相关论文: PolyDroid: Learning-Driven Specialization of Mobil…

In my dissertation, I will analyze how the product market position of a mobile app affects its pricing strategies, which in turn impacts an app's monetization process. Using natural language processing and k-mean clustering on apps' text…

Android apps are built on APIs that abstract core Android system functionalities. These APIs are officially documented in multiple files distributed with the Android source code or SDK, which we collectively refer to as Android API Lists…

Software engineers make use of design patterns for reasons that range from performance to code comprehensibility. Several design patterns capturing the body of knowledge of best practices have been proposed in the past, namely creational,…

Before developing a new mobile app, the development team usually endeavors painstaking efforts to review many existing apps with similar purposes. The review process is crucial in the sense that it reduces market risks and provides…

[Background] Research on requirements engineering (RE) for mobile apps employs datasets formed by app users, developers or vendors. However, little is known about the sources of these datasets in terms of platforms and the RE activities…

Recent industrial and academic research has focused on data-driven analytics with smartphones by collecting user interaction, context, and device systems data through Application Programming interfaces (APIs) and sensors. The Android OS…

Recommender systems have become ubiquitous in our digital lives, from recommending products on e-commerce websites to suggesting movies and music on streaming platforms. Existing recommendation datasets, such as Amazon Product Reviews and…

This paper considers the task of learning users' preferences on a combinatorial set of alternatives, as generally used by online configurators, for example. In many settings, only a set of selected alternatives during past interactions is…

The state space of Android apps is huge and its thorough exploration during testing remains a major challenge. In fact, the best exploration strategy is highly dependent on the features of the app under test. Reinforcement Learning (RL) is…

We have carefully instrumented a large portion of the population living in a university graduate dormitory by giving participants Android smart phones running our sensing software. In this paper, we propose the novel problem of predicting…

As the operations of autonomous systems generally affect simultaneously several users, it is crucial that their designs account for fairness considerations. In contrast to standard (deep) reinforcement learning (RL), we investigate the…

Software testing is an important phase in the software development life-cycle because it helps in identifying bugs in a software system before it is shipped into the hand of its end users. There are numerous studies on how developers test…

Android is among the most targeted platform by attackers. While attackers are improving their techniques, traditional solutions based on static and dynamic analysis have been also evolving. In addition to the application code, Android…

Managing the limited energy on mobile platforms executing long-running, resource intensive streaming applications requires adapting an application's operators in response to their power consumption. For example, the frame refresh rate may…

In this paper, we report our recent practice at Tencent for user modeling based on mobile app usage. User behaviors on mobile app usage, including retention, installation, and uninstallation, can be a good indicator for both long-term and…

Crowdsourcing models applied to work on mobile devices continuously reach new ways of solving sophisticated problems, now with a use of portable advanced devices, where users are not limited to a stationary use. There exists an open problem…

Large software organizations such as Facebook or Netflix, who otherwise make daily or even hourly releases of their web applications using continuous delivery, have had to invest heavily into a customized release strategy for their mobile…

Widely-used Android static program analysis tools, e.g., Amandroid and FlowDroid, perform the whole-app inter-procedural analysis that is comprehensive but fundamentally difficult to handle modern (large) apps. The average app size has…

Several recent studies have demonstrated that people show large behavioural uniqueness. This has serious privacy implications as most individuals become increasingly re-identifiable in large datasets or can be tracked while they are…

We study the problem of eliciting the preferences of a decision-maker through a moderate number of pairwise comparison queries to make them a high quality recommendation for a specific problem. We are motivated by applications in high…