Abstract: A device may receive, from an augmented reality device, speech data identifying augmented reality interactions with an augmented reality robot. The device may receive, from a camera, video data identifying movements of a real robot based on the augmented reality interactions with the augmented reality robot. The device may process the speech data to obtain first action data identifying first actions that the real robot is to perform. The device may process the video data to obtain second action data identifying second actions that the real robot is to perform. The device may process the first action data and the second action data to generate pseudocode. The device may transform the pseudocode into code. The device may cause the real robot to execute the code, wherein executing the code causes the real robot to perform the first actions and the second actions.

Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for application release and orchestration. In one embodiment, a system is introduced that can communicate with a centralized automation server via an autonomous program. The system centrally test and validate the code and application release using an iterative data deployment process.

Abstract: A system and method for updating patient devices is disclosed. The patient devices (720, 730, 740) may include respiratory therapy devices (4000) that operate in accordance with instruction sets (726), such as software or firmware. A server (710) may maintain a database of configuration data (718) indicating the versions of the software and firmware that is currently installed on the patient devices (720, 730, 740). The server (710) may also transmit updated instructions (716) from over a network (4282), including a wireless network. Particular patient devices (720, 730, 740) may be selected for updating based on the configuration data (718). Upon performing an update a patient device (720, 730, 740) may transmit configuration data (728) to the server (710).

Abstract: Extension patterns are deployed to core deployment patterns stored in a first software repository. An event relating to registration of a component is detected. In response to detecting the event, a tool registry can be queried to identify one or more extension deployment patterns for use with one or more core deployment patterns. Based upon the query, one or more extension deployment components can be retrieved from a second software repository. The one or more extension deployment components can be deployed on top of one or more instances of the one or more core deployment patterns.

Abstract: An information processing apparatus includes a display unit that displays a first list which is a list of available software and a second list which is a list of software installed on a target device; and a receiving unit that receives an instruction operation of installing the software displayed in the first list on the target device and an instruction operation of performing a predetermined process on the installed software displayed in the second list, in which the display unit continues to display the software in the second list, in a case where the software included in the second list is no longer newly provided, and the display unit does not display the software in the first list or displays a fact that it is not allowed to install the software, in a case where the software included in the first list is no longer newly provided.

Abstract: This disclosure describes techniques for testing and publishing of resource handlers in a cloud environment. For example, a code-development interface may be utilized to generate initial code for the building of resource handlers. The initial code may be verified and the resource handlers may be built and deployed to a test platform. One or more execution tests may be run on the resource handlers in the test platform to determine if the resource handlers execute successfully. The resource type associated with the resource handlers may be published to a registry service and the resource type may be made available for provisioning.

Abstract: Systems of the present disclosure provide a versatile, reusable mock server to respond to Application-Programming-Interface (API) requests. The mock server receives an API request and a cookie associated with the API request. The API server identifies response instructions found in the cookie. The response instructions may include a static response value, a name of an API server for the mock server to imitate, or code for the mock server to execute in the process of generating a mock API response. The mock server generates a mock API response based on the response instructions and sends the mock API response in reply to the API request.

Abstract: Methods and apparatus are provided for testing computing devices. A host computing device is provided for testing devices under test (DUTs) using a test suite that includes first and second tests. The DUTs can include a first group of DUTs with a first DUT and a second group of DUTs with a second DUT. The first and second groups of DUTs can share a common design. The host computing device can determine that the DUTs execute the first test before the second test. The host computing device can receive failing first test results for the first DUT. The host computing device can determine, based on the first test results and that the first and second DUT groups share a common design, to execute the second test before the first test and can subsequently instruct the second DUT to execute the second test before the first test.

Abstract: Systems and methods for distributed ledger-based software supply chain management are disclosed. According to one embodiment, in an information processing apparatus comprising at least one computer processor, a method for distributed ledger-based software supply chain management may include: (1) receiving, from a software tool, a metadata artifact for a software development lifecycle event; (2) writing the metadata artifact to a metadata store; and (3) updating a present state database with values for metadata keys referencing the metadata artifact in the metadata store.

Abstract: A programming language and a compiler are disclosed that optimize the use of look-up tables (LUTs) on a synchronous digital circuit (SDC) such as a field programmable gate array (FPGA) that has been programmed. LUTs are optimized by merging multiple computational operations into the same LUT. A compiler parses source code into an intermediate representation (IR). Each node of the IR that represents an operator (e.g. ‘&’, ‘+’) is mapped to a LUT that implements that operator. The compiler iteratively traverses the IR, merging adjacent LUTs into a LUT that performs both operations and performing input removal optimizations. Additional operators may be merged into a merged LUT until all the LUT's inputs are assigned. Pipeline stages are then generated based on merged LUTs, and an SDC is programmed based on the pipeline and the merged LUT.

Abstract: A method, computer program product, and a system to replace monolithic applications with microservices includes a processor(s) obtaining a requirement for the monolithic application. The processor(s) automatically identifies, based on a sentence comprising the requirement, a given component of the monolithic application, based on analyzing the requirement. The processor(s) determines, based on syntax of the sentence, an initial class and a responsibility for the given component. The processor(s) generates a bounded context for the given component, based on analyzing one or more additional sentences comprising the requirement, to identify additional classes beyond the initial class associated with the responsibility in the requirement. The processor(s) identifies, in a microservices architecture executing in a shared computing environment, one or more microservices within the bounded context.

Abstract: An approach is provided for configuring a service management (SM) tool. During an application deployment, a service registry receives a query from a tier of the application for a list of SM tools that provide a SM function. The service registry sends the list of SM tools to the application. Using an application programming interface (API) in an integration layer, (i) a user-selected SM tool included in the list of SM tools, (ii) a business criticality of the tier of the application, and (iii) parameters specifying the SM function are received. Using the API and based on the business criticality of the tier of the application, the selected SM tool is configured with the parameters specifying the SM function.

Abstract: A method for detecting and localizing a fault in a system under test (SUT) includes generating an initial set of test cases using combinatorics test design. The method further includes determining, based at least in part on a first set of execution results, a set of failing test cases. The method further includes determining, based on a machine learning model, a subset of false positives from the failing test cases. The method further includes generating a set of new test cases from a selected failing test case that is not in the subset of false positives. The method further includes executing the set of new test cases to obtain a second set of execution results, and localizing the fault based at least in part on the second set of execution results.

Abstract: Systems and methods are provided for identifying a safe window for creating a firmware update package. In some embodiments, an Information Handling System (IHS), may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: generate tokens based upon a log of historical firmware update package creation events; identify a plurality of workflows based upon the tokens; predict, based upon the plurality of workflows, a future workload of a firmware update package creation service; and indicate, based upon the future workload, a time window for creating a firmware update package using the firmware update package creation service that increases a probability of successful creation.

Abstract: Systems and methods that augment an entity's building and deployment of multiple applications using a metadata library component and a metadata orchestrator that controls details of the configurations of data stores, metadata which may include linkage rules of the metadata structures and that leverages the metadata across individual application development and completed application silos are discussed.

Abstract: Example apparatus, systems and methods receive a new firmware image at a memory device and place the new firmware image into second nonvolatile storage locations of the memory device such that the second nonvolatile storage locations do not overlap with first nonvolatile storage locations of the memory device that store a current firmware image. Embodiments place a logical address to physical address mapping for the new firmware image into a remap data structure stored in memory circuits of the memory device. The remap data structure also includes a logical address to physical address mapping for the current firmware image. Embodiments provide a first status value to indicate that the logical address to physical address mapping for the new firmware image is a valid firmware image and a second status value to indicate that the logical address to physical address mapping for the current firmware image is an invalid firmware image.

Abstract: Manufacturing processes can be optimized using machine learning models. For example, a system can execute an optimization model to identify a recommended set of values for configurable settings of a manufacturing process associated with an object. The optimization model can determine the recommended set of values by implementing an iterative process using an objective function. Each iteration of the iterative process can include selecting a current set of candidate values for the configurable settings from within a current region of a search space defined by the optimization model; providing the current set of candidate values as input to a trained machine learning model that can predict a value for a target characteristic of the object or the manufacturing process based on the current set of candidate values; and identifying a next region of the search space to use in a next iteration of the iterative process based on the value.

Abstract: Described herein is a computer-implemented method for deploying a software product to an environment. The method comprises defining an environment lock for the environment, the environment lock being configured to selectively prevent deployment of a software product to the environment. The method further comprises receiving a request from a requesting entity to deploy a designated software product to the environment, determining a status of the environment lock, and either permitting or preventing the deployment of the designated software product to the environment by reference to the determined status of the environment lock.

Abstract: A system of printing devices installs an upgrade version of firmware for the devices on a limited number of devices before doing a total installation. The number of the limited devices for analyzing the upgrade firmware is determined based on the failure rate of the devices. A ratio of failure is determined that is scaled by a factor to obtain the number of test devices. An analytical time interval also is determined to test the upgrade firmware on the limited number of devices. The failure rate within the limited number of devices is monitored to determine whether to upgrade all of the applicable devices.

Abstract: Methods and apparatus are described by which artificial intelligence (AI) is used to enable the rapid development of reliable test suites for web and mobile applications. An AI agent guided by reinforcement learning explores an application-under-test (AUT), interacting with the AUT to traverse the flows through the AUT by seeking novel application states. A subset of these flows is then identified as being representative of the functionality of the AUT. The interactions between the AI agent and the AUT that define these identified flows form the basis for the test suite.