An app migration system including at least one processor which places an app in one of an inside and an outside of a space joined by at least one user in a user group in which information is shareable; sets, for the app, a permission corresponding to a placement location of the app; migrates the app in one of a route between a public space and a private space and a route between the inside and the outside of the space; and sets, for the migrated app, a permission corresponding to a migration destination of the app.

Techniques are disclosed that enable automating user interface input by generating a sequence of actions to perform a task utilizing a multi-agent reinforcement learning framework. Various implementations process an intent associated with received user interface input using a holistic reinforcement policy network to select a software reinforcement learning policy network. The sequence of actions can be generated by processing the intent, as well as a sequence of software client state data, using the selected software reinforcement learning policy network. The sequence of actions are utilized to control the software client corresponding to the selected software reinforcement learning policy network.

Techniques described herein relate to a method for managing migrations of applications. The method may include identifying, by a verification manager associated with an execution environment, an application potential migration event associated with an application; in response to identifying the application potential migration event: obtaining application configuration information associated with the application; making a determination that the application configuration information indicates the execution environment is capable of hosting the application; generating potential migration information associated with the execution environment and the application; and sending an affirmation and the potential migration information to the application.

Managing application migration is provided. An API server on a controller node is invoked to update a configuration map of a reverse proxy on a worker node for the reverse proxy to route user service requests corresponding to unmigrated applications of a set of applications from a first computing platform to a second computing platform to maintain liveness of the unmigrated applications during migration. The API server is invoked to build an image for an application of the set of applications based on source code of the application obtained from the second computing platform. The API server is invoked to generate a pod on the worker node to perform a workload of the application using the image. The API server is invoked to update a service on the worker node to select the pod on the worker node performing the workload of the application.

A computer-implemented method comprising: receiving, by a computing device, user input defining a workflow; receiving, by the computing device, information defining schemas at convergence points in the workflow; determining, by the computing device, a set of mapping parameters at outputs of nodes of the workflow based on the schemas; receiving, by the computing device, input values to the mapping parameters; storing, by the computing device, the input values to the mapping parameters in a structure corresponding to the schemas; and executing, by the computing device, the workflow based on the input values to the mapping parameters, wherein the executing includes invoking one or more applications residing on one or more application servers through application programming interface (API) calls.

A method for enabling a task management interface includes receiving an instruction for enabling the task management interface, displaying the task management interface in response to the instruction for enabling the task management interface, where the task management interface includes a preview interface of at least one application program and an icon corresponding to at least one function of the application program, receiving an operation instruction for the icon, and switching the application program corresponding to the icon to a foreground and executing the function in response to the operation instruction.

This application provides a method for managing a resource in a computer system and a terminal device. The method includes: obtaining data, where the data includes application sequence feature data related to a current foreground application, and the data further includes at least one of the following real-time data: a system time of the computer system, current status data of the computer system, and current location data of the computer system; selecting, from a plurality of machine learning models based on at least one of the real-time data, a target machine learning model that matches the real-time data; inputting the obtained data into the target machine learning model to rank importance of a plurality of applications installed in the computer system; and performing resource management based on a result of the importance ranking.

A computing device can intercept a request to launch a requested application. The request can be intercepted by a calling process executed by the computing device. The request can include information identifying the requested application. The computing device can determine that a user interaction is required before launching the requested application by consulting a set of application policies based on the information identifying the requested application. The computing device can establish that the calling process is associated with a controlling terminal provided by an operating system in response to determining that the user interaction is required. A process session group containing processes launched within a user session can be selectively associated with the controlling terminal by the operating system. The computing device can perform the user interaction using the controlling terminal in response to establishing that the calling process is associated with the controlling terminal.

A method and an apparatus for determining a usage level of a memory device to notify a running application to perform memory reduction operations selected based on the memory usage level are described. An application calls APIs (Application Programming Interface) integrated with the application codes in the system to perform memory reduction operations. A memory usage level is determined according to a memory usage status received from the kernel of a system. A running application is associated with application priorities ranking multiple running applications statically or dynamically. Selecting memory reduction operations and notifying a running application are based on application priorities. Alternatively, a running application may determine a mode of operation to directly reduce memory usage in response to a notification for reducing memory usage without using API calls to other software.

Disclosed are various approaches for workflow service application networking. In some aspects, a workflow creation user interface is provided to create a networking workflow with at least one networking action. A networking action is specified for a first application to utilize application content from a second application. The networking action is verified based on a response to a test action request transmitted to the workflow service. The networking action is transmitted from the workflow application to a workflow service to cause the first application to utilize the application content from the second application according to the networking action.