Abstract: A computer-implemented method for carrying out an update management for updating application software on data processing units. The method includes: providing an error model, which indicates a number of errors across software versions of the application software; determining an update sequence for data processing units, depending on their particular software version; and updating the application software or providing an update prompt to update the application software in the data processing units according to the update sequence.

Abstract: A computation unit for performing a computation of a neural network layer is disclosed. A number of processing element (PE) units are arranged in an array. First input values are provided in parallel in an input dimension of the array during a first processing period, and a second input values are provided in parallel in the input dimension during a second processing period. Computations are performed by the PE units based on stored weight values. An adder coupled to the first set of PE units generates a first sum of results of the computations by the first set of PE units during the first processing cycle, and generates a second sum of results of the computations during the second processing cycle. A first accumulator coupled to the first adder stores the first sum, and further shifts the first sum to a second accumulator prior to storing the second sum.

Abstract: The present disclosure provides a permission-controlled smart contract upgrade method. The method first deploys a contract upgrade smart contract, and then deploys a smart contract to be upgraded including information of a required minimum number of agreements on passing a proposal related to the contract. Then, any of the blockchain nodes receives a contract upgrade proposal submitted by one of the plurality of user clients. After the contract upgrade smart contract determines to pass the proposal, a proposing event is generated and then is forwarded to each user client participating in the contract. After the user client receives the proposing event, the user client receives user's vote and feeds it back to the contract upgrade smart contract. If the number of agreements exceeds the required minimum number of agreements, the proposal is passed and employed, and a binary replacement is performed to complete upgrade of the smart contract.

Abstract: In a vehicle master device, a first device includes an update data acquisition unit that is configured to acquire update data, an update data distribution unit that is configured to distribute the update data acquired by the update data acquisition unit to a rewrite target ECU, a process execution request unit that is configured to request the second device to execute at least a part of a process related to verification of the update data before the update data distribution unit distributes the update data, a processing result acquisition unit that is configured to acquire a processing result from the second device, and a verification unit that is configured to verify the update data using the processing result acquired by the processing result acquisition unit.

Abstract: The present disclosure relates generally to a system that includes a storage component that stores data and a processor. The processor may install an application using a portion of the storage component, partition the portion of the storage component from a remaining portion of the storage component, and execute the application via the portion of the storage component.

Abstract: A data structure called a product version map is introduced. The product version map contains a catalog of available application versions to be used by the application orchestration services. It can describe the available versions. For each version, there is an image, such as a Docker® container image, that can be used to instantiate the application instance. Furthermore, in some example embodiments, an expiration date can be given, which could be used to enforce upgrades of application instances when their used version expires.

Abstract: Methods for supporting a development of application source code using input from a first smart glasses of a first user and a second smart glasses of a second user is provided. Methods may include retrieving the application source code from an internal development platform and displaying the application source code on an augmented reality (“AR”) display of the first smart glasses and an AR display of the second smart glasses. Methods may include receiving, from the first smart glasses, a command to edit the application source code and in response, deactivating each input device of the second smart glasses. Methods may include receiving input of one or more edits on the first smart glasses and updating the application source code to include the input. Methods may include displaying the updated application source code on the AR displays and reactivating each input device of the second smart glasses.

Abstract: Systems, machines, methods and products for generating a configured software solution using one or more configuration packages. A decision service may be configured to generate decision data based on a configuration package comprising user-generated input, a collection of configurations, and a decision flow template. The user-generated input may be used for selecting an artifact from an artifact library in a configuration database. The collection of configurations may be infused, dynamically, into the decision flow template. The decision flow template may be exposed for user modification. The decision flow template may be integrated into the configuration package in association with at least one configurable decision element and a user configuration selected from the collection of configurations for specifying one or more parameters in the artifact. The artifact and the user configuration may be combined with the decision flow template to generate the configured software solution.

Abstract: A method may include applying to at least a portion of historical runtimes associated with each of a plurality of tests included in a test suite, a machine learning model trained to identify one or more outlying runtime values. The portion of historical runtimes may include an n quantity of the most recent historical runtimes. An expected runtime for each test may be determined based on the portion of historical runtimes excluding the outlying runtime values. A schedule for executing each test in the test suite may be determined based on the expected runtime of each test. The test suite may be executed in accordance with the schedule. Moreover, the executing of the test suite may be monitored based on the expected runtime of each test. Related systems and computer program products are also provided.

Abstract: In various embodiments, a data processing consent capture system may be configured to prompt the data subject to consent to one or more types of data processing (e.g., to provide a desired consent) in response to identifying particular cookies (e.g., or types of data processing) that a data subject has not consented to. The system may, for example, substantially automatically prompt the data subject to consent for one or more particular types of data processing in response to determining that the user (e.g., data subject) has requested that a website or other system perform one or more functions that are not possible without a particular type of consent from the data subject. The system may, for example, prompt the user to consent in time for a certain interaction with the website, application, etc.

Abstract: Technologies described herein reduce the size of a software application. In some embodiments, the size of one or more resource files of an application are reduced. Resource files include key/value pairs that define elements of the application. In some embodiments, the application's source code is analyzed to determine if an entry in a resource file may be removed. For instance, initialization functions in the application's source code may be analyzed to determine if a value loaded from a resource file is replaced before being used. For example, a button with a color property may be defined as grey by a resource, but later set to orange in an initialization function. In this case, the resource entry defining the button as grey is superfluous and may be safely removed. This technique allows for entries to be removed from a resource file even though the source code references the entries.

Abstract: The present disclosure pertains to a system configured to generate output data from a series of configurable cloud-computing processing operations. Some embodiments may; obtain, from a first database, data in a first format; process, in a first stage, the obtained data such that the obtained data is normalized; process, in a second stage, data in a second format different from the first format using a first set of cloud-computing devices; and detect, via a user interface, a first selection of at least two processing operations, the first selection being made from among a plurality of available processing operations. Each of the processing stages may include input data, a processing operation, and output data.

Abstract: A method for collaborative logic designing and debugging of a circuit includes initiating, via a session manager, a hardware debug session that includes a plurality of instances of client applications that can access one or more source-codes associated with a logic design of the circuit, the plurality of instances of client applications configured to replicate an execution state of the logic design. The method also includes analyzing, using an instance of a first client application from the plurality of instances of client applications, a defect in the logic design based on the execution state of the logic design. The method also includes editing, using an instance of a second client application from the plurality of instances of client applications, the one or more source-codes, to repair the defect in the logic design.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to allocate hardware in virtualized computing architectures. An example apparatus to manage a virtual server rack comprises a drift analyzer to determine that hardware resources assigned to a virtualized workload domain exceed the resources requested for the virtualized workload domain; and a rebalancer to reassign one or more of the hardware resources in response to an indication from the drift analyzer.

Abstract: In various embodiments, a system may be configured to analyze data for a particular consent capture point to identify a change in consent capture rate from the capture point. The system may, for example, be configured to automatically detect that the system has stopped receiving consent records from a particular capture point. In such embodiments, the system may be configured to generate an alert, and transmit the alert to any suitable individual (e.g., privacy team member, IT department member, etc.) regarding the capture point. The system may, for example, enable an entity to identify one or more capture points that may have become non-functional (e.g., as a result of one or more changes to the capture point).

Abstract: Provided is a specification document creation system including a first computer and a second computer, wherein the first computer is configured to generate, based on configuration information, display data for displaying a first display item, which is determined by the configuration information, of a BIOS on a display device, the configuration information indicating a hardware configuration of the first computer, and analyze the display data to generate first information including the first display item included in the display data, and the second computer is configured to analyze a source code of the BIOS to generate second information including a second display item, which is determined independently of the hardware configuration of the first computer, of the BIOS, and create a specification document for the BIOS in which the first display item included in the first information and the second display item included in the second information are described.

Abstract: Embodiments disclose systems and methods for generating source code. One or more application specific inputs and one or more external inputs are received. Using a machine learning model, source code is automatically generated based on the one or more application specific inputs and the one or more external inputs. The source code can embody the one or more application specific inputs and the one or more external inputs. One or more revisions to the automatically generated source code may be made, and a difference determined between the generated source code and the revised source code. The machine learning model may be further trained to generate a future source code based on the differences it determines.

Abstract: A vehicle electronic control system includes a center device and a vehicle master device. The center device includes: a campaign information obtainer obtaining campaign information of a program update; a vehicle state obtainer obtaining a vehicle state of a target vehicle of the program update; an execution requirement setter setting an execution requirement of a phase in the program update based on the campaign information obtained by the campaign information obtainer and the vehicle state obtained by the vehicle information obtainer; an execution requirement notifier notifying the vehicle master device of the execution requirement set by the execution requirement setter; and an update data deliverer delivering the update data to the vehicle master device.

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: Techniques for adaptive thresholding are provided. A first data point in a data stream is received, and a first plurality of data points from the data stream is identified, where the first plurality of data points corresponds to a timestamp associated with the first data point. At least a first cluster is generated for the first plurality of data points, and a predicted value for the first data point is generated based at least in part on data points in the first cluster. A deviation is computed between the predicted value for the first data point and an actual value for the first data point. Upon determining that the deviation exceeds a first predefined threshold, the first data point is labeled as anomalous, and reallocation of computing resources is facilitated based on labeling the first data point as anomalous.