Abstract: One or more computer processors receive a pattern string comprising a pointer to a pattern search point and a string comprising a pointer to a search point; determine a plausible search point within the string for the pattern character; execute a search string (SRST) instruction with the determined search point and the pattern character; compute a pattern offset comprising a difference between a first occurrence of the determined pattern character located within the pattern string but not in the correct position and a current pattern character position; execute a subsequent SRST instruction with the current pattern character position and the computed offset set as a new search point; and responsive to identifying all pattern characters in the correct position within the string based on the executed subsequent SRST instruction, transmit memory address associated with a substring comprised of the string and corresponding pattern characters in the correct position.

Abstract: Methods, systems, and computer program products for constraints-based refactoring of monolith applications through attributed graph embeddings are provided herein.

Abstract: Systems and methods for implementing a build-time, automatic, exporter configuration rule generator that removes the need for manual definition of exporter configurations are described. A processing device may perform a scan of source code of an application to identify one or more classes of the application, each of the one or more classes enabling an exporter to access metrics generated by the class. For each of the one or more classes, the processing device may analyze source code of the class with a set of templates and heuristics to generate a set of configuration rules for the class. The processing device may then generate an exporter configuration for the exporter based on the set of configuration rules for each of the one or more classes.

Abstract: For each continuous integration and continuous delivery/deployment (CI/CD) pipeline of a plurality of CI/CD pipelines created for a project, a data structure reflecting an execution configuration of the respective CI/CD pipeline is created. A request to submit a code change to the project is received. Among the plurality of CI/CD pipelines, at least one CI/CD pipeline having the data structure that matches the code change to the project is identified. The code change to the project on the at least one identified CI/CD pipelines is executed.

Abstract: A firmware update system includes firmware storage device(s), an operating system engine coupled to the firmware storage device(s), and a remote access controller device coupled to the firmware storage device(s) and the operating system engine. The remote access controller device receives a single out-of-band firmware update command and, in response, performs a firmware storage device unlock operation to unlock the firmware storage device(s), transmits a firmware update package including a firmware update utility and a firmware update image to the operating system engine to cause the operating system engine to utilize the firmware update utility to update firmware stored in the firmware storage device(s) that was unlocked with the firmware update image and, subsequent to the operating system engine updating the firmware stored in the at least one firmware storage device that was unlocked, performs a firmware storage device lock operation to lock the firmware storage device(s).

Abstract: A method implemented by a data processing system including: accessing the container image that includes the first application and a second application; determining, by the data processing system, the number of parallel executions of the given module of the first application; for the given module, generating a plurality of instances of the container image in accordance with the number of parallel executions determined, for each instance, configuring that instance to execute the given module of the first application; causing each of the plurality of configured instances to execute on one or more of the host systems; and for at least one of the plurality of configured instances, causing, by the second application of that configured instance, communication between the data processing system and the one or more of the host systems executing that configured instance.

Abstract: Systems and methods for automatic validation of software components comparing source code and feature documentation are provided herein. An exemplary method includes assessing functional validation of software components by comparing the claimed features of software components against the features extracted from their source code. To prevent the issue of having to try unverified software components the present disclosure provides a solution that uses machine learning to extract claimed features of a software component and its actual features that are implemented in its source code. Then, for evaluating the software components, the disclosed solution compares the claimed features of software components against the features extracted from their source code to give a validated score to the developer so that the developer can easily decide on choosing the validated software.

Abstract: Implementing an application for a data processing engine (DPE) array can include detecting, using computer hardware, a component of a hardware library package instantiated by an application. The application is specified in source code and is configured to execute on a DPE array. An instance of the component is extracted from the application. The extracted instance specifies values of parameters for the instance of the component. The instance can be partitioned by generating program code defining one or more kernels corresponding to the instance of the component. The partitioning is based on a defined performance metric of the component and a defined performance requirement of the application. The application is transformed by replacing the instance of the component with the program code generated by the partitioning. The application, as transformed, is compiled into program code executable by the DPE array.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for container-based server environments. In some implementations, a server environment is provided using a plurality of containers that provide instances of different software modules. The plurality of containers includes a first container running a first software image of a particular software module. Various operations can be performed in response to determining that an updated software image is available for the particular software module. For example, execution is started for a second container that provides an instance of the updated software image. Incoming requests are to the second container while continuing to process, using the first container, one or more requests that were received before starting execution of the second container. In response to determining that a level of activity of the first container is below a threshold, the execution of the first container is stopped.

Abstract: A block frequency of a block in an irreducible loop in computer code is statically determined. The statically determining includes splitting an incoming block mass among multiple loop headers of the irreducible loop to provide an initial mass for the block. A bottom-up traversal and a top-down traversal of a plurality of loops of the computer code including the irreducible loop are iteratively performed to update a mass of the block. The iteratively performing commences with propagating the initial mass of the block to one or more blocks of one or more loops of the plurality of loops and continues with propagating and updating masses of select blocks of the plurality of loops until a predefined point is reached providing a resulting mass for the block. The block frequency of the block is determined using the resulting mass and is to be used in processing associated with the computer code.

Abstract: An API reader reads a system application's API specification file and creates a root.yml file containing key:value pairs, in which the keys are objects, and the values are staging_object.yml files. Each staging_object.yml file includes a set of entries, with each entry including a REST operation, a REST endpoint, and a description of the operation to be performed using that entry. An intelligent API converter creates structured object.yml files based on corresponding unstructured staging_object.yml files, and replaces the staging_object.yml files of the root.yml file with the newly created object.yml files. Each object.yml file includes a plurality of entries, corresponding to the entries of the respective staging_object.yml file. Each entry of the object.yml file includes an OPERATION, a JSON payload, and a VALIDATION section. An API builder uses the root.yml file to build a REST API for the system under test which is used to automate testing of the application.

Abstract: Systems and methods for generating dynamically updated metadata using real-time artificial intelligence models. For example, the system may receive a first metadata tag requirement for first metadata of a first media asset. The system may determine a first metadata field for the first metadata based on the first metadata tag requirement. The system may determine a first content population function for the first metadata field. The system may generate the first metadata with the first content population function. The system may generate the first media asset with the first metadata.

Abstract: This disclosure relates to building and finalizing an operating system (OS) image package in a way that allows for flexibility and customization of OS images while preventing certain runtime modifications after deployment of the OS image package on one or more target devices (e.g., embedded devices). For example, the systems described herein can build an OS image package based on information from an OS manifest that provides a declarative summary of a target OS. The systems described herein can further finalize the OS image package by performing one or more actions on the OS image package that prevent an end-user from performing various runtime modifications to the target OS after deployment of the OS image package. This finalization process provides an improved pipeline for implementing OS updates while providing safeguards against a variety of security risks associated with deploying OS image packages on a large scale.

Abstract: A machine learning model is trained to translate source code from one or more programming languages into a common programming language. The machine learning model translates source code from the other languages into the common programming language. A language embedder generates a vector for each function in the source code, all of which is now in the common programming language. A user provides a text search query which is converted by a language embedder to a vector. Based on the vector of the text search query and the vectors for the source code, search results are generated and presented in a user interface. Additional machine learning models may be trained and used to measure function complexity, test coverage, documentation quantity and complexity, or any suitable combination thereof. These measures may be used to determine which search results to present, an order in which to present search results, or both.

Abstract: A computer-implemented method is provided for data augmentation. The method includes receiving a set of different base models already pretrained and a set of different test cases. The method further includes collecting a plurality of prediction results of the set of different test cases from the set of different base models. The method also includes identifying a test case as a candidate for the data augmentation based on a number of models in the set of different base models which fail to solve the test case. The method additionally includes augmenting, by a processor device, the identified test case with additional data to form an augmented training dataset. The method further includes retraining at least some of the different base models with the augmented training dataset.

Abstract: An analysis of software stored and executing on one or more assets in an enterprise includes determining a hierarchy of nodes in the software and among the assets and analyzing dependencies among those nodes and assets through a static analysis of the software as it is stored as well as through a dynamic analysis of the software as it executes.

Abstract: Generally described, the present application relates to providing a container orchestration service (“service”) that can automatically detect and terminate a failed deployment and automatically roll back to a previous healthy deployment. For example, the service may receive a request to deploy a new user code onto one or more compute instances usable to execute the new user code, where the new user code is an updated version of an old user code to be replaced by the new user code. The service may then attempt to execute a plurality of instances of the new user code on the one or more compute instances, determine, prior to replacing all instances of the old user code to be replaced by the plurality of instances of the new user code, that the deployment of the new user code has satisfied a failed deployment condition, and terminate the deployment of the new user code.

Abstract: Mutation testing can indicate whether mutants of a software application, created by intentionally altering source code of the software application, are successfully “killed” by test cases executed against the mutants. Mutation testing can be performed via parallel threads by, within each parallel thread, modifying individual source code class files and recompiling the modified class files to generate and test mutants. Individual mutation test results produced within each of the parallel threads can be aggregated to generate an aggregated test result report that indicates overall testing metrics associated with the mutation testing across the parallel threads.

Abstract: Database systems and methods are provided for visual design and customization of processes for web applications. A method involves identifying a plurality of configured actions added to an aggregate action component region on a graphical user interface (GUI) display, automatically generating configured code for each of the configured actions in accordance with a respective user configuration of the respective configured action, identifying a user configuration associated with the aggregate action component, automatically generating aggregate action component code configurable to cause a browser application to initiate the configured code for each of the configured actions in parallel in accordance with the user configuration, and automatically generating process flow code including a reference to the aggregate action component code in accordance with a sequence defined for a web page.

Abstract: A method and a system determine a technological layer in which a module of a Manufacturing Operations Management (MOM) application is to be deployed. The specific MOM application has two or more modules that are separately deployable in at least two technological layers. For the specific MOM application, a set of characteristic parameters is defined that characterize business, process and information technology characteristics of the specific MOM application relevant for technological layer computation purposes. For each given module, there is defined a layer-deploying function, having as input a subset of the characteristic parameters and having as output a range value determining the technological layer to deploy the module at configuration time. For at least one of the given modules, there is determined the corresponding deploying technological layer by applying its corresponding layer-deploying function.