Honeysuckle

Abstract

In-app privacy notices can help smartphone users make informed privacy decisions. However, they are rarely used in real-world apps, since developers often lack the knowledge, time, and resources to design and implement them well. We present Honeysuckle, a programming tool that helps Android developers build in-app privacy notices using an annotation-based code generation approach facilitated by an IDE plugin, a build system plugin, and a library. We conducted a within-subjects study with 12 Android developers to evaluate Honeysuckle. Each participant was asked to implement privacy notices for two popular open-source apps using the Honeysuckle library as a baseline as well as the annotation-based approach. Our results show that the annotation-based approach helps developers accomplish the task faster with significantly lower cognitive load. Developers preferred the annotation-based approach over the library approach because it was much easier to learn and use and allowed developers to achieve various types of privacy notices using a unified code format, which can enhance code readability and benefit team collaboration.

Document Details

Document Type
Pub Defense Publication
Publication Date
Sep 09, 2021
Source ID
10.1145/3478097

Entities

People

  • Elijah B. Neundorfer
  • Jason I. Hong
  • Tianshi Li
  • Yuvraj Agarwal

Organizations

  • Air Force Research Laboratory
  • Carnegie Mellon University
  • Columbus State University
  • National Science Foundation

Tags

Fields of Study

  • Computer science
  • Engineering

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Government and Public Administration Law.
  • Software Engineering.