A framework to assess Android mobile applications energy consumption and privacy policies.

为什么我的手机电量已经很低了？我每月的话费几乎都用完了，这是怎么回事？为什么这个新应用会跟踪我的位置？这些都是不明显的问题。选择应用程序需要努力、耐心地检查相关信息和技术知识。事实上，最佳的应用组合取决于用户偏好、使用不同功能的频率、单个功能的性能、用户对隐私的关注以及应用（隐藏）成本。如果我们考虑Android生态系统，对于任何给定的应用类别（例如，电子邮件客户端，天气预报，商业，通信，工具，游戏），用户都有很多不同的应用选择（通常实现相同或非常相似的功能）。然而，通常情况下，虽然应用类别列出了许多应用，但提供的信息仅限于特定应用的广告、Android市场元数据和应用排名。在设置Android手机环境时，用户需要尝试不同的应用程序，验证实现的功能，评估广告的侵入性，考虑不同应用程序的利弊，希望在此过程中不会泄露个人或机密信息。

Why is my cell phone battery already low? How did it happen that almost all the data of my monthly phone plan is already used up? Why is the new app tracking my location? These are non-obvious questions. Choosing apps requires effort, patience to examine pertinent information, and technical knowledge. In fact, the best app combination depends on user preference, frequency of use of different features, single feature performance, user privacy concerns, and app (hidden) costs. If we consider the Android ecosystem, for any given app category (e.g., e-mail clients, weather forecast, business, communication, tools, games), the user has plenty of choices for different apps (often implementing the same, or very similar, features). However, quite often, while an app category lists dozens of apps, the information supplied is limited to the advertisement for a specific app, the Android market meta-data, and the app ranking. When setting up an Android phone environment, the user has to try different apps, verify implemented features, evaluate intrusiveness of advertisements, ponder pros and cons of different apps, hoping that, in doing so, no personal or confidential information is leaked. This research program is directed to the development of a framework that will support users and developers. We aim at supporting users in selecting the best set of apps, given the user needs, and supporting developers in designing and implementing efficient and energy aware apps. Specifically, we will support the analysis, assessment and verification of mobile apps’ 1) energy consumption per specified scenario; 2) app implemented features (and feature specific energy consumption); and 3) app privacy implemented policies. In the short term, we will make available a WEB portal to users and selected developers. Users will be able to select some app categories, set their energy, network, and confidentiality concerns (high, medium, low or don’t care), specify the list of grants they are willing to give to apps, and, automatically, obtain a list of optimal, or close to optimal, apps to be installed in their phones. We will generalize this with a scenario definition language. Also, we will offer selected developers the possibility to upload an app, select a scenario (define an app specific scenario if needed), and produce an app energy consumption profile. In the long term, we aim at extending the tool chain supporting 1) mixed language apps (native C and Java or pure C/C++ apps); 2) app and app execution scenarios co-evolution; and 3) different hardware and Android versions. These are all non-trivial and challenging goals. Different hardware implies different screen geometry, device drivers and Android API. App and Android evolution may substantially modify the way in which the user and the app interact: scenarios, privacy policies, and setup to gather information leading to the need of app and scenarios co-evolution.