65 results about "Declaration" patented technology

In an example embodiment, a language server connected to an integrated Development Environment (IDE) is used to identify, from a given input code, various code artifacts, such as functions, variables, etc., and then to search a repository of code files for declarations, definitions, and references related to those identified code artifacts. The declarations, definitions, and references can then be passed as context into an LLM.

The invention relates to the technical field of artificial intelligence and software development, in particular to a context-aware code generation and real-time optimization method and system based on a large language model.The method comprises the following steps that a compiler front-end technology is utilized, input codes are analyzed, and an abstract syntax tree is constructed; function definition, variable declaration and statement block structure information are extracted through an abstract syntax tree, so that syntax and semantic structures of codes are obtained, and basic data support is provided for subsequent code generation and optimization; the method has the beneficial effects that the context graph covering grammar, semantics and runtime behaviors is constructed by fusing static grammar analysis (AST construction) and dynamic execution tracking (such as variable value change and function call time sequence), and the problem of context perception deficiency in a traditional code generation technology is solved. And the compatibility, the maintainability and the expandability of the generated code and the project architecture are improved.

The invention discloses a script code processing method and device and a nonvolatile storage medium. The method comprises the steps that script codes of a target program are obtained, and the script codes are based on a front-end programming language; determining a back-end programming language of the target program, and determining a first abstract syntax tree corresponding to the front-end programming language and a second abstract syntax tree corresponding to the back-end programming language; according to the first abstract syntax tree and the second abstract syntax tree, establishing a syntax mapping relation between the front-end programming language and the rear-end programming language; according to the grammar mapping relation, converting the back-end programming language into a target declaration file conforming to the front-end programming language; and loading the target declaration file by utilizing an editor. According to the method and the device, the technical problem of low conversion efficiency caused by the fact that one programming language needs to be manually converted into another programming language in related technologies is solved.

Systems are provided for generating, modifying and using SBOMs for facilitating risk assessment and threat mitigation for corresponding programs, and particularly for large programming builds. The creation and modification of the SBOMs includes processes for omitting declarations referenced in chunk SBOMs of program chunks incorporated into a final programming build associated with a build SBOM, but which are not actually utilized by the final programming build, as well as processes for adding new declarations for code segments that are not declared in the related chunk SBOMs, even though the code segments are utilized by the final programming build. Systems are also configured to use SBOMs in combination with configuration restriction records to assess and resolve threat events in a manner that can prevent unnecessary remedial actions for threat events that appear to be relevant to one or more files or dependencies incorporated into a program.

The embodiment of the invention discloses a code conversion method and device based on a domain-specific language and a medium, and relates to the technical field of code conversion, the method comprises the steps that a DSL file and a target conversion language input by a user are received, the DSL file comprises at least one class definition, and the class definition comprises a class name, a field declaration and a method signature declaration; the DSL file is analyzed to extract a plurality of class annotations marked in the class definition, and the class annotations comprise target language identification information, unique class identification information, construction mode identification information and array access mode identification information; and according to the target language identification information in the target conversion language and the class annotations, a matched specified class annotation set is extracted from the class annotations, a code file conforming to the grammar of the target conversion language is generated based on the specified class annotation set, and the specified class annotation set comprises the class annotations, field annotations and method annotations.

The invention provides an error information instant detection method which can provide more accurate, timely and more credible detection results in a dynamic and complex error information environment. The method comprises the following steps: (1) a retrieval enhancement generation step: (1) retrieving context information related to declarations needing to be classified on a network; (2) the context information is further extracted, and several contents with the highest ranking are extracted; (3) inputting several extracted contents with the highest ranking into a large language model, and summarizing context information by the large language model; (4) enabling the large language model to output a prediction result of statement classification and related evidence, naming the content output by the large language model as priori knowledge, and then combining the statement with the priori knowledge to complete the expansion of the statement; (2) an information classification step; and inputting the expanded declaration into a large language model for classification to obtain a final detection result.

The invention relates to the field of intelligent information processing, in particular to a carbon border adjustment mechanism intelligent auxiliary customs declaration method and system based on natural language processing, and the method comprises the steps: carrying out the real-time translation and key information extraction of CBAM related rule files and unstructured documents; a dynamic CBAM knowledge graph is constructed based on related rule texts, rule updating is monitored in real time through a text classification and event extraction technology, and calculation rules and declaration logic are dynamically adjusted; performing standardization processing on supplier data in different formats, integrating an industry emission factor library, automatically matching a calculation model according to a product type, generating a carbon emission result meeting a CBAM requirement, and mapping the data to a corresponding position of a CBAM declaration form; based on historical declaration data and related rule texts, analysis and compliance risk prediction are carried out by using a natural language processing technology, so that the declaration data are ensured to accord with latest rules, and violation risks caused by rule changes are avoided.

The invention discloses an intelligent auxiliary method, a medium and equipment for constructional engineering title review. According to the method, key feature information of unstructured text data in a declaration material is extracted by using a natural language processing technology, image data features are analyzed by using a ResNet-50 deep learning model, and a comprehensive quantitative scoring mechanism of a construction engineering performance material is established. And integrating education background, working experience, scientific research achievements and multi-modal performance data, constructing a constructional engineering title review rule base, setting a standard score threshold based on historical declaration data, and generating a title simulation review score and a review prediction result. And finally, aiming at the model, designing a feature weight analysis layer, and automatically outputting improvement suggestions of the declaration material defects according to the simulation review score after being associated with the associated review rule base. According to the method, automatic feature extraction and quantitative evaluation of the unstructured material are realized, the problems of low manual auditing efficiency and fuzzy standard are solved, and the objectivity of title evaluation is improved through the rule base and the evaluation prediction model.

The embodiment of the invention provides an evaluation method and device for a retrieval enhancement generation (RAG) system, and relates to the technical field of data processing.The method specifically comprises the steps that a preset question and answer text is input into a target retrieval enhancement generation (RAG) system to obtain a first answer text and a retrieval context text; performing declaration comparison on a standard declaration set corresponding to the obtained standard reply text, a first declaration set corresponding to the obtained first reply text and a retrieval context declaration set corresponding to the obtained retrieval context text; and analyzing and calculating the correct declaration subset, the wrong declaration subset, the missing correct declaration subset and the irrelevant declaration subset in the generated first declaration set to obtain first performance analysis results, and generating a target comprehensive performance evaluation result of the target RAG system based on a plurality of first performance analysis results. According to the method, the RAG system can be subjected to performance evaluation from multiple aspects, and powerful support is provided for wider and more efficient application of the RAG system in the field of artificial intelligence.

The embodiment of the invention discloses a test script generation method, system and device, a medium and a product, and relates to the technical field of tests.The method comprises the steps that target structured DBC data is obtained; processing the target structured DBC data by utilizing a target test script generation model to obtain at least one CAPL test script fragment; the target test script generation model is obtained by training according to historical structured DBC data and corresponding historical CAPL test script fragments; the CAPL test script fragment comprises at least one of variable declaration, function definition and event processing; and according to the at least one CAPL test script fragment, determining a target CAPL test script so as to quickly realize verification of the CAN bus communication condition.

The invention discloses a Function Declaration-oriented code intelligent comparison and incremental updating method and system, and belongs to the technical field of data analys.The method specifically comprises the steps that grammar analysis is conducted on code files of different versions, an abstract syntax tree is constructed, the abstract syntax tree is traversed to extract a function declaration set, and the function declaration set is stored in a database; comparing the function declaration set by adopting an anti-collision hash algorithm, marking the changed function declarations, and carrying out difference analysis; on the basis of the difference analysis result, the system automatically formulates and executes an incremental updating strategy, the unchanged codes are reserved to the maximum extent, and the code upgrading efficiency and reliability are improved.

A method utilizes a policy engine for supply chain security analysis. The method includes processing programming code, written in an imperative programming language, using a fact collector to instantiate a programming object representing a set of facts of a build system that includes an artifact. The method further includes processing the programming object using a mapper to expose the set of facts as a fact database. The method further includes evaluating a policy, written in a declarative programming language, and the fact database using a policy engine to construct a result corresponding to the artifact of the build system. The method further includes presenting the result with a supply chain security analysis of the artifact.

Methods and systems for generating a symbolic model from a markup document, and instantiating a model instance from a symbolic model are described. A markup document containing human language content and mathematical content is parsed into a symbolic model that contains only symbolic code representing an optimization problem. The markup document is parsed to extract a markup declaration, the markup declaration is then processed to a math content span, any metadata entity and any relationship between any metadata entity and the math content span. The math content span is processed into a math content parse tree. The math content parse tree is converted into symbolic code of the symbolic model using any relationship between the metadata entity and the math content span. The symbolic model can be instantiated using data definitions.

The invention discloses a heterogeneous model calling method and device oriented to a strong type language and a storage medium in the technical field of information, and aims at solving the problem that in the prior art, heterogeneous model calling is complex. The method comprises the following steps: describing interface information of a target heterogeneous model in a JSON format, and generating a model interface definition; deserializing the model interface definition corresponding to the target model into an instance of a model interface definition class in a strong type language, modifying the attribute of the instance according to a target demand, and serializing the instance into a model interface definition in a JSON format; and the serialized model interface definition in the JSON format is used as a parameter to be transmitted into a pre-constructed bridging layer so as to execute a conversion function and an activation function, and dynamic calling of a target heterogeneous model interface is carried out. According to the method, the configuration description of the model interface and the dynamic calling capability of the Python weak language are combined, explicit declaration of the model interface or additional model packaging interface transformation is not needed, and the flexibility of the model calling method is improved.

The application discloses a kind of big language model generation content's two-way dynamic fact anchoring verification method and system, belong to artificial intelligence and natural language processing technical field.For part fact verification scheme can only verify " right or wrong " of generated content, it is difficult to verify the problem of " full or not " of key fact, the two-way closed loop of positive verification and reverse verification is established: positive verification is compared with external knowledge base entity for semantic consistency of atomic declaration, and numerical value type declaration is forced to determine according to numerical value difference rate;Reverse verification extracts the list of key facts related to user questions from the knowledge base, checks if it is directly mentioned or implicitly covered by the answer, and generates a missing list;Based on the positive pass rate and reverse coverage rate, the comprehensive confidence is calculated, and the graded reference is output combined with the domain adaptive threshold.The application outputs fact verification results, evidence pointers and graded references, does not cache retry session, and does not perform final shunt based on model output layer uncertainty, and the final disposal can be covered by downstream cognitive honesty decision module.

The invention discloses an LLM-based automatic test software rapid establishment system and method, electronic equipment and a storage medium, and the test software system comprises a script conversion system which is used for inputting a script matched with an SCPI and converting the script into a high-level language source code; the compiling system is used for compiling the high-level language source code into a dynamic link library; the large language model interaction system is stored in the large language model server, converts a declaration file corresponding to the radio frequency test instrument into Prompt, and reads and stores data returned by the large language model; the project processing system is developed, the blank template project is created, and the stored return data is written into the blank template project to obtain the project which can be used for executing the radio frequency test. According to the method and the device, the required script file is configured once, and the relevant function corresponding to the radio frequency test instrument can be permanently called to realize a specific function; the repeated process of looking up a user manual and writing codes again due to instrument replacement during the radio frequency automatic test is avoided.

The embodiment of the invention discloses a declaration form data processing method and related equipment, which are used for improving the flexibility, maintainability and calculation accuracy of declaration form data processing so as to solve the problems of poor system adaptability and high change cost caused by service rule solidification in the prior art. The method provided by the embodiment of the invention comprises the following steps: determining a corresponding target declaration template according to a declaration subject identifier; analyzing the target declaration template, and obtaining a calculation formula set associated with the target declaration template; wherein the calculation formula set comprises at least one configurable formula with a preset format; and processing and calculating source business data based on the calculation formula set to generate declaration form data.

The present application relates to a method, apparatus, computer equipment, storage medium and computer program product for generating a code service call relationship. By traversing the syntax parse tree corresponding to the source code to be detected, the first relationship between the method declaration code module and at least one method call code module in its child node in the syntax parse tree, the second relationship between the method call module and its class and at least one method declaration code module in the corresponding parent class and child class, and the service party to which each code module belongs are obtained, and based on the first relationship and the second relationship, the call relationship table between the code modules in the source code to be detected is determined, and the corresponding service party identifier is added to the code module in the call relationship table to obtain the corresponding code service call relationship table. Compared with the traditional method of obtaining the call relationship between services through the service registration center, this solution obtains the service call relationship in the code by traversing the syntax tree before the code is run, thereby improving the maintainability of the code.

The invention relates to a method for selecting at least one source datum, the source datum being suitable for generating a response to a request from a client agent (Agt) associated with a large language model (LLM), the method comprising: - receiving (E30), from the client agent (Agt), a request and a certificate associated with a declaration of the client agent relating to the request; - calculating (E40) a vector representative of the received request and declaration; - selecting (E40) the at least one source datum by means of a comparison between a vector representative of the source datum used for formulating a response to the request and furthermore representative of a usage constraint for the source datum, and the calculated vector.

The invention relates to the technical field of programming language compilation, and provides a type checking method, electronic equipment and a storage medium, the method comprises the following steps: reading an instruction statement in a to-be-checked program to obtain an operation code, an operand and an expected type of the operand in the instruction statement; based on the operation code, determining the check strict degree of the instruction statement; based on the checking strict degree of the instruction statement, the expected type of the operand and the declaration type of the operand are checked, and the declaration type is determined based on the declaration statement in the program to be checked. According to the method, the electronic equipment and the storage medium provided by the invention, an effective type checking mechanism with universality is realized for a low abstraction level of a virtual instruction set class, and the security of a program is guaranteed. And moreover, more flexible type checking which is more suitable for the own requirements of the instruction statements is realized, unnecessary type limitation caused by strictly fixed type checking is avoided, and the convenience of programming and debugging is improved.

The present application provides a method and apparatus for type inference in a programming language. The method comprises: acquiring an abstract syntax tree of source code, wherein the abstract syntax tree comprises a first node and a subtree of the first node, the first node indicates a first field in the source code, and the first field is one of the following: a variable, a class, a function or a parameter; constructing or updating a full type tree on the basis of the abstract syntax tree, wherein the full type tree indicates the types of a plurality of nodes in the abstract syntax tree and the relationship between the plurality of nodes, and the types of the plurality of nodes are determined on the basis of at least one of the following: the type of a second node in the plurality of nodes is indicated by the abstract syntax tree, and the type of a third node in the plurality of nodes is obtained from a type map, or the type of a fourth node in the plurality of nodes is based on the type of a fifth node, and the type of the fifth node is indicated by the abstract syntax tree or obtained from the type map, wherein the type map indicates the mapping relationship between at least one declaration and at least one type; and outputting an inference result on the basis of the full type tree, wherein the inference result comprises the type of the first node. The solution of the present application facilitates quick and accurate type inference.

The embodiments of the present application provide a method, device, processor, storage medium and program product for adding tracking points. The method includes: obtaining an executable file to which tracking points are to be added; converting the executable file to obtain an abstract syntax tree corresponding to the executable file; traversing the abstract syntax tree to determine the function declaration contained in the abstract syntax tree; obtaining the function name of the function declaration and a preset tracking point configuration file, the preset tracking point configuration file includes a target tracking point function array and a tracking point calling function; when it is determined that the target tracking point function array contains the function name, the tracking point calling function is added to the function corresponding to the function name. This method of adding tracking points does not require manual participation, improves the efficiency of adding tracking points, and will not miss any points. It can accurately and comprehensively track the functions to which tracking points need to be added. In addition, the tracking point reporting rules can be flexibly configured to meet the requirements of multiple aspects for tracking point data reporting.

The invention provides a code completion model training method and device based on semantic attribution. The code completion model training method based on semantic attribution comprises the steps that training codes are acquired; identifying a plurality of first variables from the training code, wherein the first variables are referenced variables with declaration statements in the training code; deleting the target code snippets from the training codes to obtain initial contexts; identifying a second variable from the plurality of first variables according to the initial context, wherein the second variable is the first variable which has the declaration statement in the initial context but is not quoted; deleting a declaration statement of a second variable in the initial context to obtain a target context; and performing model training on the initial model according to the target context and the target code snippet to obtain a code completion model. Deterministic constraints can be overcome, so that the prediction code snippets output by the model conform to real business logic, and the code prediction accuracy is improved.

The present invention discloses a method and system for intelligent code comparison and incremental update for Function Declaration, belonging to the field of data analysis technology. The method specifically includes: performing syntax parsing on code files of different versions, constructing an abstract syntax tree, traversing the abstract syntax tree to extract a set of function declarations, using an anti-collision hash algorithm to compare the set of function declarations, marking changed function declarations, and performing difference analysis; based on the difference analysis results, the system automatically formulates and executes an incremental update strategy to retain unchanged code to the greatest extent, thereby improving the efficiency and reliability of code upgrades.

This application discloses a method and system for generating code review comments on modified code, belonging to the field of computer technology. The method includes: parsing the submitted source code through an IDEA plugin module to abstract the modified file into an abstract syntax tree; extracting information from the abstract syntax tree to obtain extracted information, which includes: the package name, class name, class comments, signatures, comments, and field declarations of other unmodified methods in the class; storing the context information of the modified code obtained from the extracted information into a database; querying the context information through a backend service module and constructing prompt words based on the context information; and guiding a large language model to generate code review comments through the prompt words. This generation method can automatically generate code review comments, thereby improving the intelligence level of code review.

The application discloses a kind of multi-modal fact checking methods of large language model based on retrieval and reasoning enhancement, it is to the sample to be checked containing declaration image and declaration text, first utilize semantic enhancement retrieval module in the uniformity of news domain alignment graph-text feature space, retrieve the evidence image consistent with declaration semantics from candidate evidence;Again, utilize knowledge enhancement retrieval module to carry out entity extraction, knowledge graph / retrieval and refine internet evidence text, obtain background knowledge and high-quality text evidence;Finally, declaration and evidence are jointly input into multi-modal large language model, through the two-stage self-refining reinforcement fine-tuning of cold start, group relative strategy optimization, so that model output contains the authenticity determination result of reasoning process.The application can improve the accuracy and consistency of fact checking based on the joint optimization of multi-modal evidence retrieval and reasoning, so as to provide more reliable automated multi-modal authenticity determination result for news, social media and other scenes.

The present disclosure provides a method, apparatus, device and storage medium for dynamic compilation, in the field of computer technology, particularly in the field of research and development and operation and maintenance of Internet and mobile applications. The specific implementation scheme is: using the DSL specification, parsing the source file to determine the DSL syntax tree corresponding to the source file, and obtaining a first target file; and according to the DSL syntax tree, determining the declaration type and calling order of the program object represented by each node, and then determining the loading order of the declaration type according to the declaration type and the calling order, and obtaining a second target file. Since the second target file contains the declaration types of each program object whose arrangement order is consistent with the calling order, in the process of converting the DSL product in the first target file into the executable file corresponding to the source file in the executable environment, the speed of loading the declaration type and program object can be greatly accelerated, thereby improving the efficiency of converting the DSL product into page display content in real time.

The invention relates to the technical field of text compilation, and discloses an ST compiler implementation method, an ST syntactic analyzer under a C #. NET platform is generated by means of Antlr4, the analyzer analyzes and analyzes an ST source code input by a user, an abstract syntax tree AST is generated, characteristics of a C language and an object-oriented thought are used, a set of data type definition, variable declaration, initialization and read-write are pre-defined, and the data type definition, the variable declaration, the initialization and the read-write are integrated. Templates of declaration, definition, calling and other functions of functions and function blocks are provided; according to the method, traversal and semantic check of the abstract syntax tree are realized, and the C language code is generated according to the predefined template.

Systems are provided for generating, modifying and using SBOMs for facilitating risk assessment and threat mitigation for corresponding programs, and particularly for large programming builds. The creation and modification of the SBOMs includes processes for omitting declarations referenced in chunk SBOMs of program chunks incorporated into a final programming build associated with a build SBOM, but which are not actually utilized by the final programming build, as well as processes for adding new declarations for code segments that are not declared in the related chunk SBOMs, even though the code segments are utilized by the final programming build. Systems are also configured to use SBOMs in combination with configuration restriction records to assess and resolve threat events in a manner that can prevent unnecessary remedial actions for threat events that appear to be relevant to one or more files or dependencies incorporated into a program.