Abstract: The disclosed computer-implemented method may include predicting, by a machine learning model, a user action and a timing of the user action for an application on a computing device. The method may also include determining that an expected lag in executing the user action is greater than a predetermined threshold based on one or more resource constraints of the computing device and initializing a setup of the application to reduce the expected lag in executing the user action based on the predicted timing. Furthermore, the method may include prefetching one or more application components in response to initializing the setup of the application and preprocessing at least a portion of a function of the application used to execute the user action. Finally, the method may include executing the user action for the application in response to a user request. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include identifying an application, on an electronic device, with a minimum requirement for a resource of the electronic device. The method may also include determining that an available amount of the resource of the electronic device does not meet the minimum requirement of the application. Additionally, the method may include selecting, based on the determination, an alternative user-interface mode of the application with a lower minimum requirement for the resource. Furthermore, the method may include instantiating the alternative user-interface mode of the application. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A customization technique that provides a customized user interface in software to a user based on user behaviors while using the user interface during one or more sessions is described. In this customization technique, a usage pattern of the user is determined from the user behaviors, and a user-specific customization of the user interface is generated based on the determined usage pattern. Note that determining the usage pattern may involve generating a directed graph in which vertices correspond to visual components in the user interface and edges between vertices correspond to user behaviors. Then, the user interface in a current release of the software is customized based on the user-specific customization. For example, the customized user interface may include: only a subset of the visual components; a different order of the visual components; and/or a visual component associated with a set of operations.