Abstract: Disclosed are systems and methods for managing software applications. The system receives, via a graphical user interface, a request to generate a chain application with a sequence of execution comprising a first application and a second application. In response to determining that an output type of the first application is not compatible with an input type of the second application, the system updates, without further user input, the sequence of execution such that the second application precedes the first application. The system generates the chain application configured to execute the first application and the second application in the updated sequence of execution.

Abstract: A method includes receiving a text description of a system capability request, and converting the text description into a normalized description of the system capability request. A repository is then queried, based on the normalized description and using a search algorithm, to identify multiple candidate application software units (ASUs). The candidate ASUs are displayed to a user for selection. The user-selected ASU is then deployed, either locally or to at least one remote compute device, in response to receiving the user selection. Deployment can include the user-selected candidate ASU being integrated into a local or remote software package, thus defining a modified software package that is configured to provide the system capability.

Abstract: Systems and methods for testing software such as webservices and APIs using behavior-driven development (BDD) language are disclosed. Software such as, for example, an Application Programming Interface (API) or webserver is tested using a BDD expression such as, for example, a Gherkin. The Gherkin may be converted into machine-executable code for the test. The machine-executable code may be executed if the software is available. A response output generated by the software may be validated based on validation information of input data. A report based on the validation may be generated.

Abstract: Methods and systems to provide enablement information by implementing a plug-in application by: executing the plug-in application in a course of application development of the software package connected to a cloud-based computing system; parsing a set of applications contained in the software package to generate a set of metadata data that includes an entire set of metadata for the software package; receiving a set of rules via the cloud-based computing system; defining a set of definitions for each rule in the set of rules to enable a comparison of each rule to the set of metadata to extract one or more features of each application contained in the software package; generating an inventory set of one or more features based on rule definitions for the software package; and generating a recommendation related to a feature of the inventory set of features in each application of the software package.

Abstract: Simulated software conversion offers advance warning of possible issues that may arise during a full conversion process. An engine interposed between a planner and an upgrade module interacts with the planner and an upgrade module to simulate compliance checks, and to reference a data model to simulate conversion tasks (e.g., simplification items, add-ons, custom code). The engine instructs the planner to continue (rather than halt/suspend) iterative interrogation of the existing production landscape to create an un-truncated stack.xml file, even when the planner encounters an unknown/unfamiliar software element. The upgrade module expects an incoming modified stack.xml file as input, that modified stack.xml file including additional information (such as a flag) referenced by the upgrade module to perform conversion compliance checks and other conversion tasks. The engine enriches the full stack.xml file received from the planner, creating the modified stack.

Abstract: In an embodiment, the present invention is directed to a processor including a decode logic to receive a multi-dimensional loop counter update instruction and to decode the multi-dimensional loop counter update instruction into at least one decoded instruction, and an execution logic to execute the at least one decoded instruction to update at least one loop counter value of a first operand associated with the multi-dimensional loop counter update instruction by a first amount. Methods to collapse loops using such instructions are also disclosed. Other embodiments are described and claimed.

Abstract: The current document is directed to a safe-operation-constrained reinforcement-learning-based application manager that can be deployed in various different computational environments, without extensive manual modification and interface development, to manage the computational environments with respect to one or more reward-specified goals. Control actions undertaken by the safe-operation-constrained reinforcement-learning-based application manager are constrained, by stored action filters, to constrain state/action-space exploration by the safe-operation-constrained reinforcement-learning-based application manager to safe actions and thus prevent deleterious impact to the managed computational environment.

Abstract: The current document is directed to transfer of training received by a first automated reinforcement-learning-based application manager while controlling a first application is transferred to a second automated reinforcement-learning-based application manager which controls a second application different from the first application. Transferable training provides a basis for automated generation of applications from application components. Transferable training is obtained from composition of applications from application components and composition of reinforcement-learning-based-control-and-learning constructs from reinforcement-learning-based-control-and-learning constructs of application components.

Abstract: A firmware update method for a smart charging device is disclosed. First, firmware of a first board is updated, and the first board then sets work flags to second, third board and fourth boards. The first board queries a firmware version of the second board, and then presets the work flag of a firmware version as false. When the firmware version of the second board is older, the first board sets the work flag as true, and updates the firmware of the second board, and sets the work flag as false. The first board again queries whether the work flag is set as true, when the firmware versions of the second and first boards are the same, the work flag is set as false. According to the above procedures, the firmware of the third and fourth boards is updated, so as to completely update firmware of all boards.

Abstract: Systems and methods can implement a review process to evaluate changes to target code as part of development cycles for a continuous integration, continuous deployment pipeline for software-based products. The system can aggregate data and determine if the target code has been modified preliminarily and then intelligently determine where further review is needed before the changes are permanently implemented. To do this, a changeset including the preliminarily changed target code can be obtained from the aggregated data. The changeset can be tested with a prediction model based on feature data that characterizes aspects of a coding process carried out to generate the preliminary modification. The prediction model can provide an activation recommendation for the preliminary modification based on a plurality of risk factors determined from the testing. The prediction model can be trained, continuously, with training data that includes a plurality of data artifacts resulting from a code build processes.

Abstract: Described herein is a computer implemented method. The method comprises receiving, by an issue tracking system, a deployment update from a deployment system which includes deployment information in respect of one or more issues maintained by the issue tracking system. The method further comprises associating one or more issues maintained by the issue tracking system with deployment information by identifying the one or more issues to which the deployment information in the deployment update relates, extracting the deployment information from the deployment update, and associating the deployment information with each of the identified issues.

Abstract: A processing device can establish a machine learning model to produce software dependency recommendations. The model can be periodically retrained to update its knowledge of available dependencies. The software dependencies can be incorporated into software by developers who receive the selection or automatically by an intelligent software development platform. A processing device can train the model by assembling sparse user data based on feedback corresponding to software dependencies to produce a vector of preferences for each user. The processing device can also generate a latent vector of attributes for each software dependency. The processing device can then apply matrix factorization to the vectors to produce a behavior matrix that is used to train the machine learning model.

Abstract: A computer-implemented method of identifying federations of manufacturing apps using House of Quality (HoQ) analysis includes receiving user request information comprising a plurality of desired functions and an importance value for each of the plurality of desired functions and generating a correlation matrix between the plurality of apps, wherein each element of the correlation matrix indicates a degree of correlation between a pair of apps. A relationship matrix is generated which comprises numerical values indicating relationships between a plurality of apps and the plurality of desired functions, wherein each column of relationship matrix is associated with an app and each row is associated with a desired function. Next, a weighted matrix is created by multiplying each row in the relationship matrix by the importance value corresponding to the desired function associated with the row.

Abstract: This application discloses a virtual machine hot migration method performed by a virtual machine hot migration apparatus to a cloud computing system including a plurality of hosts, each host including a plurality of virtual machines. The apparatus obtains a load of each host, determines a host whose load exceeds a preset threshold as a source host, determines a to-be-hot-migrated target virtual machine in the source host; and controls the target virtual machine to be hot-migrated from the source host to a target host. According to the solutions provided in the embodiments of this application, when a load of a host is excessively high, a redundantly configured virtual machine on the host is hot-migrated to another host, thereby improving the resource utilization rate of the host when use by a user is ensured.

Abstract: Systems and techniques are disclosed for an enhanced automated protocol for secure application testing. An example method includes receiving, via a first component of a system and from a user device, selection of testing information, the testing information including a test device to perform one or more selected test suites, and the test suites being associated with an application. Test suite information is generated via a second component of the system based on the selected test suites, with the first component instructing the second component to generate the testing information according to the particular protocol. The test suite information is provided via the second component to the test device, with the test suite information being provided in response to polling from the test device. Test results are received via the second component, with the test results being routed by the second component to the first component for presentation via the user device.

Abstract: A device may receive a request to configure an environment for a target enterprise resource planning (ERP) system. The device may identify a system image of an ERP package. The device may provide, to other devices that are to support the environment, the system image and installation information to cause the other devices to use the system image to host the ERP package. The device may establish paths that permit data transmission between the target ERP system and a source ERP system. The device may identify development-operations (Dev-Ops) and test tools to be configured within the environment. The device may provision, using the one or more paths, the environment with the set of Dev-Ops and test tools. The device may provide instructions to the other devices to cause the other devices to deploy the environment of the target ERP system and to permit user devices to access the environment.

Abstract: Embodiments of the invention are directed to classifying requests associated with personal data at or before a point of entry to a trusted computing network. The invention provides for determining whether a request associated with personal data requires classification (for example, whether the request is impacted by regulations or other requirements necessitating classification/categorization). The determination may be based on what entity is requesting the data, the origin of the request, whose data is being requested, the type of action associated with the request and/or the data elements associated with the request. In addition, once the request has been determined to require classification the specific classification is determined and assigned to the request. The classification may be determined based on the rules associated with the regulation or other requirement(s) necessitating the classification/categorization.

Abstract: The current document is directed to automated reinforcement-learning-based application managers that that are trained using adversarial training. During adversarial training, potentially disadvantageous next actions are selected for issuance by an automated reinforcement-learning-based application manager at a lower frequency than selection of next actions, according to a policy that is learned to provide optimal or near-optimal control over a computing environment that includes one or more applications controlled by the automated reinforcement-learning-based application manager.

Abstract: A method, computer program product, and system includes a processor(s) of a host obtaining, from a client, via a communication connection over a network, a request to commit a modified version of program source code to a repository administered by the host. The processor(s) identify formatting in the modified version implemented by an editor executing on the client and remove the formatting. The processor(s) transform the modified version into a first storage structure that includes content of the modified version without the identified formatting. The processor(s) identify one or more differences between the first storage structure representing the modified version and a second storage structure (an unmodified version of the program source code stored in the repository). The processor(s) store the one or more differences in the repository.

Abstract: The current document is directed to automated reinforcement-learning-based application managers that use local agents. Local agents provide finer-granularity monitoring of an application or application subcomponents and provide continued application management in the event of interruption of network traffic between an automated reinforcement-learning-based application manager and the application or application subcomponents managed by the automated reinforcement-learning-based application manager.