11 results about "Native API" patented technology

The invention discloses a simulation method and a simulation system for an intelligent robot with a body of a cross-physical simulation engine. According to the method, a general meta-action library irrelevant to a simulation engine is defined, a meta-action mapping file is automatically generated in combination with a robot URDF file, and a high-level task instruction is decoupled into a bottom-layer motor control instruction; and then the instruction is converted into native API (Application Program Interface) calling of a target physical simulation engine (such as Isaac Sim, Gazebo and MuJoCo) through a pluggable multi-engine adapter, so that'one-time definition and multi-position operation 'is realized. Meanwhile, by deploying VNC services for all simulation engines, capturing and coding 3D rendering pictures of the simulation engines, multi-instance video streams are integrated in a unified Web workbench, and same-screen viewing, operation and switching are supported. According to the method, the algorithm development efficiency and verification reliability are remarkably improved, the repeated development cost is reduced, and consistent cross-platform simulation experience is provided.

The application belongs to the technical field of computers, and particularly relates to a distributed container scheduling system and method based on a Docker native API. A resource acquisition module creates a communication connection with a local host Docker engine according to a Docker SDK, and acquires real-time resource data of a container managed by the local host. An index evaluation module calls preset custom index evaluation rules to evaluate node availability according to the real-time resource data, and constructs a dynamic resource pool. An intelligent scheduling decision module constructs a decision tree according to node information in the container managed by the local host, takes the dynamic resource pool as a growing resource of the decision tree, calls a rule-based scheduling algorithm to distribute the real-time resource data to nodes corresponding to the decision tree, and a management deployment module directly creates, starts, stops and migrates the container according to a resource scheduling and distribution result of the intelligent scheduling decision module. The application can solve the problem of poor strategy flexibility in the prior art.

The invention discloses a method and a device for performing automatic crawler testing on an applet by using a browser, and relates to the technical field of software testing and data crawling. The method comprises the following steps: acquiring a front-end source code of the applet, converting the front-end source code into a format which can be analyzed and executed by a browser, and redirecting a native API (Application Program Interface) call of the applet to simulation implementation in the browser; when JavaScript used for simulating the core running environment of the applet is injected and executed in the browser instance for running, interactive elements are recognized based on the current page state in the constructed browser simulation environment, interactive operation is executed according to a preset crawler strategy, and page state changes are monitored and iteratively executed till a termination condition is met; and intercepting and recording all network requests and response data through the man-in-the-middle agent, and analyzing and extracting the structured information based on a preset rule. According to the method, efficient and automatic testing and data crawling of the applet in a standard browser environment are achieved, and dependence on a real machine environment is avoided.

The implementation method of the government affair browser based on Electron cross-platform technology utilizes the device driver service middleware to perform hardware adaptation of the government affair peripheral module product on an operating system, and develops a unified standard interface dynamic library; the system level API interface is developed based on Electron Native API and Node.js, the calling of the C++ code function of the unified standard interface dynamic library is realized for the plug-in page of the government affair browser, the specified government affair peripheral module product is operated through the plug-in page, the data of the government affair browser and the hall government affair system are connected based on the Electron Node.js capability, the running state data of the device is pushed to the device management platform in a heartbeat mode by the government affair browser, and the management of the hall unified device and the client is realized. The government affair browser has the web browser and system operation tool capability simultaneously, and the affair efficiency and data security are improved.

The invention discloses a heterogeneous accelerator card sharing and isolating method and system based on API hijacking, and relates to the technical field of resource allocation, the method comprises the following steps: identifying and managing heterogeneous computing equipment mounted on a GPU node, and reporting resource information of the heterogeneous computing equipment; task workloads are distributed to appropriate GPU nodes through an extension scheduler; the GPU node mounts a heterogeneous device API interceptor for the task workload; intercepting API (Application Program Interface) calling of various heterogeneous computing devices; and judging whether the allocated workload exceeds a resource limiting quantity or a video memory limiting quantity, carrying out resource limitation on the exceeded heterogeneous computing equipment, and calling the native API of the heterogeneous computing equipment with sufficient computing resources to execute the task workload. By means of the technical scheme, isolation and sharing of fine grit are achieved, the resource limiting quantity and the video memory limiting quantity of all the devices can be scheduled and managed in a unified mode, and the resource utilization rate of the heterogeneous computing devices is increased.

The invention discloses an automatic interface testing method and device, equipment and a storage medium, and relates to the technical field of interface test.The method comprises the steps that an interface calling request generated by a flow chart platform based on a flow chart case is responded, and the interface calling request carries interface calling parameters; performing case matching in a preset case database based on the interface calling parameters; obtaining target callback data of the current calling interface based on a case matching result; and in the verification execution stage, target callback data is obtained through the flow chart platform, and test result verification is performed based on the target callback data. The callback data of the interface can be obtained through the flow chart platform in the verification execution stage, and the test result verification is performed based on the callback data, so that the interface callback and verification can be separated, and the problems that the callback data of the native API of the client cannot be directly captured by an automatic test method in the prior art, and the test efficiency is high are solved. And instant verification cannot be carried out.

Systems, methods, and non-transitory computer readable media including instructions for implementing a runtime virtual barrier for fine grained execution control are disclose. Implementing the runtime virtual barrier for fine grained execution control includes receiving, by an application capable of JavaScript execution, an executable code including an API invocation; intercepting, by a virtual barrier, the API invocation; determining that the API invocation is an invocation for a native API configured for subsequent execution in response to a trigger event; based on the determination that the API invocation is an invocation for a native API configured for subsequent execution, recording an invocation source identifier; and upon occurrence of the trigger event: retrieving the invocation source identifier; and influencing execution of the native API based on the invocation source identifier.

The invention provides a unified advertisement space implementation method and device for a cross-platform applet and electronic equipment, and relates to the technical field of applet application development, and the method comprises the steps: obtaining processed standardized advertisement data through an advertisement UI component by taking an advertisement space identifier as input; wherein the advertisement interface service packages a complete advertisement service logic, and calls an applet native API (Application Program Interface) through a platform adapter in the advertisement interface service so as to complete the whole process from parameter assembly, network request, error removal to exposure report; rendering according to the standardized advertisement data through the advertisement UI component; and in response to interaction of the user on the rendered advertisement, calling the advertisement interface service to execute unified interaction processing through the advertisement UI component so as to automatically finish effect reporting and calling the native navigation API through the platform adapter to realize skipping. According to the invention, advertisement service logic centralization, platform adaptation transparency and access mode standardization can be realized, and the development efficiency, the system maintainability and the data consistency are effectively improved.

The application provides an adaptation development method and device based on multiple IDEs, electronic equipment and program product. An adaptation communication module is used to listen to an IDE native event, and the event is converted into a standardized request according to an event mapping rule. A central logic module is used to execute target business logic according to a general specification and encapsulate a standardized response. Finally, the adaptation communication module is used to convert the standardized response into an IDE native API calling instruction according to an environment mapping rule. The technical means shields the event and API heterogeneity of different IDEs, realizes the decoupling of the core business logic and the IDE, achieves "one development and multiple IDE reuse", greatly reduces the development and maintenance costs, guarantees the consistency of the functions and interfaces of the IDE plug-ins, simplifies the installation and upgrade operations of the users, improves the use experience, provides a convenient adaptation path for supporting the newly-added IDEs, and enhances the expansibility.

This invention relates to the field of large language model application technology and heuristic optimization algorithms, specifically a method for optimizing toolsets and calling toolchains based on native APIs of large language models. The core steps include: Step 1, Sample Dataset Construction: Extracting multiple sets of "task-conclusion" pairs formed by human analysis from historical reports to construct a sample dataset D; Step 2, Toolset Refinement: Structuring the native APIs of the data platform to refine them into an initial toolset with higher information density; Step 3, Toolset Fine-tuning: Iteratively optimizing the refined toolset using a greedy algorithm to obtain a fine-tuned toolset T adapted for large language model calls. opt Step 4: Using Monte Carlo tree search toolchain invocation; Monte Carlo tree search technology is used to improve the efficiency and stability of toolchain invocation, ensuring high information density, personalized optimization and strong robustness.

This invention discloses a cloud-native API decoy and tracing method and system. The method comprises: 1) designing application-layer API decoys for Kubernetes and Docker respectively, targeting API vulnerabilities in containers and orchestrated cloud components within the cloud environment, and deploying each application-layer API decoy in a honeypot system; 2) updating the priority of each application-layer API decoy based on its current and historical access frequency; 3) sorting the priorities of each application-layer API decoy, setting the top N application-layer API decoys with the highest priority values ​​to an enabled state, and setting the remaining application-layer API decoys to a disabled state; 4) recording logs generated after an attacker enters the honeypot system, generating activity logs of the attacker's intrusion within the cloud environment's intranet based on the logs, and tracing the attacker's origin.