Abstract: Methods, systems and computer program products are provided for automated runtime configuration for dataflows to automatically select or adapt a runtime environment or resources to a dataflow plan prior to execution. Metadata generated for dataflows indicates dataflow information, such as numbers and types of sources, sinks and operations, and the amount of data being consumed, processed and written. Weighted dataflow plans are created from unweighted dataflow plans based on metadata. Weights that indicate operation complexity or resource consumption are generated for data operations. A runtime environment or resources to execute a dataflow plan is/are selected based on the weighted dataflow and/or a maximum flow. Preferences may be provided to influence weighting and runtime selections.

Abstract: A method of processing test execution logs to determine error location and source includes creating a set of training examples based on previously processed test execution logs, clustering the training examples into a set of clusters using an unsupervised learning process, and using training examples of each cluster to train a respective supervised learning process to label data where each generated cluster is used as a class/label to identify the type of errors in the test execution log. The labeled data is then processed by supervised learning processes, specifically a classification algorithm. Once the classification model is built it is used to predict the type of the errors in future/unseen test execution logs. In some embodiments, the unsupervised learning process is a density-based spatial clustering of applications with noise clustering application, and the supervised learning processes are random forest deep neural networks.

Abstract: A method and system may be provided for recording discussions about computer code in an integrated development environment (“IDE”). In some aspects, a communication channel is integrated with an IDE. Communications and discussions may be tracked and linked with specific code sections.

Abstract: Methods, system and apparatus for the augmentation of an integrated development environment (IDE). The system and methods provide for the integration of all aspects of a development workflow to be initiated and completed from within the IDE. Every phase of development, including, grabbing a ticket, working on the ticket, asking teammates questions, requesting feedback, initiating code reviews, performing code reviews, creating feature branches, creating pull requests, creating merge requests and generating audit trails of all interactions users have with the IDE are managed and performed from within the IDE, eliminating the need to context switch or open additional application or websites.

Abstract: Systems, apparatuses and methods may provide for technology that assumes, by a root of trust located in a trusted region of a system on chip (SOC), control over a reset of the SOC and conducting, by the root of trust, an authentication of an update package in response to an update condition. The root of trust technology may also apply the update package to firmware located in non-volatile memory (NVM) associated with a microcontroller of the SOC if the authentication is successful.

Abstract: Provided is a program update management device that includes: an acquiring part that acquires a scene signal indicating a scene in which a vehicle is used; a determining part that determines a level indicating how strongly the vehicle is restricted when respective functions of a plurality of ECUs are impaired, the plurality of ECUs each having the same function in the scene indicated by the scene signal; and a selecting part that selects, from among the plurality of ECUs, an ECU for which a program update is performed, based on the level.

Abstract: Systems, methods, and related technologies for device software monitoring and device software updating are described. In certain aspects, a device is selected based on being a smart device and a software version of associated with the software of the device is determined. The device software may then be automatically updated if newer software is available.

Abstract: A processor of a sensor device performs measurement processing by one or a plurality of sensors and transmission processing of sensor data generated by the measurement processing. The sensor device includes a processing routine table that stores a processing routine configured to include, corresponding to an identifier for identifying processing performed by a processor, a type of the processing, an execution trigger of the processing, and trigger information that prescribes a trigger for transmitting the sensor data. The processor controls processing in a processing routine of the processing routine table, based on trigger information, so that the sensor data subjected to measurement processing is immediately transmitted, or temporarily stored in a buffer and transmitted after a predetermined time.

Abstract: The disclosure relate to detecting performance regressions in software used to control autonomous vehicles. For instance, a simulation may be run using a first version of the software. While the simulation is running, CPU and memory usage by one or more functions of the first version of the software may be sampled. The sampled CPU and memory usage may be compared to CPU or memory usage by each of the one or more functions in a plurality of simulations each running a corresponding second version of the software. Based on the comparisons, an anomaly corresponding to a performance regression in the first version of the software relating to one of the one or more functions may be identified. In response to detecting the anomaly, the first version of the software and the one of the one or more functions may be flagged for review.

Abstract: An example method of operation may include automatically receiving information from a storage area in response to a signal, which information may include test results for a computer product evaluated by a plurality of test stages. The method may also include retrieving deployment parameters for the computer product, determining whether the test results satisfy the deployment parameters for the computer product, and automatically authorizing deployment of the computer product based on whether the test results satisfy the deployment parameters.

Abstract: A system and method are disclosed for creating solution design blueprints. A solution design blueprint is a machine-readable data structure that includes a conceptual design model for an application framework. A user interface is configured to receive a plain language textual request from a user that describes a desired application or solution to a problem. Artificial Intelligence is leveraged to fit the textual request to semantic data models and map elements of the textual request to components of a design library. The resulting solution design blueprint can be presented to a user, and the user interface can be used to provide feedback related to the solution design blueprint that can be utilized to update machine learning algorithms and/or neural networks. In some embodiments, the solution design blueprint can be converted to an application framework that is provided to the use in an integrated development environment of the user interface.

Abstract: An information processing device, includes a memory; and a processor coupled to the memory and configured to: generate second data by adding, to first data including a machine language, first machine language data that may be destroyed at a time of transfer of the first data and second machine language data that is not destroyed at the time of the transfer, and transmit the second data.

Abstract: A method can include storing first instruction data in a first region of a nonvolatile memory device; mapping addresses of the first region to predetermined memory address spaces of a processor device; executing the first instruction data from the first region with the processor device; receiving second instruction data for the processor device. While the first instruction data remains available to the processor device, the second instruction data can be written into a second region of the nonvolatile memory device. By operation of the processor device, addresses of the second region can be remapped to the predetermined memory address spaces of the processor device; and executing the second instruction data from the second region with the processor device.

Abstract: An engine model construction method includes generating test patterns in which a plurality of manipulated variables used for an engine test are changed with time, correcting the test patterns based on first coverage of a first space of manipulated variables are allowed to take and second coverage of a second space of change rate values of the manipulated variables are allowed to take, acquiring pieces of time series data of operation amounts of the manipulated variables and controlled amounts with respect to the manipulated variables by performing an engine test using the corrected test patterns, and constructing a first engine model by performing machine learning on training data in which the corrected test patterns are adopted as input and the pieces of time series data are adopted as correct answers, by a processor.

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system can provide a service to recommend actions and transformations, on an input data, based on patterns identified from the functional decomposition of a data flow for a software application, including determining possible transformations of the data flow in subsequent applications. Data flows can be decomposed into a model describing transformations of data, predicates, and business rules applied to the data, and attributes used in the data flows.

Abstract: The disclosed technology includes systems and methods for automatically generating a dynamic system context diagram based on machine-readable code. A method can include receiving, at a rules engine, machine-readable code describing interactions among a plurality of applications in software architecture, evaluating, with the rules engine in communication with a system of record (SoR), compliance of the interactions among the plurality of applications according to the SoR, identifying, with the rules engine, and based on compliance evaluation, one or more dependencies among the plurality of applications, generating, with an output engine, a system context diagram image comprising a graphical representation of the plurality of applications with associated interactions and dependencies, and outputting, for display, the system context diagram image.

Abstract: A transfer learning system is used for the development of neural transformer models pertaining to software engineering tasks. The transfer learning system trains source code domain neural transformer models with attention in various configurations on a large corpus of unsupervised training dataset of source code programs and/or source code-related natural language text. A web service provides the trained models for use in developing a model that may be fine-tuned on a supervised training dataset associated with a software engineering task thereby generating a tool to perform the software engineering task.

Abstract: Processing a neural network data flow graph having a set of nodes and a set of edges. An insertion point is determined for a memory reduction or memory restoration operation. The determination is based on computing tensor timing slacks (TTS) for a set of input tensors; compiling a candidate list (SI) of input tensors, from the set of input tensors, using input tensors having corresponding TTS values larger than a threshold value (thTTS); filtering the SI to retain input tensors whose size meets a threshold value (thS); and determining an insertion point for the operation using the SI based on the filtering. A new data flow graph is generated or an existing one is modified using this process.

Abstract: A system and a computer-implemented method for viewing at least one robotic process automation (RPA) workflow using a web based user interface are disclosed herein. The computer-implemented method includes accessing the web based user interface and identifying the at least one RPA workflow for viewing. The computer-implemented method further includes generating, using a workflow object model component, a workflow diagram for the identified at least one RPA workflow. The computer-implemented method further includes rendering, using a web based visualization engine component, the generated workflow diagram for the identified at least one RPA workflow and displaying the rendered workflow diagram for viewing of the at least one RPA workflow on the web based user interface.

Abstract: According to certain aspects of the disclosure, non-transitory computer readable media, systems and methods are disclosed for creating and executing test scenarios for automated testing of web pages. A computer system, for example, may perform operations including: recording one or more actions performed by a user on a web page, the one or more actions resulting in a web page element being displayed in the web browser application, recording an identifier of the web page element, in response to detecting a user input indicating a selection of the web page element, and recording a characteristic of the web page element; and generating, by the testing extension, a test scenario specifying a testable outcome resulting from the one or more actions, the testable outcome being an occurrence of an element having the identifier and the characteristic.