On the Violation of Honesty in Mobile Apps: Automated Detection and CategoriesDistinguished Paper Award
Human values such as integrity, privacy, curiosity, security, and honesty are guiding principles for what people consider important in life. Such human values may be violated by mobile software applications (apps), and the negative effects of such human value violations can be seen in various ways in society. In this work, we focus on the human value of honesty. We present a model to support the automatic identification of violations of the value of honesty from app reviews from an end-user perspective. Beyond the automatic detection of honesty violations by apps, we also aim to better understand different categories of honesty violations expressed by users in their app reviews. The result of our manual analysis of our honesty violations dataset shows that honesty violations can be characterised into ten categories: unfair cancellation and refund policies; false advertisements; delusive subscriptions; cheating systems; inaccurate information; unfair fees; no service; deletion of reviews; impersonation; and fraudulent-looking apps. Based on these results, we argue for a conscious effort in developing more honest software artefacts including mobile apps, and the promotion of honesty as a key value in software development practices. Furthermore, we discuss the role of app distribution platforms as enforcers of ethical systems supporting human values, and highlight some proposed next steps for human values in software engineering (SE) research.
Wed 18 MayDisplayed time zone: Eastern Time (US & Canada) change
21:00 - 21:50 | Session 7: Developer Wellbeing & Project CommunicationTechnical Papers / Data and Tool Showcase Track / Industry Track at MSR Main room - odd hours Chair(s): Bram Adams Queen's University, Kingston, Ontario | ||
21:00 7mTalk | On the Violation of Honesty in Mobile Apps: Automated Detection and CategoriesDistinguished Paper Award Technical Papers Humphrey Obie Monash University, Idowu Oselumhe Ilekura Data Science Nigeria, Hung Du Applied Artificial Intelligence Institute, Deakin University, Mojtaba Shahin RMIT University, Australia, John Grundy Monash University, Li Li Monash University, Jon Whittle CSIRO's Data61 and Monash University, Burak Turhan University of Oulu Pre-print | ||
21:07 7mTalk | How heated is it? Understanding GitHub locked issues Technical Papers Isabella Ferreira Polytechnique Montréal, Bram Adams Queen's University, Kingston, Ontario, Jinghui Cheng Polytechnique Montreal Pre-print Media Attached | ||
21:14 4mTalk | The OCEAN mailing list data set: Network analysis spanning mailing lists and code repositories Data and Tool Showcase Track Melanie Warrick University of Vermont, Samuel F. Rosenblatt University of Vermont, Jean-Gabriel Young University of Vermont, amanda casari Open Source Programs Office, Google, Laurent Hébert-Dufresne University of Vermont, James P. Bagrow University of Vermont DOI Pre-print Media Attached | ||
21:18 4mTalk | The Unexplored Treasure Trove of Phabricator Code Reviews Data and Tool Showcase Track Gunnar Kudrjavets University of Groningen, Nachiappan Nagappan Microsoft Research, Ayushi Rastogi University of Groningen, The Netherlands DOI Pre-print | ||
21:22 4mTalk | The Unsolvable Problem or the Unheard Answer? A Dataset of 24,669 Open-Source Software Conference Talks Data and Tool Showcase Track Kimberly Truong Oregon State University, Courtney Miller Carnegie Mellon University, Bogdan Vasilescu Carnegie Mellon University, USA, Christian Kästner Carnegie Mellon University DOI Pre-print | ||
21:26 4mTalk | Exploring Apache Incubator Project Trajectories with APEX Data and Tool Showcase Track Anirudh Ramchandran University of California, Davis, Likang Yin University of California, Davis, Vladimir Filkov University of California at Davis | ||
21:30 7mTalk | A Culture of Productivity: Maximizing Productivity by Maximizing Wellbeing Industry Track Brian Houck Microsoft Research | ||
21:37 13mLive Q&A | Discussions and Q&A Technical Papers |