1085results about "Program code adaption" patented technology

The invention provides a cross-frame code migration method and system, electronic equipment and a storage medium, and the code migration method comprises the steps: carrying out the frame-level conversion of a first frame code, and generating a target engineering skeleton adaptive to a second frame protocol; analyzing the construction configuration and the entry file, determining an entry point and a compiling rule of code migration, analyzing the first frame code through an abstract syntax tree, and generating a target code range list needing to be migrated; and according to the target code range list and the dependency item list, applying a preset conversion rule to the first framework code, and generating a second framework code adaptive to a second framework protocol. Through automatic framework-level conversion and dynamic rule adaptation, rapid migration from the first framework code to the second framework code is realized, a multi-terminal code library is unified, the manpower development cost is reduced, synchronous operation of business iteration and migration is supported, and the development efficiency is improved.

The invention provides a cross-hardware platform AI algorithm model automatic matching migration method and system based on low-code development, and the method comprises the steps: firstly receiving an AI algorithm model uploaded by a user, obtaining the information of a target hardware platform needing to be migrated, carrying out the optimization adjustment of the AI algorithm model according to the obtained information of the target hardware platform, and carrying out the automatic matching migration of the AI algorithm model. The optimization and adjustment process comprises the following steps: analyzing the AI algorithm model, selecting a corresponding model type according to the function of the algorithm model, carrying out parameter quantification, model conversion, model deployment and evaluation on the AI algorithm model according to the model type, classifying and downloading the converted model, and carrying out optimization and adjustment on the model. An optimized AI algorithm model is obtained; and finally, deploying the obtained AI algorithm model to a target hardware platform. According to the method, the defects of a traditional matching method can be overcome, the model performance and universality are improved, and a unified adaptive solution is provided for different hardware platforms.

Example implementations include a method, apparatus, and computer-readable medium configured for implementing a workflow using a large language model (LLM). A workflow automation application sends a first prompt to a large language model (LLM) to transform a first input data source in a first format to a second format. The workflow automation application sends a second prompt to the LLM to define multiple steps of a workflow starting on the data source in the second format. The workflow automation application sends a third prompt to the LLM to define execution of business logic for each step of the workflow. The workflow automation application receives, from the LLM, output data indicating that each step of the workflow has been executed.

The invention relates to the technical field of computing power resource sharing in a data center application environment, and discloses an enterprise computing power layout and intelligent decision mobile application system and an implementation method thereof. And real-time monitoring and dynamic scheduling of internal or cloud computing resources of an enterprise are realized. Historical data and real-time load are processed by using machine learning and an optimization algorithm, an optimal scheduling scheme is generated, and an alarm is automatically triggered when abnormality is detected, so that efficient utilization of enterprise resources is ensured. The method has the advantages of being high in real-time performance, intelligent, flexible in expansion, safe, reliable and the like, and the operation and maintenance efficiency and decision response speed of enterprises can be remarkably improved.

The invention discloses a Direct3D rendering model compatible method based on a dynamic template pool, which comprises the following steps: establishing three types of mapping tables between D3D and Vulkan when compiling DXVK, constructing resource metadata, and creating a core, extended and temporary three-level template pool according to the mapping tables after starting; when the D3D application creates resources, metadata is initialized, parameters are verified, physical memories are allocated and grouped, resource groups are pre-verified, a batch binding command is generated, memory binding is completed, and the metadata is updated; when a resource view is created, a template is matched from a template pool, a handle is generated after instantiation, a resource handle is associated, and a descriptor is bound; when a rendering state is set and a rendering instruction is executed, the rendering state and the rendering instruction are respectively converted into a Vulkan related state and a Vulkan related instruction through a mapping table, a handle is bound after a PSO cache is inquired, a command buffer area is submitted to a GPU queue to execute drawing, and compatible operation of the D3D application on a platform supporting a Vulkan operating system is realized under the condition that the GPU does not support VKKHRmaintence5 and VKKHRmaintence6 extension.

The invention provides a software package source code optimization method of a cross-instruction-set architecture. The method comprises the following steps: step 1, retrieving and collecting various architecture migration optimization cases; step 2, the verified optimization cases are accumulated through the optimization library; 3, collecting a software package source code with a poor migration effect in a project, and providing the software package source code to a big language model to generate an optimization suggestion of migration between an original architecture and a target architecture; 4, inputting the to-be-optimized software package source code and the optimization suggestion into the large language model to generate a candidate optimization code; 5, further evaluating and screening the candidate optimization codes; step 6, retrieving in the optimization library based on the semantic features of the current code to obtain an excellent instance; step 7, performing optimization again by using a large language model; and step 8, evaluating a construction speed increase rate and function consistency. According to the scheme, a double-stage task decomposition strategy is adopted, the semantic drift risk is effectively reduced, and the accuracy of instruction-level conflict repair is improved.

The invention relates to the technical field of computer software engineering and cross-platform development, in particular to a system for assisting in transplanting Android language to ArkTS (ArkTS) of the swan Mongolia, which comprises a code input module for acquiring Java and Kotlin double-language source codes, an analysis module for analyzing codes by using an improved grammar analysis algorithm, and a storage module for storing the codes. The translation module constructs an abstract syntax tree based on an analysis result and generates an attribute description array, and the generation module generates an ArkTS interface code according to the attribute description array; the distributed computing architecture realizes efficient task scheduling and processing, and the post-processing optimization module guarantees the code quality. Through multi-module cooperation, the probability-rule fusion algorithm, the type dynamic mapping and other technologies, code transplantation can be rapidly and accurately completed, the large project transplantation period is shortened from several weeks to several days, the manual correction cost is reduced, the code conversion accuracy and the system stability are improved, and the development of the wide-gap application ecology is powerfully promoted.

The invention relates to the technical field of electric digital data processing, and provides a secondary development code cross-product transplantation method and device, computer equipment and a medium. The method comprises the steps of loading a source project, screening a to-be-transplanted source code file, identifying an original API type, determining a mapping relation between the original API type and a target API type, and generating an adaptation layer code framework according to the mapping relation; copying the to-be-transplanted source code file into the target project; on the premise of keeping the project hierarchical structure of the source project, replacing the calling node of the original API type with the calling node of the adapter type, and replacing the namespace reference with the corresponding namespace in the target project to obtain a migrated source code file; and obtaining a secondary development project of the target project based on the second product API according to the adaptation layer code framework and the migrated source code file. According to the method and the device, the transplantation efficiency and accuracy of the transplantation of the cross-product secondary development codes are improved.

The invention discloses a multi-dimensional evaluation method for credential environment migration, and particularly relates to the field of evaluation. According to the method, an evaluation index system covering infrastructure, an application system, data resources and security compliance is constructed, and comprehensive scanning is realized through instruction set detection, binary analysis and equal security compliance inspection; dynamically calculating the weight by adopting an AHP-entropy weight hybrid model, and triggering weight rebalance based on the volatility; through combination of static scanning and a dynamic probe, the compatibility, performance and safety differences are quantitatively analyzed; and finally, generating a visual risk assessment report, integrating data of each stage to calculate a compatibility score, a performance loss rate and a security level, providing instruction level difference comparison, a performance flame graph and a vulnerability attack path interaction view, and outputting a migration suggestion comprising a priority reconstruction list, an NEON instruction optimization scheme and a staged reinforcement plan.

The invention provides a Java-to-ArkTS code conversion method and system based on a large model, and belongs to the field of computers.The Java-to-ArkTS code conversion method comprises the steps that S1, a Java project to be converted is comprehensively analyzed, the dependency relationship and semantic information between files are extracted, and a code knowledge graph is constructed; s2, determining a code conversion sequence based on the code knowledge graph, extracting context information and multi-modal semantic information of a to-be-converted code, and completing conversion from Java to TS codes in combination with a multi-agent cooperation mechanism; and S3, comparing and analyzing the TS code with an official ArkTS coding specification, identifying a violation code, and correcting and verifying the violation code through a plurality of intelligent agents to generate an ArkTS code which accords with the ArkTS grammar specification and is consistent in semantics. According to the method, the automatic migration from the Java project to the ArkTS project can be effectively supported, the project migration efficiency and the code quality are improved, and the manual intervention cost is reduced.

The invention belongs to the technical field of software engineering, and particularly relates to a large language model automatic vulnerability patch migration method based on grammar and semantic enhancement. The method comprises the following steps: extracting semantic and grammatical signatures related to vulnerabilities from a patch function of an original branch, wherein the semantic and grammatical signatures comprise a signature before repair and a signature after repair; extracting a corresponding vulnerability function signature from the vulnerability function of the target vulnerability branch; generating a patch migration prompt by using the signature information; using an original-target patch function to finely adjust the data set and the large language model; generating an initial repair function through the fine-tuned large language model; detecting semantic anomaly, placeholder anomaly and grammar anomaly by adopting a heuristic check method; and iteratively optimizing the repair function according to a check result until conditions are met, and outputting a final repair function. The method can effectively improve the success rate of migration of the vulnerability patches among different code branches, reduce manual intervention and reduce security risks.

The invention relates to the technical field of software and hardware compatibility testing, in particular to a domestic software and hardware compatibility intelligent evaluation system and method, and the system comprises a compatibility analysis engine, a compatibility detection task execution engine, a software behavior analysis module, a fault positioning module, a knowledge graph module, a performance optimization suggestion module and a visual interface. The software behavior analysis module constructs a high-dimensional feature space of a software running state through deep learning, and extracts abnormal features based on a topological space mapping technology; the fault positioning module constructs a dynamic causal network based on a probability graph model, and identifies a root node through a chaos sensitivity analysis algorithm; the knowledge graph module constructs a software and hardware dependency relationship model and provides priori knowledge for fault location; and the performance optimization suggestion module generates an optimization scheme based on the root positioning result, so that the functions of automatically executing a compatibility test, accurately positioning the root of the compatibility problem and providing targeted optimization suggestions are realized, and the adaptation efficiency of domestic software and hardware is greatly improved.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and providing transformed code snippets using a large language model. In particular, the disclosed systems can determine a code snippet from a code, for instance, based on user selection of the code snippet. The disclosed system can analyze the code and / or the code snippet to generate a prompt comprising context. The context contains information about the functionality of the code. The disclosed systems further use a large language model to analyze the code snippet and the prompt comprising the context and generate transformed code. The disclosed systems may provide the transformed code snippet to one or more devices.

Techniques for complex code modification via chain of thought prompting are described. A modification service obtains code to be modified according to a modification goal, and can decompose the modification goal, via use of a database or a machine learning model, to identify a set of modification steps. The set of modification steps may be organized according to a chain of thoughts, tree of thoughts, or graph of thoughts. The modification service can execute the set of modification steps via use of a machine learning model to yield modified code, which can be returned to a user.

The invention provides an algorithm plug-in collaborative development method and system based on multi-version control, and relates to the technical field of software development, and the method comprises the following steps: creating a development task and distributing the development task to a plurality of development nodes, constructing a dependency graph and analyzing version conflicts, performing code review, and deploying and testing in test environments of different version underlying frameworks. The compatibility score is calculated through the support vector machine, the release version is determined, and the release information is synchronized, so that collaborative development of multiple development nodes is realized, dependency conflicts are recognized in advance, and the compatibility of the algorithm plug-in under a multi-version framework is ensured.

The invention belongs to the technical field of artificial intelligence and localization basic platforms, and discloses a local large language model operation framework transplantation and adaptation method based on a domestic DCU environment. According to the method provided by the invention, DCU-based local operation framework adaptation is realized, and the hardware selection range of a mainstream large language model operation framework is greatly expanded; through the model quantification and compression technology, the hardware of the local deployment large language model can be quickly applied to the field of natural language processing, and the competitiveness of the domestic hardware in the large language model application is improved.

The invention discloses an architecture system applied to embedded system development, and relates to the field of embedded system development, and the architecture system comprises an application layer which is used for executing business logic in an embedded system and managing the configuration of the embedded system, and the application layer is developed by adopting a Lua script; the hardware abstraction layer provides a unified hardware access interface; and the virtualization interface layer is used for providing a uniform interface for the application layer, so that the application layer can access the hardware resources of the hardware abstraction layer and call the system service in the embedded system. According to the method and the device, the problem that cross-platform transplantation is difficult due to the fact that a C language direct programming mode is adopted in an embedded system in the related technology is solved.

The invention relates to the technical field of business process management, in particular to a data processing method, system and device based on business process management and a medium, and the method comprises the steps: constructing a business process model driven by an abstraction layer, and configuring a multi-protocol standardized interface; according to the business process model driven by the abstraction layer and the multi-protocol standardized interface, a process instance matched with the business scene is generated, and a task is distributed to a target client according to a task demand; managing form state circulation and node jump logic according to a task control engine; an event monitor is deployed through a process key node to monitor the process, and when the process reaches a specified node, external service calling operation is triggered to form an end-to-end automatic closed loop. Therefore, the problems of code redundancy, high maintenance cost, difficulty in quickly adapting to diversified customer requirements and the like due to the fact that business process management generally needs to be subjected to customized development for different subsystems in related technologies are solved.

The invention relates to the technical field of deep learning, in particular to a PyTorch framework-based compatibility expansion system, which comprises a cross-framework model converter, a heterogeneous hardware abstraction layer, a hybrid computational graph execution engine, an intelligent distributed trainer and a self-adaptive optimizer, the cross-frame model converter converts input model formats of different frames into PyTorch executable formats, the heterogeneous hardware abstraction layer supports rear ends of various hardware and automatically selects an optimal calculation path, and the hybrid calculation graph execution engine fuses dynamic graph flexibility and static subgraph optimization and supports dynamic control function execution flow. An intelligent distributed trainer automatically selects a parallel scheme and is compatible with multi-protocol communication, a self-adaptive optimizer performs dynamic optimization based on hardware characteristics and a PyTorch tensor, a cross-frame model converter supports model conversion of multiple deep learning frames, the cost of migration among different frames by a user is reduced, and the universality of the PyTorch frame is improved.

The invention discloses an automatic generation method and system for an intelligent adaptation layer based on API change. The method comprises the steps that API change detection is conducted according to new and old version API interface definitions, adaptation codes are generated according to an API change detection result and compiled into a compatible adaptation layer library, and the compatible adaptation layer library is packaged into an installation package; in the installation stage, the new version target library and the compatible adaptation layer library are installed in a target directory; and loading the compatible adaptation layer library prior to the new-version target library in the running stage, taking over and processing the old-version API interface through the compatible adaptation layer library, and transferring the new-version API interface in the new-version target library. The invention aims to solve the compatibility problem caused by the API change of the software library, realize the automatic generation of the intelligent adaptation layer to ensure the seamless compatibility of the application program with different version libraries under the RPM and other software package management systems, and reduce the maintenance workload for solving the incompatibility problem caused by the API change.

The invention relates to the technical field of chip development, and discloses a transplanting method and device of a swan gap system, a storage medium and computer equipment, and the method comprises the steps: constructing a swan gap system to be transplanted based on a target chip, obtaining a corresponding source code, and then configuring a compiling configuration file in the source code, the compiling subsystem is used for establishing a compiling environment based on configuration information in the compiling configuration file, performing transplantation adaptation on a kernel layer in the compiling environment to generate a kernel mirror image, configuring the starting recovery subsystem, generating a root file system mirror image based on the file system configuration file, and starting the starting recovery subsystem. And finally burning the kernel mirror image and the root file system mirror image to a target chip, and performing function verification and test on the target chip. According to the method disclosed by the present invention, the swan-gap system transplantation including kernel layer transplantation, subsystem adaptation and root file system customization is designed and realized, so that the swan-gap system is successfully adapted to the target chip, and the accelerator equipment carrying the target chip can stably and reliably operate.

The invention provides a large-model-oriented heterogeneous computing power adaptive compiling method, which comprises the following steps that: a user inputs a trained large model through a system interface, and a system front-end conversion module analyzes a computational graph of the model and converts the computational graph into an intermediate representation based on a unified operator description language (UDL); the system hardware sensing module automatically detects and extracts hardware feature fingerprints of at least one piece of target hardware; based on the unified operator description language UDL intermediate representation and the hardware feature fingerprint, automatically generating an optimization adaptation rule oriented to at least one piece of target hardware; wherein the basis of parameterized filling comprises specific parameters of hardware feature fingerprints and optimized attribute tags carried in an intermediate representation of a unified operator description language (UDL); and generating and deploying multiple back-end codes. The method has the beneficial effects that intelligent compiling based on hardware features can be realized, and the deployment efficiency and the operation performance of a large model in a complex heterogeneous computing power cluster are remarkably improved.

The invention belongs to the technical field of software management, and particularly relates to a cross-platform repair method and system based on a large language model.The method comprises the steps that a cross-platform package manager interface is used for conducting static analysis on a dependency list of a target software project, a cross-platform dependency tree is obtained, and the target software project is repaired based on the cross-platform dependency tree; respectively injecting lightweight monitoring probes into at least two operating system platforms, and collecting dynamic tracking data of each dependency component in the dependency tree; fusing the dependency tree and the dynamic tracking data, and establishing a cross-platform security map comprising a dependency calling edge, a version conflict edge and a platform vulnerability association edge; according to the method, the lightweight monitoring probe is injected into the multi-operating system platform, the loading sequence, the function call sequence and the memory layout difference of the dependent components are dynamically collected, and the cross-platform security map is constructed in combination with the static dependency tree, so that the specific potential safety hazard of the platform can be accurately identified, and the comprehensiveness and the accuracy of cross-platform risk perception are remarkably improved.

Embodiments of the present invention provide a system for performing multi-platform software code merging and migration using hybrid neural networks. The system is configured for identifying source files in a software code development environment, wherein each of the source files comprise software code associated with entity applications that is developed by one or more users in one or more software programming languages, translating the software code in each of the source files that is developed in the one or more software programming languages into a translated code that is in a first software programming language, merging the translated code associated with the software code in each of the source files into a unified code, wherein the unified code is in the first software programming language, automatically performing build and packaging of the unified code for deployment, and automatically deploying the packaged unified code into a software code production environment.

The invention discloses a language migration detection method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps of obtaining a first language source code and a second language migration code, wherein the second language migration code is obtained by migrating the first language source code to a second language environment; analyzing the first language source code to obtain a first abstract syntax tree, and analyzing the second language migration code to obtain a second abstract syntax tree; respectively encoding each first node of the first abstract syntax tree and each second node of the second abstract syntax tree through a pre-trained semantic encoder to obtain a first semantic vector of each first node and a second semantic vector of each second node; and inputting the first semantic vector and the second semantic vector into a pre-trained logic detection model, and determining whether the logic of the first language source code and the logic of the second language migration code are consistent or not through the logic detection model, thereby realizing comprehensive detection of the business logic of the source code and the migration code.

To make it possible to highly accurately and automatically convert a model to a model in a different computer modeling environment.SOLUTION: A model conversion device 10 includes a derivation unit 30A, and a generation unit 30B. The derivation unit 30A derives a piece of function specification connection information 52 in which an element B specified in SysML model 50 and a specification element SB as the requirement specification corresponding to the function are associated based on a SysML model 50 (first model), which is generated in a first computer modeling environment of model-based systems engineering and expresses the function of the system by combining multiple elements B. The generation unit 30B generates model generation specification information 54 that is input to an automatic conversion tool 32 that generates a Simulink model 56 (second model) of a second computer modeling environment based on the function specification connection information 52.SELECTED DRAWING: Figure 3

The invention provides an automatic cross-project vulnerability verification method and device based on a large language model, relates to the technical field of vulnerability verification, and aims to solve the problem that whether an upstream vulnerability can still be triggered or not is difficult to efficiently confirm in the prior art in a scene that significant differences exist between parameter semantics and input formats of a source project and a target project. According to the method, a multi-agent parallel target sensing parameter migration framework is constructed, and a legal command line parameter combination related to a vulnerability function is automatically generated from a target software manual in combination with an RAG retrieval enhancement technology; a ReAct intelligent agent is further introduced, a source PoC file is embedded into an acceptable input shell of target software in a cross-format mode under the condition that manual intervention is not needed, and an initial cross-format seed is formed. And iteratively optimizing the parameter-seed pair by taking the function-level trajectory similarity as a feedback index, and driving the parameter sensitive grey box fuzzy test to quickly converge to accurate input capable of triggering vulnerabilities.

The invention provides an LLM command line generation tool based on OpenHarmony and a transplantation method, belongs to the technical field of industrial Internet of Things, and aims to solve the problems that a traditional TypeScript / Node. Js scheme has limitation, is insufficient in local reasoning performance, safety performance and reliability and is high in deployment cost. The tool comprises an ETS development environment module, a code migration module, a dependency library adaptation module, a security enhancement module certificate and a deployment and operation module, a zero-dependency transplantation scheme is designed for special environments of unpacked management tools such as OpenHarmony, the problem of strong coupling of a traditional Node.js application to the environment during operation is solved, and the safety of the Node. Js application is improved. And the deployment threshold of the heterogeneous system is further reduced.

The invention relates to the technical field of computers, and provides a program previewing method and device.The method comprises the steps that an original code and an update code of a program are determined; based on the difference between each character in the original code and the character at the same position in the update code, generating an editing operation sequence which refers to editing operation executed at the same position in the process of converting the original code into the update code; and sending the editing operation sequence to the terminal, so that the terminal incrementally updates the program preview application page based on the editing operation sequence and displays the updated preview application page. According to the program previewing method and device provided by the invention, the data transmission quantity is greatly reduced, and the previewing application page can quickly reflect the latest state of the code, so that the real-time previewing function of code editing is realized.

The disclosure comprises systems and methods for migrating an application between platforms, the method comprising identifying a legacy application for transfer from a legacy mainframe to an enterprise platform. The method can include determining legacy data associated with the legacy application. The method can include receiving the legacy data and the legacy application into the enterprise platform. The method can include determining a classification of the legacy application. The method can include implementing an emulator application wherein the emulator application is configured to generate at least one integration application associated with the classification of the legacy application. The method can further include generating an enterprise application on the enterprise platform based on the legacy data, the legacy application, and the classification of the legacy application.