Abstract: A method for updating a domestic appliance includes determining a configuration of the domestic appliance, wherein the configuration relates to a state of at least one component of the domestic appliance. A restriction assigned to predefined update information is determined for domestic appliances, including the domestic appliance. The control information of at least one component of the domestic appliance is updated on a basis of update information if the configuration of the domestic appliance meets the restriction. The configuration includes an attribute of a component of the domestic appliance, and the attribute is determined on the basis of an identification of the domestic appliance and an assignment of the identification to the attribute.

Abstract: Embodiments relate to a system, program product, and method for generating an enhanced feature catalog for a predictive model. The embodiments disclosed herein include capturing predictive model design time information including training data lineage metadata to determine the features of the training data, model design time measurements, and model design time metadata. Once the predictive model is built, the training data lineage metadata is used to capture the features that will be maintained within a feature catalog. The model design time measurements and model design time metadata provide further correlation between the predictive model and the features. Runtime metrics on the predictive model create additional correlations between the captured data and metadata with the features in the feature catalog to expeditiously identify the relevant features of the predictive model.

Abstract: In various embodiments, a method, apparatus, and computer program product are provided involving, at a first device: opening the application on the first device, performing an action utilizing an application, updating a state of the application, for being communicated with the second device; and, at a second device: utilizing the updated state of the application received from the first device, displaying an interface including: a button for opening the application utilizing the second device, and indicia that indicates that the first device has updated at least one aspect of the application, and in response to a detection of the selection of the button, accessing the application utilizing the second device such that the application is accessed so as to reflect the updated state of the application.

Abstract: A software updating system based on differential updating for reducing the size of updating data and a method of controlling the same are provided. The method includes acquiring differential data between an original image and an updating image for each of a plurality of updating target controllers included in a vehicle. Then low-ranking differential data is acquired in at least one stage between differential data for each of the plurality of updating target controllers and a plurality of differential combinations are generated for all of the plurality of updating target controllers. An optimum combination of the plurality of differential combinations is then determined and updating data is generated depending to the optimum combination.

Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.

Abstract: Managing firmware updates of an information handling system (IHS), including performing, at a first time, a calibration and configuration of a firmware update risk model, including: identifying predictor data associated with a plurality of IHS; training, based on the predictor data, the firmware update risk model, including generating a configuration policy including configuration rules, the configuration rules for performing computer-implemented actions responsive to a firmware update; receiving, at a second time, the firmware update at a particular IHS, and in response: identifying particular predictor data of the particular IHS; in response to identifying the particular predicator data of the particular IHS, i) accessing the firmware update risk model including the configuration policy, ii) identifying one or more of the configuration rules based on the identified particular predicator data, and iii) applying the one or more configuration rules to perform computer-implemented actions responsive to receivin

Abstract: An approach to code refactor renaming may be provided. Source code with a naming convention for functions and classes can be presented to a machine learning model. The model may identify the names for functions and classes. The identified names may be tokenized. Docstrings associated with functions and classes may be identified. Code for the identified functions and classes and associated may be input into a feature vector generation mechanism. A model may be trained mapping the generated feature vectors to tokenized identified names, via regression. The model can be utilized to analyze input code with the same naming convention to predict names for functions and classes, allowing for the recommendation of function and class names in accordance with the programming code naming convention.

Abstract: A system is provided for computer program code issue detection and resolution using an automated progressive code quality engine. In particular, the system may automatically detect issues with computer program code automatically resolve the issues detected on any computing system within a network environment. The system may comprise a progressive code quality engine configured to use machine learning algorithms to adaptively detect code quality issues and a rule imposition engine that automatically resolves the issues detected by the code quality engine. The system may further comprise one or more edge device-based quality enablers that may coordinate the resolution of code quality issues with a cloud-based master controller. In this way, the system provides a seamless and dynamic end-to-end solution for addressing code quality issues.

Abstract: Container image building using shared resources is disclosed. A first instruction file that contains a first plurality of instruction keywords is read. Based on the first plurality of instruction keywords, a first plurality of files from a shared location is copied to a first consolidated location. Based on the first plurality of instruction keywords, a first container command file that references at least some of the first plurality of files on the first consolidated location is generated, the first container command file including commands that comply with a container builder syntax.

Abstract: Techniques for performing machine learning-based program analysis using synthetically generated labeled data are described. A method of performing machine learning-based program analysis using synthetically generated labeled data may include receiving a request to perform program analysis on code, determining a first portion of the code associated with a first error type, sending the first portion of the code to an endpoint of a machine learning service associated with an error detection model to detect the first error type, the error detection model trained using synthetically generated labeled data, and receiving inference results from the error detection model identifying one or more errors of the first error type in the first portion of the code.

Abstract: A system includes a server comprising a memory and a processor, where the processor is in communication with the memory. The processor is configured to download, by the updating agent, a second version of source files associated with a second version of the updating agent, where the second version of source files are stored separately from the first version of the source files, where the second version of the updating agent is operable to update a second set of libraries of the application. Next, the updating agent overwrites the first version of the source files with the second version of the source files. The updating agent then re-starts the updating agent with an update parameter designating a location of the downloaded second version of the source files, wherein the third version of the source files are executed to re-start the updating agent.

Abstract: Computing systems, for example, multi-tenant systems deploy software artifacts in data centers created in a cloud platform using a cloud platform infrastructure language that is cloud platform independent. The system receives pipeline templates including templating expressions that can be substituted with values for generating pipelines. A pipeline can be executed to perform a set of actions associated with continuous delivery of a software artifact. The system stores sets of partially hydrated pipeline templates. The partially hydrated pipeline templates can be compiled into executable pipelines associated with services configured on a datacenter of a cloud platform. The system stores different versions of pipeline templates as deployment packages. The system stores version pointers that identify specific deployment packages that are selected when a software release is deployed. The version pointers allow the deployment package to be updated in case of roll back or for deploying more recent changes.

Abstract: A method of operating a telemetry system includes automatically populating a base field of a schema in an event definition using a logging library of the telemetry system for an event of an instrumented application, and automatically populating a conditional field of the schema in the event definition using the logging library in response to a selected condition for the event.

Abstract: Methods are described herein for creating and installing software updates which may be rolled back, without requiring large processing capabilities and/or large storage capacity at a device. Delta software updates are determined comprising differences, on a bit-level, between a first version of the software and a second, updated, version of the software, and metadata defining how to apply the differences. Methods of performing a rollback-capable update at a device are also described herein.

Abstract: In an approach, a processor, in response to detecting a new customer resource (CR) file: requests, the computing environment to deploy a plurality of function deployment components in the computing environment, where: the CR file indicates information of a plurality of functions of an application; the plurality of function deployment components request the computing environment to deploy a plurality of function components in the computing environment; and the plurality of function components execute the plurality of functions of the application; determines that each of the plurality of function components has been deployed in the computing environment; and in response to determining that each of the plurality of function components has been deployed in the computing environment, requests the computing environment to delete each of the plurality of deployed function deployment components.

Abstract: A system is provided for computer code development environment cloning and authentication using a distributed server network and machine learning. In particular, the system may use a machine learning algorithm configured to automatically identify and analyze changes in computing code between two or more environments and publish a record of said changes to a private distributed register stored on a plurality of distributed server nodes. Based on the analysis, the system may generate one or more recommended changes to the source code. If the changes are confirmed by one or more authorized users, the system may automatically implement the changes and publish a confirmation record of the implemented changes to the distributed register. In this way, the system may provide an efficient way to ensure synchronization of code across multiple computing environments.

Abstract: A system for compiling programs for execution thereof using a hierarchical processing system having two or more levels of memory hierarchy can perform memory-level-specific optimizations, without exceeding a specified maximum compilation time. To this end, the compiler system employs a polyhedral model and limits the dimensions of a polyhedral program representation that is processed by the compiler at each level using a focalization operator that temporarily reduces one or more dimensions of the polyhedral representation. Semantic correctness is provided via a defocalization operator that can restore all polyhedral dimensions that had been temporarily removed.

Abstract: An online data hub/portal that provides for data to be extracted from production environments, sanitized (removal of non-public information NPI) and loaded into non-production environment (e.g., testing and development environment). The online data hub/portal allows users to extract data from a disparate production applications into a first secure staging location that triggers identification of Non-Public Information (NPI), sanitization of the identified NPI and validation of the data (e.g., verifying that NPI has been identified and sanitized and that all relationships between data elements in downstream and upstream applications are kept intact). Once sanitized and validated, the data hub places the data in a second secure staging location that provides for loading the sanitized data into the non-production environment.

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: System to design and/or update programs for the operator interface of machines and/or plants that comprises at least one first calculation device dedicated to the management of a machine and/or plant, which contains at least one application program to manage the human-machine interface (HMI) of the machine and/or plant, and a second calculation device to execute a software, or development environment, to create a project file, wherein on the first calculation device and on the second calculation device respective communication programs are installed, suitable to transfer the project to the first calculation device, where the application program for the management of the HMI interface displays the project by means of a suitable OPC UA standard information model, by means of which it is possible to make modifications to the project dynamically, without interrupting the execution of the human-machine interface program, and so that every modification to the project, and therefore to the human-machine interface pr