Abstract: A system to support validation and debugging of compiled low-level instructions for a machine learning (ML) network model on an ML-specific hardware. A compiler identifies well-defined boundaries in the ML network model based on primitives used to generate low-level instructions for the hardware. The ML network model is partitioned into units/layers/sub-graphs based on the plurality of well-defined boundaries. The compiler then generates an internal representation for each of the units wherein the internal representation is mapped to components in the hardware. Each of the units is compiled into a first set to be executed on the ML-specific hardware and a second set to be executed on a second computing device. The output results from executing the two sets of low-level instructions are compared to validate the first set of low-level instructions. If the outputs do not match fully, the first set of low-level instructions is debugged and recompiled.

Abstract: A system including at least one processor programmed to translate a policy into policy code, wherein: the policy is provided in a policy language; the policy code is in a programming language that is different from the policy language; and the policy includes a statement that maps an entity name to one or more metadata symbols to be associated with an entity in a target system against which the policy is to be enforced.

Abstract: Improved compilers recognize interception declarations in source code, and emit code that replaces invocations of specified artifacts with invocations of specified interceptors instead. Source generators proactively modify program behavior in arbitrary desired ways without introducing hidden security violations and without requiring edits by the program's developers. Interception declarations are visible in source code and development tools. In some cases, different invocations of a particular method at respective locations are intercepted by different replacement methods. Replacement methods have identical signatures, or are otherwise compatible. Some interceptors specify optional parameters. Method calls, field accesses, and property calls may be intercepted. Work to modify program behavior is moved in the program lifecycle from runtime to compile time, thus improving runtime performance and eliminating JIT compilation security risks.

Abstract: Examples of performing an out-of-band firmware update of a server computing device are described. In an example, a first disk image is mounted onto a server computing device. The first disk image comprises a bootable firmware and is mounted in response to a mount command received through an out-of-band communication service. In another example, a second disk image is also mounted onto the server computing device. The second disk image is also mounted in response to another mount command received through the out-of-band communication service and is to provide a read-writable container, when mounted. Thereafter, a booting process of the server computing device may be initiated based on mounted first image to update the firmware of the server computing device. Information related to the update of the firmware is store in the read-writable container.

Abstract: The disclosure invention provides a method for executing a program compiled for a source architecture on a machine having a different target architecture, a non-transitory computer readable medium configured to store instructions for performing such a method, and a system for performing such a method.

Abstract: The present disclosure relates to an information processing device, an information processing method, and a program capable of suppressing labor and cost for generating a unique identifier. According to the present disclosure, provided is an information processing device provided with software in which first identification information having uniqueness is registered, and an application that obtains the first identification information from the software, converts the first identification information into second identification information having uniqueness for communication, and registers the second identification information in the software. With this configuration, it is possible to suppress labor and cost for generating a unique identifier.

Abstract: The present invention generally relates to system, method and graphical user interface for executing one or more tasks in dynamic data driven enterprise application. The invention includes creation of rules on a rule creation interface by one or more syntax from a rule creation syntax data library. The invention provides machine learning models driven rule engine for executing the tasks.

Abstract: A microcode (uCode) hot-upgrade method for bare metal cloud deployment and associated apparatus. The uCode hot-upgrade method applies a uCode patch to a firmware storage device (e.g., BIOS SPI flash) through an out-of-band controller (e.g., baseboard management controller (BMC)). In conjunction with receiving a uCode patch, a uCode upgrade interrupt service is triggered to upgrade uCode for one or more CPUs in a bare-metal cloud platform during runtime of a tenant host operating system (OS) using an out-of-bound process. This innovation enables cloud service providers to deploy uCode hot-patches to bare metal servers for persistent storage and live-patch without touching the tenant operating system environment.

Abstract: Generation of an executable file derived from a parent executable file having ranges of physical addresses referencing a binary code of at least one core feature (CR), a binary code of a set of native features (F), bytecodes of a set of java features (Pkg), by selecting at least one native feature from the set of native features to be removed, defining the range of physical addresses where the binary code of the selected native feature is stored, selecting at least one java feature from the set of java features to be relocated, and relocating the bytecodes of said at least one selected java feature in the defined range of physical addresses.

Abstract: A device management system includes an automatic updater that automatically generates an automatic F/W update task in accordance with an automatic F/W update plan which is a setting for automatically generating the automatic F/W update task as a task for updating firmware of an image forming apparatus. The automatic F/W update plan includes specifying of firmware for update and a mode in which the update is fully executed on all electronic apparatuses of a target of the software update. The automatic updater automatically generates the automatic F/W update task in accordance with the automatic F/W update plan at a specific timing in a repeat manner.

Abstract: Aspects of managing inventory for data transport connections within a virtualized computing environment are described. A virtualized management system managing a cluster of host devices obtains a data transport capacity parameter and an aggregate memory consumption value from respective host devices. The virtualized management system further identifies an update status associated with each of the host devices. In response to receiving a data transport connection request, the virtualized management system selects a host from the cluster of hosts to satisfy the data transport connection request based at least in part on the upgrade status, data transport capacity parameter and aggregate memory consumption value.

Abstract: Systems and methods for rules-based automated penetration testing and regression to certify release candidates against known patterns that inject vulnerabilities are disclosed.

Abstract: A method for providing a federated, multi-product data mesh via automated code generation is disclosed. The method includes receiving, via an application programming interface, a data model, the data model including model artifacts that define data governance for a data product; automatically generating source code for software components based on the data model, the software components corresponding to data mesh components for the data product; integrating data product customizations into the software components, the data product customizations including business logics and testing configurations; initiating an automated continuous integration and continuous delivery pipeline to generate a service that corresponds to the data product based on the integrated software components; and deploying the generated service in a namespace that corresponds to the data product.

Abstract: An apparatus comprises a processing device configured to obtain testing logs generated by executing test cases on information technology assets of an information technology infrastructure, to parse the testing logs to generate a set of log event templates for testing actions performed during execution of the test cases on the information technology assets of the information technology infrastructure, to generate vector representations of the test cases utilizing the generated set of log event templates, and to perform, utilizing one or more machine learning-based hierarchical clustering algorithms that take as input the generated vector representations of the test cases, hierarchical clustering of the plurality of test cases. The processing device is also configured to generate, based at least in part on the hierarchical clustering results, testing plans for a given information technology asset of the information technology infrastructure.

Abstract: In some implementations, a device may generate, based at least in part on a first set of inputs, a serverless software development environment associated with a set of cloud resources. The device may generate, based at least in part on a first machine learning model, a technology stack recommendation having a set of associated tools for performing a software development task. The device may instantiate the selected technology stack in the serverless software development environment and generate a set of applications based at least in part on executing the set of tools. The device may deploy the set of applications in one or more serverless application environments. The device may use machine learning to observe deployed applications, detect hidden anomalies, and perform root-cause analysis, thereby providing a lean and sustainable serverless environment.

Abstract: According to one aspect, a method for compiling by a compilation tool a source code into a computer-executable code comprises receiving the source code as input of the compilation tool, translating the source code into an object code comprising machine instructions executable by a processor, then introducing, between machine instructions of the object code, additional instructions selected from illegal instructions and no-operation instructions so as to obtain the executable code, then delivering the executable code as output of the compilation tool.

Abstract: A development assistance device includes: multiple conversion units each converting either an inputted signal value or inputted meta information into either a signal value or meta information, and outputting either the signal value after conversion or the meta information after conversion as output information; a pipeline unit causing, on the basis of pipeline information showing a relationship of mutual connections between the multiple conversion units, the multiple conversion units to sequentially perform the corresponding converting processes; an inference unit making an inference by using the output information outputted by a final conversion unit which the pipeline unit causes, on the basis of the pipeline information, to finally perform the converting process, out of the multiple conversion units; and an image generation unit generating image information for visualizing the connection relationship shown by the pipeline information, and a relationship of a connection between the final conversion unit and

Abstract: In a dynamic memory allocator, a method of allocating memory to a process, the method comprising executing on a processor the steps of: creating one or more arenas within the memory, each arena comprising one or more memory blocks and each arena having an n-byte aligned arena address; upon receiving a memory request from the process, returning a pointer to the process, the pointer having as its value an address of a memory block selected from one of the arenas; upon determining that the memory block is no longer needed by the process, retrieving the address of said memory block from the pointer and releasing the memory block; and, upon a new arena being created, shifting forward the n-byte aligned address of said new arena according to a stored variable such that each memory block of said new arena is also shifted by the stored variable, the stored variable having n bytes and the stored variable having a random value.

Abstract: This application provides a plug-in implementation system and method. The system includes a plug-in module and a terminal software module. When the terminal software module does not include a service implementation of a first plug-in interface, the plug-in module may load a default implementation of the first plug-in interface to invoke the first plug-in interface. In this way, a plug-in may be extended to extend a service function of a terminal. In addition, when the plug-in interface is inconsistent with a plug-in function, the default implementation of the plug-in interface is implemented by using the plug-in module, so that an open-source software module can run normally, to ensure normal running of an electronic device as much as possible. Therefore, the open-source software module no longer depends on the terminal software module, and the terminal software module can be decoupled from the open-source software module.

Abstract: According to an aspect of an embodiment, operations include receiving a set of NL descriptors and a corresponding set of PL codes. The operations further include determining a first vector associated with each NL descriptor and a second vector associated with each PL code, using language models. The operations further include determining a number of a set of semantic code classes to cluster the set of PL codes into the set of semantic code classes, based on the number, the first vector, and the second vector. The operations further include training a multi-class classifier model to predict a semantic code class, from the set of semantic code classes, corresponding to an input NL descriptor. The operations further include selecting an intra-class predictor model based on the predicted semantic code class. The operations further include training the intra-class predictor model to predict a PL code corresponding to the input NL descriptor.