Matcha：用于创建准确隐私营养标签的IDE插件
Matcha: An IDE Plugin for Creating Accurate Privacy Nutrition Labels
AI总结：
Matcha是一个IDE插件，通过自动化代码分析帮助开发者创建准确的Google Play数据安全标签，实验表明其提高了标签准确性并获开发者偏好。
摘要：
苹果和谷歌在移动应用商店中推出了各自版本的隐私营养标签，以更好地告知用户应用的数据实践。然而，这些标签由开发者自行报告，并因对标签分类法的误解而被发现存在许多不准确之处。在这项工作中，我们提出了Matcha，一个IDE插件，它利用自动化代码分析帮助开发者创建准确的Google Play数据安全标签。开发者可以受益于Matcha检测用户数据访问和传输的能力，同时通过添加自定义Java注解和修改自动生成的XML规范，保持对生成标签的控制。我们与12名开发者的评估表明，Matcha帮助参与者提高了他们使用谷歌官方工具为其实开发的应用创建的标签的准确性。我们发现参与者更偏好Matcha，因为它具有准确性优势。基于Matcha，我们讨论了用于创建准确标准化隐私通知的开发者工具的一般设计建议。
英文摘要：
Apple and Google introduced their versions of privacy nutrition labels to the mobile app stores to better inform users of the apps' data practices. However, these labels are self-reported by developers and have been found to contain many inaccuracies due to misunderstandings of the label taxonomy. In this work, we present Matcha, an IDE plugin that uses automated code analysis to help developers create accurate Google Play data safety labels. Developers can benefit from Matcha's ability to detect user data accesses and transmissions while staying in control of the generated label by adding custom Java annotations and modifying an auto-generated XML specification. Our evaluation with 12 developers showed that Matcha helped our participants improved the accuracy of a label they created with Google's official tool for a real-world app they developed. We found that participants preferred Matcha for its accuracy benefits. Drawing on Matcha, we discuss general design recommendations for developer tools used to create accurate standardized privacy notices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
