Abstract: Systems and methods for learning differentially private machine-learned models are provided. A computing system can include one or more server computing devices comprising one or more processors and one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors cause the one or more server computing devices to perform operations. The operations can include selecting a subset of client computing devices from a pool of available client computing devices; providing a machine-learned model to the selected client computing devices; receiving, from each selected client computing device, a local update for the machine-learned model; determining a differentially private aggregate of the local updates; and determining an updated machine-learned model based at least in part on the data-weighted average of the local updates.

Abstract: In certain embodiments, a software pipeline (“pipeline”) is configured by the use of gates for progressing an application from one stage to another (e.g., from a development stage to a production stage). A configuration file having a set of attribute values that is descriptive of an application, and a gate mapping file having information associated with the gates to be invoked for different combinations of attribute values are obtained. The configuration file is processed using the gate mapping file to determine a set of gates to be invoked for progressing the application in the pipeline based on the attribute values of the application. The set of gates are invoked to cause a corresponding set of software routines to be executed for progressing the application.

Abstract: In some examples, a system processes event data and video frames produced by a program during execution of the program, the event data representing user actions with respect to a graphical user interface (GUI) of the program. The system identifies an area of the GUI that corresponds to a respective user action of the user actions, wherein identifying the area of the GUI uses a first video frame before an event corresponding to the respective user action, and a second video frame after the event corresponding to the respective user action. The system identifies, based on the identified area, a test object representing a user interface (UI) element, and generates a test script for testing the program, the test script including the test object.

Abstract: A self-healing build pipeline architecture for a software application build job across a distributed computer platform comprises a public API that receives configuration data describing the build job, stores the configuration data in a decentralized database, serves requests to/from a pipeline tracker API, and stores states of build pipelines during the build job. The decentralized database stores the configuration data and a project identifier for the build, and metadata regarding states of the build pipelines collected across the distributed computer platform. The pipeline tracker API runs local to the build environment in the distributed computer platform and sends a build status to public API for updating the decentralized database. For any failures in any of the build pipelines, the state is retrieved from the decentralize database and a new build pipeline is triggered locally that resumes from the failed state to provide a self-healing build pipeline architecture.

Abstract: An apparatus comprises at least one processing device coupled to memory. The at least one processing device is configured to obtain an operating system image from a production server or other computing device and to implement a first operating system configuration on a non-production server, a test server or other type of server based at least in part on the operating system image. The at least one processing device is further configured to modify the first operating system configuration to generate a second operating system configuration on the server and to generate a modified operating system image-based at least in part on the second operating system configuration. The at least one processing device is further configured to provide the modified operating system image to the computing device.

Abstract: Source code of a golden version and a next version of a program is received in which procedure calls are modified to call from an entry point table (EPT) with index numbers corresponding to procedure memory addresses. An executable defect-free golden version program and next version program with a defect are received. A first entry point table (first EPT) for the new version program and a second EPT for the golden version program are generated. A series of substitutions of procedures from the second EPT to the first EPT is performed and an order of substitutions includes: a module set, a module of the module set, a procedure set of the module, and a procedure of the procedure set. The defect producing procedure is identified by substituting in order until the defect is absent and proceeding to the next substitution in order.

Abstract: Embodiments provide a thread classification method that represents stack traces in a compact form using classification signatures. Some embodiments can receive a stack trace that includes a sequence of stack frames. Some embodiments may generate, based on the sequence of stack frames, a trace signature that represents the set. Some embodiments may receive one or more subsequent stack traces. For each of the one or more subsequent stack traces, some embodiments may determine whether a subsequent trace signature has been generated to represent the sequence of stack frames included within the subsequent stack trace. If not, some embodiments may generate, based on the trace signature and other subsequent trace signatures that were generated based on the trace signature, the subsequent trace signature to represent the subsequent sequence of stack frames.

Abstract: Methods and systems for a platform development version control system for monitoring contributors to software platform development. The methods and systems generate data analytics on contributors to software platform development using group affiliations as listed in a group directory (e.g., a corporate directory for an entity providing the software platform) as a common organizing factor. For example, by organizing the methods and systems according to the group affiliations, the methods and systems may generate data analytics on contributions of contributors within those groups, irrespective of whether or not the group members are working on the same project. The methods and systems may then provide recommendations and graphical representations based on the data analytics.

Abstract: Systems and methods for maintaining the safety of a software-based system. One method includes automatically generating a first artifact tree for a hazard for a first version of the system and automatically transforming the first artifact tree into a first augmented tree using a set of heuristics. The method also includes automatically generating a second artifact tree for the hazard for a second version of the system and automatically transforming the second artifact tree for the hazard into a second augmented tree using the set of heuristics. The method further includes automatically comparing the first augmented tree and the second augmented tree to generate a delta view, and automatically generating, based on the delta view, at least one selected from a group consisting of a safety warning for the second version of the software-based system and an actionable recommendation to maintain safety of the second version of the software-based system.

Abstract: Disclosed are methods, systems, devices, apparatus, media, design structures, platforms, and other implementations, including a method that includes receiving, by a processor-based device, configuration data representative of an initial arrangement of interlinked components forming a data application, and determining based on the configuration data, by the processor-based device, one or more complexity scores indicative of levels of complexities for one or more portions of the initial arrangement of interlinked components forming the data application. The method further includes automatically reconfiguring, by the processor-based device, the initial arrangement of interlinked components based on the computed one or more complexity scores to produce a resultant arrangement of interlinked components forming the data application.

Abstract: A procedure for changing, in particular for updating, a firmware of a head station of a modular node, having a transfer of a compatibility verification routine stored on the head station from the head station on which a first firmware is stored in a nonvolatile manner to a computer connected to the head station, a verification using the verification routine executed on the computer as to whether a second firmware is compatible with the head station, and a replacement of the first firmware on the head station by the second firmware if the verification has the result that the second firmware is compatible with the head station, and also a suitably equipped head station.

Abstract: Techniques for time-series analysis for forecasting computational workloads are disclosed. A resource management system monitors a computing system and obtains metrics data from the computing system. The metrics data is stored as a set of historical data points of a data set. A first portion of the set of historical data points comprise an outlier that does not correspond to a seasonality pattern associated with a second portion of the set of historical data points. The resource management system tests a first time-series model that incorporates a first exogenous variable corresponding to a first exogeneous factor to determine that the first time-series model fits both the first portion of the set of historical data points and the second portion of the set of historical data points within an error threshold. Then, the resource management system selects the first time-series model to predict future data points of the data set.

Abstract: Methods and systems are described herein for improvements to model development, particularly in terms of source code commitments for these models. For example, methods and systems allow contributors to manage when and where commitments and/or the results of those commitments are stored and/or do so without the use of an additional layer of external software by correlating source code commitments and model result records during model development. Moreover, the methods and systems allow contributors to manage when and where commitments are store automatically without the use of an additional layer of external software through user of native source code commands and libraries.

Abstract: Systems and methods for automatic self-configuration of deployments of sets of enterprise software applications to users are disclosed. Exemplary implementations may: store information, including executable code for a set of enterprise software applications and a configuration database including deployment-specific configuration settings and corresponding setting values; monitor and quantify operations of a deployment of the set of enterprise software applications; assess whether a system-initiated modification of the deployment is likely to improve a particular monitored and quantified operation; automatically generate a system-initiated modification database based on the system-initiated modification; and modify the deployment in accordance with the system-initiated modification database.

Abstract: An intelligent determination of code change review assignments and subsequent secured access to the determined assignments. Code changes undergo code change complexity determination which is based on (i) a level of importance of the module(s) in which the changes occur, (ii) the volume of metadata files impacted by the code changes, and (iii) the dependency of the code changes on external modules. A distributed trust computing network is implemented and a code change smart contract which relies on smart contract rules is used to determine and allocate code change review assignments. In this regard, data blocks within a distributed ledger define individual segments/portions of the code change file with each data block identifying a code change review assignment.

Abstract: A system configuration derivation device 90 includes a storage unit 91 that stores a concretization rule in which a method is specified for concretizing abstract configuration information by confirming an unconfirmed portion of the abstract configuration information, which is information indicating configuration of a system in which the unconfirmed portion is included, and a generation unit 92 that concretizes the abstract configuration information included in configuration requirements of the system using the concretization rule stored to generate system configuration information, which is information indicating the configuration of the system in which the unconfirmed portion is not included, on the basis of the configuration requirements.

Abstract: Software components can be automatically integrated into a control framework in a distributed computing environment. For example, a system can determine that a flag is set in relation to a complementary resource that is monitored by a controller in a distributed computing environment. In response to determining that the flag is set, the system can identify a target software component that is not managed by the controller in the distributed computing environment. The system can then integrate the target software component into a control framework of the distributed computing environment in which the target software component is managed by the controller based on the complementary resource.

Abstract: A system includes one or more code development servers operable to monitor development of code files and one or more code execution servers operable to execute the code files. One or more code analysis tools of the system include instructions that when executed by at least one processing device result in collecting code development data associated with development of the code files on a per user basis and determining a predicted code execution performance score of one or more selected files of the code files based on the code development data. One or more resources of the one or more code execution servers associated with execution of the one or more selected files are predictively allocated based on a predicted code execution performance score. One or more code execution metrics are captured associated with executing the one or more selected files on the one or more code execution servers.

Abstract: Provided is a method of coding a robot control device according to a standardized coding format, the method including displaying a format of a syntax to be input in unit of components; with respect to each component in the syntax, displaying one or more candidate component values that are to be input as a value of each component; and completing the syntax based on a user selection on the candidate component values with respect to each component.

Abstract: In some implementations, there is provided a method that includes generating a user interface to enable selection of configuration information and initiation of a build of an application instance; receiving, from the user interface, an indication to initiate the build of the application instance; assigning at least one slave node to build, based on the configuration information, the application instance; obtaining, from at least one repository, build information including at least one of a command script, a dataset, and an application instance template; generating, based on the build information, a container file; storing the container file; generating the container image and storing the container image; and executing the image to provide a container. Related systems and articles of manufacture are also disclosed.