privacy concerns in mobile app reviews. Our analysis is conducted using a dataset of 2.6 million app reviews sampled from three different application domains. The results show that users in different application domains express their privacy concerns using different vocabulary. This domain knowledge can be leveraged to help unsupervised automated text summarization algorithms to effectively generate concise summaries of privacy concerns in review collections. Our analysis in this paper is intended to help app developers to quickly and accurately identify the most critical privacy concerns in their domain of operation.

Tue 11 Oct

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14:00 - 15:30
Technical Session 8 - Mobile Apps IIResearch Papers / Tool Demonstrations at Gold A
Chair(s): Wei Yang University of Texas at Dallas
14:00
20m
Research paper
Too Much Accessibility is Harmful! Automated Detection and Analysis of Overly Accessible Elements in Mobile Apps
Research Papers
Forough Mehralian University of California at Irvine, Navid Salehnamadi University of California at Irvine, Syed Fatiul Huq University of California, Irvine, Sam Malek University of California at Irvine, USA
14:20
20m
Research paper
Groundhog: An Automated Accessibility Crawler for Mobile Apps
Research Papers
Navid Salehnamadi University of California at Irvine, Forough Mehralian University of California at Irvine, Sam Malek University of California at Irvine, USA
14:40
20m
Research paper
Unsupervised Summarization of Privacy Concerns in Mobile Application Reviews
Research Papers
Fahimeh Ebrahimi Louisiana State University, Anas "Nash" Mahmoud Louisiana State University
15:00
10m
Demonstration
ecoCode: a SonarQube Plugin to Remove Energy Smells from Android Projects
Tool Demonstrations
Olivier Le Goaër LIUPPA, Université de Pau et des Pays de l'Adour, Julien Hertout Snapp'
DOI File Attached
15:10
20m
Research paper
The Metamorphosis: Automatic Detection of Scaling Issues for Mobile AppsVirtual
Research Papers
Yuhui Su Institute of Software, Chinese Academy of Sciences, Chunyang Chen Monash University, Junjie Wang Institute of Software at Chinese Academy of Sciences, Zhe Liu Institute of Software, Chinese Academy of Sciences, Dandan Wang Institute of Software, Chinese Academy of Sciences, Shoubin Li ISCAS, Qing Wang Institute of Software at Chinese Academy of Sciences