Abstract: In some implementations, a system may receive dependency indicators associated with a plurality of cloud-based applications and receive change indicators associated with changes to one or more first applications of the plurality of cloud-based applications. The system may receive an indicator associated with an incident ticket based on a problem with a second application of the plurality of cloud-based applications. The device may determine at least one of the change indicators associated with the incident ticket based on dependencies between the one or more first applications and the second application and based on a difference between a time associated with the incident ticket and a time associated with the at least one of the change indicators. The system may, based on determining the at least one of the change indicators, transmit a command to rollback at least one of the changes or to rollforward at least one change.

Abstract: Techniques described herein relate to a method for managing composed information handling systems. The method includes obtaining, by a system control processor manager, a composition request for a composed information handling system to perform a workflow; in response to obtaining the composition request: identifying a composed system blueprint associated with the workflow; making a first determination that there are first predictive analytics associated with the composed system blueprint; in response to the first determination: identifying a composed infrastructure associated with the composed system blueprint capable of performing the workflow based on telemetry data and the first predictive analytics; instantiating a composed information handling system using the composed infrastructure to service the composition request; and setting up telemetry services for the composed information handling system using an at least one control resource set.

Abstract: A computer-implemented method of managing artefact information and a computer system arranged and configured to execute the steps of the computer-implemented method are provided, wherein at least one internal sequence of artifact information is stored in an internal data store; wherein at least one external sequence of artifact information is stored in a respective external data repository, and wherein the respective internal sequence relates to the respective external sequence. The computer-implemented method includes: importing metadata relating to the respective external sequence from the respective external data repository to a data storage platform; importing the metadata relating to the respective external sequence from the data storage platform to the internal data store; and introducing a link into the respective internal sequence, wherein the link is based on the metadata and links the respective internal sequence with the respective external sequence.

Abstract: Systems and methods for instantiating a filter for a process graph are provided. A process graph of a workflow is received. Context data associated with the process graph is stored. A filter is instantiated to filter the process graph based on the stored context data. The filtered process graph is output.

Abstract: Session-specific edit recommendations may be made for editing a code file. After a code editing session is started, code file edits may be captured. A machine learning technique may be applied to learn the code edits and recommend alternative code portions for portions of the code file during the code editing session. The recommendations may be provided and accepted, or not, via an interface of a code editor application.

Abstract: The possibility of a desired program being automatically generated is increased by a program generation device including: a search unit configured to search for a first program that corresponds to a specification written in natural language similar to natural language that describes a specification of a program to be generated, from a set of pairs each constituted by natural language that describes a specification of a program and the program that satisfies syntax of a programing language; and a change unit configured to change the first program to generate a second program that satisfies at least one pair of an input value and an output value.

Abstract: In an example embodiment, three roles are defined for each of the following: resource discovery: provider, aggregator, and consumer. The provider is the one whose resource information will be shared. Rather than the provider needing to implement the complicated API, however, an aggregator may provide that role. The aggregator defines the API and is able to gather resource information from potentially multiple providers (and also, in some embodiments, other aggregators). The consumer then accesses the aggregator to obtain resource information rather than directly accessing the provider.

Abstract: In a method for developing a child application, an interface of a child application developer tool is displayed. The child application developer tool is configured to provide a plurality of child application development modes. Each of the child application development modes is associated with a different run-time environment. A user selection of one of the plurality of child application development modes is received via the interface. Based on the selected one of the plurality of child application development modes, development mode information of a parent application that is associated with the one of the plurality of child application development modes is obtained. The run-time environment of the parent application is created based on the obtained application development mode information. At least one of code editing or code debugging of the child application is performed via the child application developer tool.

Abstract: Techniques for cybersecurity analysis. A method includes identifying a first set of paths to a first asset. The first set of paths includes a first path which allows for uploading inspection code, a second path which allows for running the inspection code, and a third path which allows for obtaining results of running the inspection code. The first set of paths is selected such that application programming interfaces (APIs) of the first set of paths are at least partially shared with APIs of a second set of paths to each of at least one second asset and, further, selected based on at least one request processing attribute of the at least one API used in order to access the first asset. The inspection code is uploaded via the first path and run via the second path. Outputs of the inspection code are obtained via the third path and analyzed.

Abstract: A facility for retrieving content. The facility invokes an API, as part of the invocation passing to the API: (1) information identifying one or more units of content to return; and (2) an indication that an entity on behalf of which the invocation is performed attests that the entity is compliant with a license that applies to the identified units of content. The facility receives a response to the API invocation that contains the identified units of content.

Abstract: An automated system for detecting performance bugs in a program and for providing code recommendations to improve the performance of the program generates a code recommendation table from performance-related pull requests. The performance-related pull requests are identified in part from a classifier trained on semi-supervised data. A code recommendation table is generated from performance-related pull requests and is searched for similarly-improved code based on a set of difference features that includes structural and performance features of the before-code of a pull request that is not in the after-code.

Abstract: An order management system in electronic communication with a database may be configured to manage concurrent update requests for the order data stored in the database. In particular, the order management system may be configured to receive two or more order modification requests, determine that the second order modification request includes one or more aspects that conflict with the modified order and includes one or more aspects that do not conflict with the modified order, send a notification to the second user, wherein the notification includes the one or more aspects that conflict with the modified order, and modify the modified order according to the one or more aspects of the second order modification request that do not conflict with the modified order to create a second modified order.

Abstract: A method for facilitating automated enforcement of a data publication and usage contract is provided. The method includes capturing a data contract from data that is published by a data service provider, the data contract including a data contract element; converting the captured data contract into a predetermined file format; retrieving metadata that correspond to the data, the metadata including usage information that relates to a consumption of the data by a data consumer; validating the retrieved metadata based on the converted data contract; and automatically initiating an enforcement action based on a result of the validating.

Abstract: A method includes generating a temporary computing environment on a computing node, wherein the temporary computing environment comprises a bootstrapping component, generating, by the bootstrapping component, a configuration for a container platform from within the temporary computing environment, and writing, by the processing device, the configuration to storage of the computing node from within the temporary computing environment.

Abstract: An embodiment of the present invention is directed to evaluating and identifying optimal features to address and improve automation patching success. An embodiment of the present invention compares machine leaning algorithms and their accuracy in predicting the outcome of upcoming scheduled maintenance activities. Understanding that predicted outcome and the path that is generated to reach that outcome, the features that predispose an asset into a failure state can be addressed preemptively.

Abstract: A system, method, and computer readable medium receive a container image and an attestation log. The container image is built from a build pipeline and the attestation log includes information corresponding to tasks utilized by the build pipeline to build the container image. The system, method, and computer readable medium compare the information in the attestation log with policies that includes build pipeline requirements. The system, method, and computer readable medium release the container image to a destination based on the comparison indicating that tasks utilized by the build pipeline to build the container image meet the build pipeline requirements.

Abstract: An embodiment may involve persistent storage containing one or more tables, wherein the tables include entries that specify automations, wherein the automations are software applications. One or more processors are configured to: receive a specification for a new automation, wherein the specification includes a frequency at which the new automation is to be executed, and expected time or resources saved per execution; generate an automation request within the tables, wherein the automation request includes the frequency and the expected time or resources saved; generate a reference from the automation request to an automation configuration item (CI) in the tables, wherein the automation CI represents a software application used to perform the new automation; cause the software application to execute at least part of the new automation and in accordance with the frequency; and measure actual time or resources saved per execution of the new automation.

Abstract: Techniques and solutions are described for propagating extensions to data artifacts, such as data artifacts defining objects in a physical or virtual data model. One or more data artifacts are identified that are related to a first data artifact. One or more extension elements of the first data artifact are analyzed for propagation to at least one data artifact of the one or more data artifacts. Analyzing whether an extension element should be propagated can include analyzing a type of the extension element, a type of operation or context in which the extension element is used, or how the at least one data artifact refers to, uses, or incorporates the first data artifact, including particular elements thereof. The results of the analysis are compared with various rules. Extension elements are propagated automatically, manually upon user approval (e.g., propagation recommendations are provided), or in a semi-automated manner.

Abstract: A multi-processor system includes a plurality of processors, a scheduler, and a selector. Each of the plurality of processors is included in at least one of a plurality of domains. The plurality of domains include three or more domains and are defined based on a hierarchical domain structure. The scheduler receives and manages at least one task performed by the plurality of processors. The selector selects one of the plurality of domains based on states of the plurality of domains to assign the at least one task to the selected domain, and selects at least one processor among processors in the selected domain based on states of the processors in the selected domain to assign the at least one task to the selected processor, when the at least one task is received.

Abstract: Techniques are described for assisting users with the process of modernizing software applications from a source software architectural pattern (e.g., a model—view—controller (MVC) pattern, a multitier architecture, etc.) to a target architectural pattern (e.g., microservices, event-driven architecture, etc.). A decomposition analyzer receives as input artifacts associated with a software application under analysis and an architectural pattern that a user desires to use for a modernized version of the software application. The decomposition analyzer generates, based on the application artifacts, a graph-based model of the software application, where the model includes nodes representing application components (e.g., classes) and edges representing dependency relationships among the components. The decomposition analyzer further uses machine learning techniques and other types of analyses to identify recommended groupings of nodes from the graph-based model for decomposition.

Abstract: An interface for enabling a computer device to utilize data property-based data placement inside a nonvolatile memory device comprises: executing a software component at an operating system level in the computer device that monitors update statistics of all data item modifications into the nonvolatile memory device, including one or more of update frequencies for each data item, accumulated update and delete frequencies specific to each file type, and an origin of the data item; storing the update statistics of each of the data items and each of the data item types in a database; and intercepting all operations, including create, write, and update, of performed by applications to all the data items, and automatically assigning a data property identifier to each of the data items based on current update statistics in the database, such that the data items and assigned data property identifiers are transmitted over a memory channel to the non-volatile memory device.

Abstract: Disclosed herein are system, method, and computer program product embodiments for automatically cataloging updated Application Programming Interface (API) specifications. The API specifications may have been previously published to an application exchange platform. An automatic cataloging tool installed at an API development system may identify an updated API specification committed to an API specification repository. To validate that a change has been made, the automatic cataloging tool may compare the updated specification, metadata, and/or referenced documentation files to an API specification previously posted to the application exchange platform. In response to determining that the API specifications differ, the automatic cataloging tool may transmit the updated API specification to the application exchange platform. The application exchange platform may then replace the previous API specification with the updated API specification for client devices to view.

Abstract: In some examples, continuous learning-based application related trade-off resolution and implementation may include generating, based on a plurality of historical tradeoff instances, an application feature matrix. Further, association rules for historical tradeoff instances for which decisions are not known, and a decision tree for historical tradeoff instances for which decisions are known may be generated. Decision rules may be induced, and default rules may be applied to a cold start scenario. The decision rules and the default rules may be refined to generate refined rules, and a confidence level may be determined for the refined rules. The refined rules may be prioritized based on the confidence level and applied to a new tradeoff instance to generate a resolution associated with the new tradeoff instance. The resolution may be implemented with respect to the new tradeoff instance.

Abstract: In some embodiments, there is provided a method including creating at least one reusable user interface metadata definition for at least one user interface object; storing the at least one reusable user interface metadata definition; creating at least a portion of a user interface page, which includes the at least one user interface object, using the at least one reusable user interface metadata definition; overriding the at least one reusable user interface metadata definition; bundling into a container the least one reusable user interface metadata definition with other metadata definitions; and deploying the container of the at least one reusable user interface metadata definition and the other metadata definitions to a device where a metadata interpreter can generate at least one user interface object associated with the at least one reusable metadata definition. Related systems and computer program products are also provided.

Abstract: A technique manages objects in a software development project. In particular, in response to receiving a commit request for committing a group of objects, a group of historical commit requests associated with the group of objects are acquired based on a commit history, wherein historical commit requests in the group of historical commit requests involve the group of objects. A candidate object is selected from at least one object involved in the historical commit requests that is different from the group of objects. An association relationship between the candidate object and the group of objects is determined. The candidate object is identified as a missing object in response to determining that the association relationship satisfies a predetermined condition, the missing object indicating an object associated with the commit request but not included in the commit request. Accordingly, objects that are missing in a commit request can be automatically checked.

Abstract: An orchestration engine that interfaces with the various clouds to implement the system solution. The orchestration engine builds, configures, and converges the single system solution. The orchestration engine builds the system by instantiating machines and services on the various clouds. The orchestration engine configures the system according to input from the client and the solution provider and then converges the various systems by establishing relationships and connections between the various services. Optionally, the orchestration engine also runs tests to verify that the system is working properly. Once the system has been built, configured and converged, the orchestration engine provides the client with a single entry point for using the system solution.

Abstract: Methods and systems for generating a program include parameterizing a high-order function to replace data with primitive functions. A neural programmer interpreter (NPI) model is trained for the high-order function. Respective neural network models are trained for each primitive function. The neural network models generate data for the NPI model when called.

Abstract: Techniques are described for providing software developers with secure software project development environments via cloud-based or locally installed integrated development environments (IDEs). A cloud provider network provides a project development environment policy service that enables users to configure project development environment policies associated with various software projects and to deploy configured policies to users' project development environments as appropriate. A project development environment policy can include rules related to monitoring and controlling version control system actions, monitoring the content of project source code pushed to version control repositories, among other software project governance-related configurations.

Abstract: A method provides an intervention point for manipulating a variable of a runtime environment for testing a control-device program component to be tested in a test environment. Software of the control-device program component, in accordance with the AUTOSAR standard, is divided into three layers, wherein the three layers include a layer of program components, a layer of the runtime environment, and a layer of device-related basic programs. The layer of the program components has a test scenario program component for providing input values and a program component for receiving output values and displaying the test result. The method includes: providing the control-device program component to be tested with interfaces that are each defined in accordance with the AUTOSAR standard; and creating an executable program of the control-device program component to be tested and of the test scenario program component.

Abstract: Methods, systems, and computer-readable media for a query language for selecting and addressing resources are disclosed. Records are stored in a data store. The records comprise attribute data descriptive of resources managed by a provider network. The data store is queried to select one or more records matching one or more values of the attribute data. The query is expressed using a query language. A resource group is determined based (at least in part) on the query. The resource group comprises one or more resources corresponding to the one or more records selected by the query.

Abstract: A debug support program causes a computer to execute a step of extracting a set of variables having a dependency relation from a plurality of variables written in a plurality of process blocks that are included in a sequence program and each describe a process per device, that is to say, a process per slave device; a step of collecting log information recording information regarding input of a value to each of the plurality of variables written in the process blocks; a step of correcting an extraction result regarding the dependency relation on the basis of contents of the collected log information; and a step of presenting a corrected extraction result.

Abstract: Embodiments described herein a code generation and understanding model that builds on a Transformer-based encoder-decoder framework. The code generation and understanding model is configured to derive generic representations for programming language (PL) and natural language (NL) in code domain via pre-training on unlabeled code corpus, and then to benefit many code-related downstream tasks with fine-tuning. Apart from the denoising sequence-to-sequence objectives widely adopted for pre-training on natural language, identifier tagging and prediction pre-training objective is adopted to enable the model to better leverage the crucial token type information from PL, which specifically are the identifiers assigned by developers.

Abstract: Method and systems provide automated configuration of replaceable hardware components of a chassis comprising a plurality of IHSs (Information Handling Systems) and a plurality of storage devices that are configured to support demands of a specific computing solution designed for a particular computing task. The IHSs may be computing sleds and the storage devices may be storage sleds, where the sleds are coupled within bays of the chassis. Processes operating on the IHSs monitor for changes to settings related to the first computing solution. A chassis management controller detects updates to the replaceable hardware components that are coupled to the chassis and determines supported settings for detected new hardware components. Parameters for configuring the new hardware components for supporting the first computing solution are selected and used to configure the new hardware components.

Abstract: Methods, systems, and computer program products for deploying a static code analyzer based on program synthesis from input-output examples. A computer system uses program synthesis on a set of input-output examples of source code edits to generate a rewrite rule that defines a transformation pattern. Based on a determined static code analyzer format, the computer system generates a static code analyzer from the rewrite rule. The static code analyzer includes a find portion that indicates a matching condition for identifying a portion of source code text, and a fix portion that indicates a textual replacement to apply to the portion of source code text matched by the find portion. The computer system deploys the static code analyzer to a development environment, including configuring the static code analyzer to be executable against a source code file within the development environment.

Abstract: A detection modeling system performs a distribution analysis to alert to model degradation. The detection modeling system may have a distribution analysis module configured to perform an alerting process in conjunction with a processing device. The distribution analysis module may select, by the processing device, model metrics for analysis, the model metrics being a measure of a parameter associated with the analytical model and determine normal distributions for model metric results for each of the selected model metrics. The detection modeling system may further receive model metric values for each of the selected model metric, compare, by the processing device, the model metric values to the normal distributions for model metric results for each of the received model metric value, and alert, by the processing device, to model degradation of the analytical model based on the comparison of the model metric values to the normal distributions for model metric results.

Abstract: A resource provisioning service allows users to provision multiple, different network resources in an atomic manner and with a single call to a resource provisioning service. In some instances, the multiple, different network resources comprise individual types of resources that form a portion of one or more cloud-computing platforms. For instance, one or more entities may host and operate a cloud-computing platform that includes different types of network resources, such a storage service, a load balancing service, a compute service, a security service, or any other similar or different type of network-accessible service.

Abstract: Embodiments of the disclosure provide systems and methods for enabling disaster recovery from a source cluster to a target cluster in a multi-cluster cloud-computing environment. A domain cluster configures a replicated data volume to be updated with data from a data volume of the source cluster, wherein the replicated data volume resides in the target cluster; determines that the target cluster is to replace the source cluster as an active cluster; rebuilds, in the target cluster, a new container instance to replace the container instance on the source cluster; configures the container instance to utilize the replicated data volume in the target cluster; and discontinues recognition of the data volume and container instance on the source cluster as being authoritative.

Abstract: Disclosed herein are system, method, and computer program product embodiments for generating software artifacts operable across diverse platforms from a single conceptual data model. The conceptual data model may be enhanced with metadata that allows the creation of platform-specific logical data models containing additional metadata that is leveraged to create deployable software artifacts. An organization may subsequently modify the conceptual data model and all relevant software artifacts may be updated and redeployed across all integrated platforms. Such a conceptual data model further facilitates the creation of documentation describing data entities in the organization's technical infrastructure, the creation of mapping files for use by a data exchange system, and the processing of federated queries that gather data from multiple data stores across a data landscape.

Abstract: An illustrative computing system for an intelligent web service verification and validation system processes base input to identify a web service for testing. The intelligent web service verification and validation system processes user defined functional inputs, expected outputs, and assertions with a machine learning engine to provide functional inputs, expected outputs, and assertions based on provided input. The intelligent web service verification and validation system generates a test case pattern, such as a minimally sized test case pattern for regression testing. The intelligent web service verification and validation system executes testing of the service based on the test case pattern and logs test data in a data repository. The intelligent web service verification and validation system analyzes validation and test information, including inputs, outputs, and assertions, using a machine learning algorithm to improve future input and test case generation and testing procedures for the web service.

Abstract: A system for application monitoring includes an interface to receive an indication regarding an application. The system includes a processor to determine whether the application is compliant based at least in part on a set of policy rules, and in the event that the application is compliant, provide an indication that the application is compliant.

Abstract: A computing device can monitor a set of memory usage metrics of the computing device. Based on the set of memory usage metrics, the computing device can determine whether memory usage will exceed a critical memory threshold within a future period of time. In response to determining that the memory usage will exceed the critical memory threshold within the future period of time, the computing device can degrade one or more application features of an application executing on the computing device.

Abstract: A system and method are provided for logically copying data from a source database to a first target database and a second target database. Based on table partition information, the source database is queried to collect partition metadata information for a first set of partitions and a second set of partitions. A first set of the partition metadata information for the first set of partitions and a second set of the partition metadata information for the second set of partitions can be used to create at least one extent chunk for each partition of a table. The source database can be queried, based on a first set of extent chunks and a second set of extent chunks, for a first set of data to be written to the first target database and a second set of data from the source database to be written to the second target database.

Abstract: Techniques are described for automatic creation of optimal auditable entities (AEs) using a machine learning (ML)-based clustering model. The clustering model, when executed on one or more computing devices within an audit system of a company, is configured to automatically cluster the company's business processes into AEs based on similarity analyses of business process attributes. More specifically, in some examples, the clustering model ingests business processes and their corresponding attributes from a database, automatically clusters together business processes to achieve maximum intra-cluster similarity scores, and outputs the final clusters as model AEs. The resulting model AEs may be used as functional units for internal audits of the company's business processes. The resulting model AEs may improve audit efficiency due to the model AEs including only highly similar business processes.

Abstract: Prediction, detection and mitigation of network or device issues in a communication system are facilitated. An embodiment can comprise: determining whether an identified problem of a device has an associated defined solution stored in a repository of information; transmitting solution information representative of the associated defined solution to the device for application of the solution information to the device in a manner determined to have less than a defined amount of impact on the device and in accordance with defined security protocols of the device; and assessing a performance of the device after application of the solution information to the device to determine whether the solution information solved the identified problem. In some embodiments, solution detection can be performed such that based on a determination that the identified problem has been removed, the change that caused the identified problem can be determined.

Abstract: Techniques are described for automatically identifying monolithic software applications in users' computing environments for software modernization purposes. A monolithic patent application typically refers to a single-tiered application with self-contained functionality designed largely without modularity, although many types of applications can have monolithic characteristics. In many cases, modularity in a software application's design is desirable and thus developers may often seek to decompose monolithic applications into more modular “microservices” or other subunits when possible. A software modernization system includes a software analysis service that obtains, for one or more software applications undergoing evaluation, a collection of application artifacts, application profiling metrics, and other application profile data.

Abstract: Disclosed are systems and methods for providing a hybrid mobile application. The method may include: receiving specification of at least one feature of a mobile application. The mobile application may be specific to a first programming platform. The method may further include generating the at least one feature based on the specification. The at least one feature may be written in a programming language specific to a second programming platform, and the second programming platform may be different from the first programming platform. The method may also include compiling a programming wrapper based on the at least one feature of the mobile application, combining the at least one feature and the programming wrapper into a programming component, packaging the programming component into the mobile application, and distributing the mobile application in a repository of the first programming platform.

Abstract: A method, computer program product, and computer system for obtaining an input for a build. An initial orchestration job scheduler object may be obtained based upon the input for the build. A directed acyclic graph (DAG) may be determined based upon, at least in part, a dependency engine preprocessing. The DAG may be stored in a format. An array of steps may be built based upon, at least in part, the object, wherein the DAG may be translated from the object into a format readable by an initial orchestration job scheduler to build the array of steps. The array of steps may be executed to perform the build.

Abstract: A method, system, and computer program product for implementing automated system capacity optimization is provided. The method includes retrieving from plug-in components running on a plurality of hardware and software sources, metrics data associated with the plug-in components. The metrics data is cross-referenced with respect to operational sizing recommendations for each plug-in component based on aggregated disparate sizing guidelines and resulting software code modules are generated. Software and hardware requirements for enabling target computing components are determined based on results of executing the software code modules and operational functionality of the target computing components are enabled in accordance with the software and hardware requirements.

Abstract: A computer-implemented method comprises receiving by a servers of a development platform, an upload of a trained ML model and configuration data from a tenant user, for use by a mobile enterprise application that is made available to one or more tenants of the development platform, the mobile enterprise application capable of invoking the trained ML model, wherein the configuration data defines an input data format and an output data format of the trained ML model. The server generates API based on the configuration data and downloading the API to the mobile enterprise application, wherein the generating the API is performed without using an API provided by the tenant user. The generated API is further configured to pass input in the input data format to the trained ML model and configured to receive output in the output data format from the trained ML model for further processing or display.

Abstract: A computer-implemented schema-independent method of modeling data from diverse sources is described. A server transmits to a client computer a blueprint for visualizing and interacting with data, wherein the blueprint defines an application, for visualizing and interacting with data. The application may operate on the client computer within a web browser and may include program code or scripts that operate within the web browser and transmit data and commands to and from the server. In response to receiving a data fetch message from the application, the server receives data from a selected one of a plurality of domains. The server then transforms the received data into a semantic data format. The transformed data is then stored by the server as a first data set. The first data set can then be transmitted to the client computer for further processing and visualization by the application using the blueprint.