Abstract: Software of devices, such as medical devices or other constrained devices configured to implement specific functions, can use content files to determine text strings or other content values to present in association with user interface elements. Devices can receive relevant content files, such as new versions of previously-stored content files or new content files containing text in different languages, from a remote content file repository. The software of the devices can accordingly update content values presented in user interfaces based on newly received content files, without the software being re-coded, the software being restarted, or the devices rebooting.

Abstract: The present disclosure provides an interpreter of a reconfigurable cryptographic algorithm based on customized high-level C language, in the field of information security. The interpreter includes an input program of cryptographic algorithm customized language, a compilation optimization module, an intermediate file and data flow graph generation module, a mapping module and an array generation configuration code module. The disclosure provides an automatic mapping tool for the reconfigurable processor, which can take customized high-level C language as input, and the interpreter arranges and connects computing units like operators according to the input high-level C program, to complete the mapping of the whole computing function.

Abstract: A host computer is programmed to receive input specifying definitions of two or more stages, each of the stages representing an attribute of one or more end-user profiles that have undertaken one or more interactions, using computing devices associated with the end-user profiles, with one or more networked computers. For each stage, the user computer can interoperate with a graphical user interface comprising a virtual canvas, a palette comprising a plurality of different graphical icons each representing at least an entry condition and an activation order for digital presentation of information. Visual selection and dragging operations can move copies of an entry condition icon and an activation icon from the palette to the virtual canvas. An entry condition icon is defined using rules to match one or more subsets of the end-user profiles and one or more subsets of the interactions. An activation icon has order attributes order for the digital presentation of information.

Abstract: According to some implementations, while a proxy routes production traffic to a first application (app) version that runs in a plurality of container orchestration system (cos) pods having first app version containers, configuration information is received including an identification of a second app version container image for a second app version. The second app version is an updated version of the first app version. Cos pods having second app version containers are brought up based on the second app version container image identified in the configuration information. Test and/or warmup traffic is caused to be routed to the second app version containers. Responsive to an indication regarding the routing of the test and/or warmup traffic to the second app version, causing a transition to sending production traffic to the second app version containers instead of to the first app version.

Abstract: Techniques are provided for machine learning-based prediction of completion time of software code changes. One method comprises obtaining events related to software code changes; applying the events to a machine learning model that predicts a completion time of the software code changes, wherein the machine learning model is trained using (i) events for historical software code changes and (ii) a completion time for each historical software code change; and performing a remedial action based on the predicted completion time. The remedial action may comprise generating a notification, and/or adjusting an allocation of resources assigned to a completion of the software code changes. The software code changes can be monitored and a new event related to the software code changes can be applied to the machine learning model to obtain an updated predicted completion time for the changes to the software code.

Abstract: A UI service loading method is applied to a loading apparatus. One example method includes: receiving a loading request including a reuse path of a to-be-loaded UI service, where the loading request requests to load the to-be-loaded UI service; determining a dependency of the to-be-loaded UI service based on a dependency graph; and loading the to-be-loaded UI service and the dependency of the to-be-loaded UI service, where the reuse path of the to-be-loaded UI service indicates an access path of the to-be-loaded UI service, and the dependency graph indicates a dependency of at least one UI service in at least one UI service package, and indicates a UI service that references a UI service in the at least one UI service package as a dependency.

Abstract: Systems, methods, and devices facilitate generation of application programming interfaces. Systems include a computing platform implemented using a server system, the computing platform being configurable to cause monitoring application programming interface (API) traffic associated with a client service, storing a representation of the API traffic in a database system, the representation including at least an API call identifier and metadata, and generating one or more API models based, at least in part, on the representation of the API traffic, the one or more API models being configured to represent a plurality of API interactions associated with the client service. The computing platform is further configurable to cause generating one or more API objects based, at least in part, on the API models, the one or more API objects being one or more components of a client service API.

Abstract: Deferred formula computation executes software containing a set of programmed formulas, wherein the set includes a first programmed formula defined in an associated dependency graph to be dependent on a result of a second programmed formula. A method may encounter a reference to the first programmed formula during execution of the software, wherein the reference is associated with deferred formula computation request program code in the executing software to obtain a result of the first programmed formula; identify during execution of the software the second programmed formula based on traversal within the associated dependency graph of the first programmed formula; compute a result of the second programmed formula during execution of the software; compute the result of the first programmed formula during execution of the software, and return the computed result of the first programmed formula in association with the reference to the first programmed formula.

Abstract: The teachings of the present disclosure include data interaction methods, apparatus, and systems for an Artificial Intelligence (AI) inference device and an automation controller. An example method includes: S1: analyzing a topological structure of an AI model, and acquiring multiple nodes of the AI model and interconnections of the multiple nodes; S2: matching an output node of the AI model based on a user input, determining a format of an inference result based on the AI model, and mapping the format of the inference result to the automation controller; and S3: matching a communication protocol for performing data interaction by the AI inference device and the automation controller based on the user input.

Abstract: The disclosure relates to testing software for operating an autonomous vehicle. For instance, a first simulation may be run. The simulation may be run using the software to control a simulated vehicle and at least one agent. During the running of the first simulation, whether a particular type of interaction between the simulated vehicle and the at least one agent has occurred may be determined. In response to this determination, a second simulation may be run using the log data by replacing the at least one agent with a model agent that simulates a road user capable of responding to actions performed by the simulated vehicle. The second simulation may be used to determine in order to determine whether the software is able to complete the second simulation without the particular type of interaction between a second simulated vehicle and the model agent occurring.

Abstract: An example computer implemented method for generating an artificial intelligence (AI) model from a self-creating script coded in a programming language includes receiving an objective for the AI model and obtaining at least first action code corresponding to a first action, where the first action is associated with an action objective similar to the objective. The method further includes generating at least a second action code based on one of the first action code and a specification of the programming language and comparing a first outcome of the first action code and a second outcome of the second action code. The method further includes inserting one of the first action code and the second action code into the self-creating script based on the comparing the first outcome of the first action code and the second outcome of the second action code and executing the self-creating script including the one of the first action code and the second action code to satisfy the objective.

Abstract: Described techniques enable inter-environment communication between a first runtime environment and a second runtime environment of an operating system. A function requested by an application executing in the first runtime environment may require execution by a second application running in a virtual machine in the second runtime environment. An address mode (AMODE) of the virtual machine may be determined from among at least two AMODEs. The second runtime environment may be launched from the first runtime environment, and the virtual machine may be launched within the second runtime environment, using the AMODE. The function may then be executed using the second application.

Abstract: A method for obtaining coverage-guided fuzzing of software on a hardware target. The hardware target includes a breakpoint register, and is designed to stop an execution of the software prior to execution of an instruction of the software if the instruction is reached during the execution of the software; a memory address of the instruction is set in the breakpoint register. The method includes setting a first breakpoint prior to a first instruction of the software; executing or continuing a fuzzing iteration of the software; first checking whether the first breakpoint is reached while executing or continuing the fuzzing iteration; storing a piece of log information that includes that the first instruction in the fuzzing iteration has been reached, and optionally deleting the first breakpoint if the first check is positive. The coverage-guided fuzzing of the software includes the piece of log information.

Abstract: A bad change detector for operational features of digital platforms is described. Metric data from a website is acquired by the bad change detector while implementing a first version of an operational feature of the website and while implementing a second version of the operational feature. A bad change to the website is detected by measuring an inequality among values of a frequency distribution defined by a time series of the metric data. The operational feature is reverted to the first version, automatically and without user intervention, in response to detecting the bad change, thereby improving operation of computing devices that implement the website.

Abstract: A system and method for an AI-based Automated Software Application Development Platform which intelligently gathers requirements from a business analyst and generates a runnable software application from those requirements. The AI-based platform enables the business analyst with no technical knowledge to visually model their requirements rapidly without requiring any programming Using the abstract requirements architecture and the platform, the analyst creates requirements models for the application's business processes and business tasks for each of the processes including defining the supporting information needs. The system intelligently assists the user in defining the information needs for each of the business processes and their tasks. Once the requirements models are created by the analyst with the help of the platform, the platform automatically designs and creates an appropriate persistent canonical data model for the application from the defined information needs.

Abstract: Systems, apparatuses and methods may provide for technology that parses, at runtime, a deep learning graph in topological order to identify a plurality of nodes, marks a first set of nodes in the plurality of nodes as unsupported by target hardware, and marks a second set of nodes in the plurality of nodes as supported by the target hardware, wherein the first set of nodes and the second set of nodes are marked based on one or more attributes defining operation functionality, and wherein the one or more attributes include one or more of an input node parameter, a dimension, or a shape.

Abstract: A method and system provide the ability to compile computer source code. The source code is pre-processed to generate pure source code that includes definitions required for interpretation. The pure source code is formalized in a compiler, into assembly language that is processor specific. The formalization includes determining a set of two or more optimization routines, randomly selecting a selected optimization routine from the set of two or more optimization routines, and applying the selected optimization routine to each segment of the pure source code in a serialized manner. An executable binary file is then output and executed based on the formalized pure source code.

Abstract: A flow graph of a first compilation unit of the program is expanded. The first corresponding parameter states of statements of the first compilation unit are marked as empty. The statements of the first compilation unit are processed to update the first corresponding parameter states with an exact type and a value set. Processing the statements include tracking a control flow predicate of a block in the first compilation unit, wherein the block comprises a first subset of the statements. Only after the control flow predicate indicates that the block is executable, the method includes processing an invocation statement in the first subset of the first statements, and expanding, responsive to the invocation statement, the flow graph for a second compilation unit of the program that is identified by the invocation statement.

Abstract: A package deployment method and apparatus, a terminal device, and a storage medium are disclosed, which are applicable to the field of computer technologies. The method includes: searching, for a plurality of registered devices, for a package adapted to each of the plurality of devices, where a registration operation of the plurality of devices is completed by using a pre-constructed integrated development environment (IDE) tool; and distributing and deploying a found package to a corresponding device, where the corresponding device is a device in the plurality of devices. The constructed IDE tool each time can register with and be connected to a plurality of different devices; searches, for the plurality of registered devices, for a package adapted to each device; and then distributes and deploys a found package to each corresponding device.

Abstract: A first firmware source code portion corresponding to an immutable firmware portion of specific firmware to be deployed with embedded devices is identified. A second different firmware source code portion corresponding to a mutable firmware portion of the specific firmware to be deployed with the embedded devices is identified. The first firmware source code portion is used to generate the immutable firmware portion of the specific firmware. The second firmware source code portion is used to generate the mutable firmware portion of the specific firmware. The immutable firmware portion of the specific firmware is caused to be installed in fixed storage drives of an embedded device in the embedded devices. The mutable firmware portion of the specific firmware is caused to be installed in swappable storage drives of the same embedded device.