Abstract: The technology relates to executing a multi-portion web application. A web browser executing on one or more computing devices may load a main portion of a web application into a main window. The web browser may load into a sandboxed environment a feature application. The feature application may include a portion of the web application. A release isolation framework (RIF) executing on the one or more computing devices, may apply one or more patches to the sandboxed environment. The one or more patches may be configured to redirect elements from a window of the sandboxed environment to the main window.

Abstract: Provided is a method of a host device managing at least one external device connected to the host device through a management server. The method includes: obtaining measurement information measured by the at least one external device; requesting authorization by the management server; transmitting the obtained measurement information to the management server when the authentication succeeds; receiving management information for managing the at least one external device, where the management information is generated based on the measurement information by the management server; and managing the at least one external device based on the received management information.

Abstract: Herein is a machine learning (ML) explainability (MLX) approach in which a natural language explanation is generated based on analysis of a parse tree such as for a suspicious database query or web browser JavaScript. In an embodiment, a computer selects, based on a respective relevance score for each non-leaf node in a parse tree of a statement, a relevant subset of non-leaf nodes. The non-leaf nodes are grouped in the parse tree into groups that represent respective portions of the statement. Based on a relevant subset of the groups that contain at least one non-leaf node in the relevant subset of non-leaf nodes, a natural language explanation of why the statement is anomalous is generated.

Abstract: An example system can include: at least one processor; and non-transitory computer-readable storage storing instructions that, when executed by the at least one processor, cause the system to: generate a configuration manager programmed to configure a workstream including a plurality of models, wherein the workstream defines metadata associated with execution of each of the plurality of models; generate an execution manager programmed to execute each of the plurality of models in the workstream according to the metadata; and generate a results manager programmed to access results of the execution of the workstream.

Abstract: Provided is an application optimization method and an electronic device supporting the same. According to an example embodiment, the application optimization method may include: determining whether a condition set with respect to a duration of an idle state of the electronic device is satisfied, selecting an application for which application optimization is to be performed based on an application usage record of a user of the electronic device in response to the set condition being satisfied, and generating an optimized application by performing the application optimization in the background for the selected application.

Abstract: Various methods, apparatuses/systems, and media for automatically upgrading an application are disclosed. A processor creates a dynamic machine learning (ML) model; trains the dynamic ML model and scans for SDK upgrade for the application against the dynamic ML model by implementing ML algorithm for predictions. The processor executes the SDK upgrade in response to detecting that the training of the dynamic ML model is completed to trigger the processor to perform the following automated processes: implement the ML algorithm against the trained dynamic ML model to generate predictive results data for deprecated reference corresponding to the application; evaluate the predictive results data to determine whether there is a match for the deprecated reference; and when it is determined that there is a match for the deprecated reference, automatically replace code and upgrade the application to newer version of the programming language specification.

Abstract: A method of generating metrics data associated with a microservices-based application comprises ingesting a plurality of spans and mapping an ingested span of the plurality of spans to a span identity, wherein the span identity comprises a tuple of information identifying a type of span associated with the span identity, wherein the tuple of information comprises user-configured dimensions. The method further comprises grouping the ingested span by the span identity, wherein the ingested span is grouped with other spans from the plurality of spans comprising a same span identity. The method also comprises computing metrics associated with the span identity and using the metrics to generate a stream of metric data associated with the span identity.

Abstract: An industrial integrated development environment (IDE) is extended to support creation of device profiles using an intuitive graphical development environment. The environment comprises a device profile development interface that allows a user to select device profile views to be included in a device profile for an industrial device, and to submit edits to the underlying code for the selected device profile views. The system can then generate a new device profile from the modified device profile code. The device profile can be registered with the industrial IDE and used to view and edit device parameters of a corresponding industrial device. The device profile development environment also supports dynamic validation of profile view edits, rendering of graphical previews of the modified device profile view, and submission of both code-based and graphical profile view edits.

Abstract: A system can determine complexity data representative of a complexity of changes to computer code that is executable to operate at least one microservice that is part of a group of microservices, wherein a portion of the changes corresponds to a library on which the computer code depends. The system can generate a progressive deployment plan for the at least one microservice based on the complexity of changes. The system can progressively direct traffic to the at least one microservice based on the progressive deployment plan.

Abstract: An application server may identify a set of functions for the source code associated with an uninterruptable software service. In some examples, the subset of the set of functions may include one or more functions having a computational expense greater than a threshold. The application server may create a compilation template to compile a subset of the set of functions to a shared library, and may perform an instrumentation to identify the subset of the set of functions based on the shared library. The application server may create an optimized version of the shared library based on performing the instrumentation. The application server may then change one or more portions of the source code to repoint to the optimized version of the shared library based on creating the optimized version of the shared library.

Abstract: An information processing apparatus comprises a volatile memory and a non-volatile storage capable of storing a main firmware for causing the information processing apparatus to realize the predetermined function and a communication firmware for booting. The information processing apparatus accesses a predetermined server using the communication firmware, obtains recovery firmware, and loads the recovery firmware into a volatile memory. Further, the information processing apparatus obtains an updated main firmware from the predetermined server using the loaded recovery firmware, and updates the main firmware stored in the non-volatile storage.

Abstract: The invention relates to a computer-implemented method for data processing control.

Abstract: An embodiment of the present disclosure relate to a method for creating an application. The method for generating an application may comprise: identifying a component library including information on a plurality of visual logics, generating a first application based on information on a first visual logic corresponding to a first design and information on a business logic generated based on attributes of the application, identifying information on a second visual logic corresponding to a second design different from the first design, and generating a second application based on information on the second visual logic and information on the business logic. The information on the first visual logic and the information on the second visual logic may be included in the information on the plurality of visual logics.

Abstract: A fault-tolerant quantum computer using topological codes such as surface codes can have an architecture that reduces the amount of idle volume generated. The architecture can include qubit modules that generate surface code patches for different qubits and a network of interconnections between different qubit modules. The interconnections can include “port” connections that selectably enable coupling of boundaries of surface code patches generated in different qubit modules and/or “quickswap” connections that selectably enable transferring the state of a surface code patch from one qubit module to another. Port and/or quickswap connections can be made between a subset of qubit modules. For instance port connections can connect a given qubit module to other qubit modules within a fixed range. Quickswap connections can provide a log-tree network of direct connections between qubit modules.

Abstract: An apparatus for modification of operating environments, includes at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to generate update data for one or more operating environments, append a digital signature associated with an update data source to the update data, identify at least one operating environment for receipt of the update data, wherein identification includes determining a compliance of one or more operating environments and identifying the at least one operating environment as a function of the compliance, authenticate the at least one operating environment, wherein authentication includes receiving an update log associated with the at least one operating environment and comparing the update log to a central log and transmit the update data to the at least one operating environment as a function of the authentication to modify the at least one operating environment.

Abstract: In a vehicle program rewrite system, a vehicle master device includes a first progress determination unit that is configured to determine a first progress related to a program rewrite, a first progress transmission unit that is configured to transmit the first progress determined by the first progress determination unit to the center device, a second progress acquisition unit that is configured to acquire a second progress related to the program rewrite from the center device, and a first display instruction unit that is configured to instruct to create a content that is displayable on a display terminal mounted in a vehicle based on the first progress determined by the first progress determination unit and the second progress acquired by the second progress acquisition unit.

Abstract: A computing device can receive, from a version control system, a first set of pre-computed checksums for source files for a software program. The computing device can receive, from the version control system, a second set of pre-computed checksums for a second set of source files for the software program. The computing device can determine a first total checksum by combining the first set of pre-computed checksums. The computing device can also determine a second total checksum by combining the first set of pre-computed checksums. The computing device can determine, by comparing the first total checksum to the second total checksum, that the first set of source files was previously built by the build engine. The computing device can then prevent the build engine from re-building the first set of source files.

Abstract: Systems, computer program products, and methods are described herein for evaluating, validating, and implementing software release change requests to a system environment based on artificial intelligence input. The present invention may be configured to receive a software release change request including a change to be made to a configuration item of a system environment, determine, based on a change inference database, potential failure points associated with deploying the software release change request in the system environment, and determine, based on the potential failure points, a confidence score for the change using a cognitive release evaluation system module comprising an artificial intelligent or machine learning engine.

Abstract: Techniques are provided for performing server device updates using update baselines that are tagged across multiple management consoles. One method comprises obtaining, by a first management console of multiple management consoles associated with a server device, a first update baseline comprising a first tag identifier, of multiple tag identifiers, that identifies a first update of a component of the server device across the multiple management consoles; and applying the first update baseline to the server device in a maintenance mode to update the component of the server device, wherein the server device is maintained in the maintenance mode when two or more of the tag identifiers are active in the server device following the application of the first update baseline. The server device can be restored from the maintenance mode when only one tag identifier is active in the server device following the application of the first update baseline.

Abstract: Embodiments of the present disclosure relate to applications and platforms for configuring machine learning models for training and deployment using graphical components in a development environment. For example, systems and methods are disclosed that relate to determining one or more machine learning models and one or more processing operations corresponding to the one or more machine learning models. Further, a model component may be generated using the one or more machine learning models, the one or more processing operations, and one or more extension libraries in which the one or more extension libraries indicate one or more deployment parameters related to the one or more machine learning models. The model component may accordingly provide data that may be used to be able to use and deploy the one or more machine learning models.