Abstract: In one aspect, a device includes at least one processor and storage accessible to the at least one processor. The storage includes instructions executable by the at least one processor to execute a software development kit (SDK) to interface between a two-dimensional (2D) application (app) and a three-dimensional (3D) app. The instructions are also executable to identify, via the SDK, a callback from the 2D app. The callback indicates a uniform resource locator (URL) associated with a 3D model. The instructions are further executable to execute the SDK to indicate, to the 3D app, the 3D model for rendering in 3D space.

Abstract: A method and system is disclosed for migrating an application on a source computer system, which may be a legacy application running on an out-of-date operating system, to a container host running on a target computer system. The system includes software products which analyse the source system to identify application components, and which provision containers corresponding to the identified components.

Abstract: Novel tools and techniques are provided for implementing object-oriented infrastructure-as-code platform (“OOIACP”) and its functionalities. In various embodiments, when a request to process one or more lifecycle events is received, a computing system may perform: selecting and scaling across a plurality of OOIACP instances; and causing the selected plurality of OOIACP instances to process the one or more lifecycle events. In some cases, each OOIACP instance may include an infrastructure-as-code (“IAC”) command line that instantiates component infrastructure among a plurality of component infrastructure to process at least one lifecycle event among the one or more lifecycle events concurrently and independently of other OOIACP instances. In some instances, the first plurality of OOIACP instances may be located within an environment in which the plurality of component infrastructure is located.

Abstract: Embodiments of this application provide an operating system upgrade method applied to an electronic device, and the method includes: obtaining a first upgrade installation package, where the first upgrade installation package includes a first upgrade file; storing the first upgrade file in a user data partition; restarting the electronic device, and loading data in a basic partition and a second static partition; loading data in another sub-partition other than a first sub-partition in a dynamic partition, and loading the first upgrade file; and merging the first upgrade file into the first sub-partition of the dynamic partition. The method further includes: synchronizing data in a first static partition to the second static partition. According to the method in embodiments of this application, independent upgrade may be performed on a customized sub-partition in a dynamic partition, to upgrade a customized operating system.

Abstract: Described herein are machine learning methods and systems for application programming Interface (API) management. One or more machine learning-based models, such as a neural network, may be trained to provide a prediction(s) that an API request is likely to succeed (e.g., not cause the API to crash) or to fail (e.g., cause the API to crash, freeze, etc.). The one or more machine learning-based models may be trained using historical API requests that were successful and historical API requests that are not successful. Various aspects of the API requests, as well as system properties associated with the machine(s) that executes/processes the historical API requests, may be used as well when training the one or more machine learning-based models.

Abstract: A computer-implemented method is provided for managing Garbage Collection (GC) safepoints. The method includes determining whether a GC safepoint for a target native method can be removed by checking a heap occupancy ratio prior to executing the target native method. The method further includes removing the GC safepoint responsive to the heap occupancy ratio prior to executing the target native method being less than a threshold occupancy amount percentage. The method also includes determining whether the GC safepoint for the target native method can be removed by checking a most recent GC pause time. The method additionally includes removing the GC safepoint responsive to the most recent GC pause time being shorter by a threshold pause time amount percentage than an execution time of the target native method.

Abstract: A method for patch management is described. The method includes downloading a patch that is incompatible with a patch management system. The method also includes creating an archive that is executable by the patch management system. The archive includes the incompatible patch. The method further includes sending the archive to the patch management system.

Abstract: In some examples, artificial intelligence-based intelligent programming assistance may include ascertaining, for a software program that is to be completed, code for the program, and identifying, based on an analysis of error message-based contextual information associated with the ascertained code, an error in the ascertained code. A resolution to the identified error may be generated, and the code may be modified to resolve the identified error, Based on an analysis of problem description-based contextual information associated with the ascertained code, a next token associated with the ascertained code may be generated, and used to generate further code for the program. A performance of a user may be analyzed with respect to generation of the code for the program to generate feedback for the user. A query associated with the program may be ascertained from the user, and classified by utilizing an ontology to generate a response to the query.

Abstract: Embodiments relate to an intelligent computer platform to build a federated learning framework including creating a hierarchy of machine learning models (MLMs). The hierarchy of MLMs has a primary MLM in a primary layer. Training the primary MLM includes capturing contributing model updates across at least one communication channel. A secondary MLM is created and logically positioned in a secondary layer of the hierarchy. The secondary MLM is operatively coupled to the primary MLM across the at least one communication channel. The created secondary MLM is initialized, including cloning weights and framework of the primary MLM into the secondary MLM, and populated with secondary data. The populated data has model updates local to the created secondary MLM. The secondary MLM is logically stored local to the secondary layer, and limits access to the secondary MLM to the secondary layer.

Abstract: Web-based robotic process automation (RPA) designer systems that allow RPA developers to design and implement web serverless automations, user interface (UI) automations, and other automations are disclosed. Such web-based RPA designer systems may allow a developer to sign in through the cloud and obtain a list of template projects, developer-designed projects, services, activities, etc. Thus, RPA development may be centralized and cloud-based, reducing the local processing and memory requirements on a user's computing system and centralizing RPA designer functionality, enabling better compliance. Automations generated by the web-based RPA designer systems may be deployed and executed in virtual machines (VMs), containers, or operating system sessions.

Abstract: Novel tools and techniques are provided for implementing object-oriented infrastructure-as-code platform (“OOIACP”) and its functionalities. In various embodiments, an OOIACP may receive a request to perform a function from a requesting device. The OOIACP includes a declarative configuration language (“DCL”)-based infrastructure-as-code (“IAC”) software tool that provides structure and data functionalities and a wrapper tool that provides algorithm and sequence functionalities to the IAC software tool to convert the IAC software tool into an object-oriented programming (“OOP”)-based IAC system. The OOIACP uses a run command to perform the requested function, by identifying classes within a class hierarchy associated with the requested function, and initiating a set of procedures in each identified class. Each class and subclass within the class hierarchy has one or more predefined class behaviors, and each subclass inherits class behaviors of classes to which it belongs and of any intermediate subclasses.

Abstract: Systems and methods for facilitating updates to software programs via machine-learning techniques are disclosed. In an example, an application generates a feature vector from a textual description of a software defect by applying a topic model to the textual description. The application uses the feature vector and one or more machine-learning models configured to predict classifications and sub-classifications of the textual description. The application integrates the classifications and the sub-classifications into a final classification of the textual description that indicates a software component responsible for causing the software defect. The final classification is usable for correcting the software defect.

Abstract: Provided herein are systems and method for providing routing of complex dynamically updated website applications using micro front ends (MFEs). The MFEs can be instantiated in a nested fashion. Each MFE can be agnostic to other levels of the website application structure that are not directly adjacent to the MFE in the hierarchy of the nesting. Navigation events can be bubbled up to a shell application to retain top-level control of routing within the website application without requiring the shell application to have all levels of routing in the hierarchy.

Abstract: A compilation method includes obtaining a source program code. The source program code includes a first function in a first language code and a second function in a second language code. The first language code is a native language. The second language code is a non-native language. The method also includes generating a third language code based on the source program code. The third language code includes a third function, a fourth function and a fifth function. The third function is generated based on the first function. The fourth function is generated based on the second function. The fifth function is generated based on the first function and the second function. Executing the third function invokes the fourth function via the fifth function.

Abstract: A data processing apparatus is provided that includes storage circuitry to store a plurality of interconnected instructions. Analysis circuitry analyses the instructions to determine a degree of uniqueness of profile measurements of a control flow path fragments within the instructions.

Abstract: Various embodiments are provided for patching of workflows in a computing environment by one or more processors in a computing system. One or more patches may be extracted from a source workflow. The target workflow in a plurality of nodes may be statically or dynamically modified by applying the one or more patches to the target workflow. The one or more of the plurality of nodes may be added, removed, or modified in the target workflow while the target workflow is active according to applying the one or more patches.

Abstract: A method of compiling neural network code to executable instructions for execution by a computational acceleration system having a memory circuit and one or more acceleration circuits having a maps data buffer and a kernel data buffer is disclosed, such as for execution by an inference engine circuit architecture which includes a matrix-matrix (MM) accelerator circuit having multiple operating modes to provide a complete matrix multiplication. A representative compiling method includes generating a list of neural network layer model objects; fusing available functions and layers in the list; selecting a cooperative mode, an independent mode, or a combined cooperative and independent mode for execution; selecting a data movement mode and an ordering of computations which reduces usage of the memory circuit; generating an ordered sequence of load objects, compute objects, and store objects; and converting the ordered sequence of load objects, compute objects, and store objects into the executable instructions.

Abstract: Systems, devices, media, and methods are presented for determining performance metrics of client devices on a network using benchmark applications. Benchmark applications are distributed to client devices to produce performance metrics for the client devices. Performance metrics of the client devices received from the client devices are grouped to obtain performance metrics for different types of client devices.

Abstract: Systems and methods are provided herein for natively interpreting logic across disparate platforms. Rather than executing server calls that are computationally expensive, logic may be extracted into code segments that can be evaluated at run time by an interpreter. The interpreter is passed a set of evaluators, features, and contextual data, each of which is expressed in a domain specific language. An evaluator maps an identifier to a rule and describes one or more contextual data fields with which the rule is to be evaluated. A feature corresponds to a logical condition that identifies the evaluator and a return value that is returned if the condition is met. The interpreter identifies the evaluator from the feature being evaluated and evaluates its corresponding rule based on the contextual data provided to return a return value. One or more operations may be performed based on the return value provided.

Abstract: An anti-malware system monitors the emulation of a suspicious program in a sandbox environment. The anti-malware system determines that the suspicious program is attempting to access a restricted area of memory (e.g., an executable instruction in the restricted area). Rather than stop the emulation, the anti-malware system can temporarily pause the emulation of the suspicious program. During this pause, the anti-malware system can determine whether the suspicious program is containable within the sandbox environment. If the anti-malware system determines that the emulation of the executable instruction is safe (e.g., that the program is containable), the anti-malware system will resume emulation. If the anti-malware system determines that the emulation of the executable instruction is not safe, the anti-malware system may shut down emulation.