77 results about "Parameter Type" patented technology

The invention discloses a method and device for automatically generating a Java method unit test case based on AI, and the method comprises the steps: building a structured annotation specification, carrying out the automatic traversal and intelligent analysis of a Java project, extracting a method signature, a parameter type and a parameter constraint condition, constructing a test data generation model, and carrying out the automatic generation of the test case. The model is transmitted to an AI service to analyze business logic and boundary conditions, test case codes are generated, test cases are optimized and integrated to a project test directory, finally, code areas with insufficient coverage are identified through coverage rate analysis, a test completion strategy is generated, and iterative perfection of the test cases is completed. The technical problems that in the prior art, project-level automatic test case generation cannot be achieved, the generated test case cannot fully cover business logic and boundary conditions, and context relation understanding is lacked are solved, full-automatic project-level test generation is achieved, and the test efficiency and quality are improved.

The invention relates to the technical field of transformers, in particular to a transformer parameterization design method, device and equipment, and the method comprises the following steps: solidifying a transformer design standard and specification in an Excel worksheet, and defining a control parameter through a set compiling grammar; the control parameters comprise a real number type, an integer type, a character string type and a Boolean type; one writing grammar is set for each parameter type; exporting control parameters in the Excel worksheet as an XML (Extensible Markup Language) file; creating a notebook file in automatic design software, and importing the control parameters in the XML file; based on the imported control parameters, parametric modeling is carried out in automatic design software, and a three-dimensional model of the transformer is generated; and automatically generating a two-dimensional engineering drawing of the transformer according to the three-dimensional model. Standardization of links such as design, manufacturing, installation and operation of the transformer is effectively ensured, and therefore performance and reliability of the transformer are greatly improved.

Embodiments of this application relate to the communications field, and disclose a parameter configuration method, to resolve a problem of how to determine a parameter of a second-type bandwidth part BWP in a case of a discrete spectrum. A solution includes: for the parameter of the second-type BWP, determining a parameter determining rule based on a parameter type of the second-type BWP, where the second-type BWP includes N frequency domain resources, N is a positive integer, and N is greater than or equal to 2; and determining a parameter value of the second-type BWP according to the parameter determining rule. The embodiments of this application relate to a process of configuring the parameter of the second-type BWP.

A system includes a first artificial intelligence unit that predicts a performance value by using, as an input, each of a plurality of verification datasets including combinations of the parameter types that are same as the combinations of the parameter types at the time of learning; a selection unit that selects one set of parameter types from a plurality of sets of parameter types included in the plurality of verification datasets predicts performance values of a target substrate processing apparatus obtained by changing variable parameters among the parameters including the selected set of parameter types with, as an input, a fixed parameter intrinsically determined for a target substrate processing apparatus among parameters including the selected set of parameter types, and outputs a combination of parameter values yielding a performance value, among the predicted performance values, satisfying an extraction criterion.

The invention discloses a tool calling method and device, electronic equipment, a medium and a program product, and relates to the technical field of computers. And converting a first parameter output by the large language model based on the data description corresponding to the function tool into a second parameter capable of being input into a target function corresponding to the function tool, calling the target function based on the second parameter to obtain a calling result output by the function tool, and then returning the calling result to the large language model. The big language model can output the first parameter according to the input parameter structure of the target function, so that the function tool can automatically convert the first parameter into the second parameter, and the effect that a developer does not need to process parameter analysis and mapping is achieved; the code quantity is greatly reduced, the development efficiency is greatly improved, and adaptation of complex parameter types can be supported.

The invention discloses a pressure test script parameterized file data generation method and device. The method comprises the following steps: acquiring a swagger definition of an API (Application Program Interface), and obtaining a parameter definition file in a preset format; analyzing the parameter definition file, and obtaining all parameters and corresponding parameter types of the API; and generating random data according to all the parameters and the corresponding parameter types.

This application provides a method and apparatus for generating random instruction test cases, relating to the field of automated testing technology. First, target instructions or instruction sequences are encapsulated into C inline functions using inline assembly or macro definition, forming a unified function library. Next, a function parameter constraint system is constructed, defining parameter types, address ranges, instruction combination methods, and value range constraints for each encapsulated C inline function. Then, a multi-level nested structure is built based on the C inline functions to organize the instructions, where each level node is associated with a corresponding C inline function name and constraints. Finally, based on a YAML configuration file, the target C inline functions are determined from the multi-level nested structure and combined to generate random instruction test cases. The YAML configuration file includes at least the number of iterations, a random seed, a random strength factor, and test content configuration. The solution provided in this application has the advantages of improved verification efficiency and applicability to different scenarios.

The invention provides a training data generation method, electronic equipment, a storage medium and a program product. The training data generation method comprises the steps of obtaining function description information, wherein the function description information at least comprises a function name, a function description, a function input parameter type and a function input parameter description; predicting at least one function input parameter value according to the function input parameter type and the function input parameter description; predicting at least one user instruction according to the function description, the function input parameter description and the at least one function input parameter available value; respectively verifying the at least one function input parameter value and the at least one user instruction to obtain a function input parameter value passing the verification and a user instruction passing the verification; training data are generated at least according to the function name, the function input parameter selectable value passing the verification and the user instruction passing the verification, and the training data are used for training the target large language model to improve the function calling accuracy of the target large language model.

This application provides a configuration file processing method, apparatus, device, medium, and product, relating to the fields of artificial intelligence or fintech. First, configuration file change information is obtained, including modification records of the configuration file during code submissions. Then, the obtained configuration file change information is analyzed to obtain the analysis results of parameter types (including fixed values ​​or dynamic injection). If the analysis result is a fixed value, and / or there is implicit hardcoding, a failure status is returned to trigger process termination; if the analysis result is dynamic injection, and / or there is no implicit hardcoding, a success status is returned to allow the process to continue. This method, by obtaining change information of the target configuration file and analyzing parameter value types, solves the problem of lack of automated detection and mandatory constraints in configuration parameter management in the prior art, realizing automated detection and effective control of configuration parameters, ensuring that configuration parameters meet expected requirements.

The application discloses a database parameter tuning method based on parameter type customization optimization, and belongs to the field of database configuration optimization. The method comprises the following steps: dividing a database parameter space into a continuous parameter subspace and a discrete parameter subspace according to parameter types, and projecting the continuous parameter subspace and the discrete parameter subspace into a low-dimensional space; using a GP model and an SMAC model as proxy models to search for continuous parameter configurations and discrete parameter configurations in the low-dimensional continuous parameter subspace and the low-dimensional discrete parameter subspace respectively; realizing the interaction between the GP model and the SMAC model through iterative optimization and a context-based communication mechanism; and mapping the parameter configuration results back to the database parameter space for performance evaluation. The application can effectively improve the performance and efficiency of database parameter tuning, and allows users to search for database parameter configurations with higher performance in a shorter time.

1. The name of the design product: display screen panel with parameter setting graphical user interface. 2. The use of the design product: the design product is used for running programs, information display and human-computer interaction. 3. The design points of the design product: the content of the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the interface is used for the user to adjust the hardware parameters of the electric skateboard; the main view interface is the initial interface, and the user can slide left and right to select the parameter type for parameter adjustment. 6. Other changes in the situation that need to be explained: the reference diagram of the interface use state is the reference interface of the main view interface in actual use. 7. Other matters that need to be explained: the display screen panel can be used for electric skateboards and electric skateboard remote controllers.

The present application discloses an event extraction method, related devices, and readable storage media. In this solution, the text to be subjected to event extraction is input into a parameter extraction model. After processing the text, the parameter extraction model outputs the parameter information corresponding to the text. Based on the parameter information corresponding to the text, at least one event included in the text is determined. In this method, since the parameter extraction model uses the parameter content corresponding to each preset combination of event types and parameter types annotated with training texts as sample labels, joint learning of event detection and parameter recognition is achieved, reducing the impact of cascading errors. Therefore, the accuracy of event extraction results can be improved by adopting this solution.

The embodiment of the invention provides a data processing method and device.The method comprises the steps that a target application program is analyzed, a parameter type and a function calling relation corresponding to a target function in the target application program are obtained, and the target function comprises a to-be-processed function and a correlation function corresponding to the to-be-processed function; generating a data processing program corresponding to the target function by utilizing a target program generation template according to the parameter type corresponding to the target function and the function calling relationship; inserting a detection point at a function entry of the target function, and establishing an association relationship between the detection point and a data processing program; under the condition that it is determined that the target function is called, a data processing program is triggered to execute the function event in the execution process of the target function through the detection point, an event execution result is obtained from the kernel mode through the data processing program, and the event execution result comprises performance data corresponding to the target function in the execution process of the kernel mode; fine and timely-response troubleshooting and performance optimization are realized.

The invention relates to a compiling period parameter classification method and device, a target code generation method and device and computer equipment. The method comprises the steps of determining type information of a formal parameter list of a to-be-extracted function and a return value type in a compiling period; based on the function behavior of the to-be-extracted function, various types of information and return value types of the formal parameter list are processed in a recursive mode, and an input parameter type and an output parameter type are obtained; and classifying the formal parameters belonging to the input parameter type into an input parameter tuple list, and classifying the formal parameters belonging to the output parameter type into an output parameter tuple list. By adopting the method, automatic classification of parameter types can be realized under the condition of not depending on an IDL (Independent Disk Language) file.

The invention provides a statement processing method and device for a database, equipment, a medium and a product, the database can parse a to-be-processed statement to obtain a syntax tree, and an auxiliary parsing node is constructed for each expression node, so that the statement processing efficiency is improved by traversing the syntax tree. And according to the parameter class of the father node of the corresponding auxiliary node, the parameter type of the target expression node meeting the preset condition is converted, so that the parameter types of the constant and the binding parameter in the currently processed statement can be more accurately determined under the condition that the database can be used for processing data of at least two parameter types.

The invention discloses a communication module instruction fuzzy test method and system. The method comprises the steps of analyzing a historical communication module instruction, determining an instruction parameter type, and determining test record data based on historical fuzzy test data. And determining variation experience data of the instruction parameter type according to the test record data. And on the basis of the variation experience data, constructing a variator scheduling model corresponding to each instruction parameter type. And based on the previously constructed variator scheduling model, predicting a target variator of each instruction parameter type in the to-be-tested instruction, and executing a fuzzy test through the target variator. According to the technical scheme provided by the invention, the hit rate and convergence rate of fuzzy testing are remarkably improved by reusing historical experience, intelligent scheduling of variation strategies is realized, the testing resources are enabled to act on variation combinations which are easier to trigger abnormal states in a centralized manner, the exploration capability of deep states and potential problems of the communication module is enhanced, and the development efficiency of the communication module is improved. And the test efficiency and precision of the fuzzy test process are obviously improved.

The invention relates to the technical field of software testing, and provides an automatic system call specification generation method and system for kernel fuzz testing. The method comprises the following steps: a static analysis stage: compiling a Linux kernel source code to be tested into an LLVM byte code, and performing deep static analysis on the LLVM byte code to identify and reconstruct an interface and a parameter type called by a system; a symbol execution and specification generation stage: adopting a constraint extraction and solution algorithm to extract constraints under different paths, carrying out constraint solution, and generating an initialized calling specification template in combination with an interface called by the system, the parameter type and the constraints; a standard test and verification stage: constructing an evaluation system of a multi-dimensional index to verify the initialized calling standard template and generate corresponding error information; in the large language model auxiliary correction stage, the initialized calling standard template and the error information serve as input, and a high-quality calling standard template is obtained after a large model iteration repair algorithm is conducted.

Embodiments of the present disclosure provide a shared library-oriented fuzzer automatic generation method and device, which comprises: extracting an API function set requiring to be subjected to fuzz testing from source code and a header file of a target shared library; identifying control flow dependence and data flow dependence of an API interface based on the API function set, and constructing an API dependence graph; judging parameter types and deducing dependence relationships between parameters according to the API dependence graph, and distinguishing the parameters into independent variable parameters and state-dependent parameters; generating an executable fuzzer through combination scheduling based on function-to-function calling and dependence relationships in the API dependence graph, and embedding a LibFuzzer semantic coding structure into the fuzzer; and continuously tracking a coverage path during execution of the fuzzer, and preferentially selecting an unexecuted path for testing.

The embodiment of the invention provides a parameter configuration method and device for an Internet of Things terminal, equipment, a medium and a product. The method comprises the following steps: determining a parameter type of an undetermined parameter of the Internet of Things terminal and a target function of a parameter configuration target; obtaining a target population based on the value of the parameter type, and calculating a target function value of the target population according to a target function; storing the target population and the corresponding target function value into a parameter configuration knowledge base, obtaining a filial generation population based on the target population, predicting the target function value of the filial generation population based on the proxy model simulating the target function, obtaining a first population based on the filial generation population, and updating the parameter configuration knowledge base based on the first population, using the updated parameter configuration knowledge base to train an agent model, and obtaining a second population based on the first population; and performing parameter configuration for the to-be-determined parameters based on the second population when iteration stops. According to the method disclosed by the embodiment of the invention, the model adaptability and accuracy can be improved, and the cost and the accuracy are balanced in an online training mode.

Embodiments of the present application provide a kind of geometry modeling engine test method, device, electronic equipment and storage medium, it is related to software testing technical field, the method comprises: in test system, the command class instance for testing geometry modeling engine is registered;Determine the test case for geometry modeling engine, execute test case by test script, determine the test command corresponding to test case and each the parameter sequence corresponding to the test command, the parameter type of parameter sequence is first programming language;According to parameter sequence, from the registered command class instance, the target command class instance matched with test command is extracted;According to the function interface of target command class instance, parameter sequence is parsed, obtains the test parameter of parameter type for second programming language, and according to test parameter, geometry modeling engine is tested, obtains corresponding test result, flexibly and efficiently parses, processes different types of parameter data, reduces the workload of program development and maintenance.

This invention provides a transparent data encryption method, apparatus, and electronic device based on a parameter parser proxy. In this method, by constructing an encryption proxy parser that encapsulates the original parameter parser and replacing the default parser chain in Spring MVC, unified transparent automatic encryption of various heterogeneous request parameter types is achieved without intruding on business code (because the types of the original parameter parsers in the enhanced parser chain are diverse). This technology sinks the encryption logic from the business layer to the parameter binding stage of the framework layer, not only completely eliminating the burden and risk of omissions for developers to manually write repetitive encryption code and ensuring that sensitive data is converted to ciphertext before entering business logic, but also significantly improving the system's data security compliance and code maintainability.

The present invention provides a reusable unified parameter management system, which includes: judging whether it is necessary to expand the parameter type, and if so, using the parameter enumeration method to expand the process to expand the parameters; otherwise, creating parameters by the parameter creation process; entering the parameter persistence process according to the created parameters; judging whether to establish parameter references in the case of multiple parameters, and if so, performing the parameter reference process; otherwise, ending the use. Reduce the cost of subsequent modifications. The module encapsulates parameters and restricts the use type, so that users do not need to worry about type conversion. It provides custom conversion rules and default types, providing a certain amount of expansion space. It performs persistent management for parameters and stores the parameters so that the parameters can be used across modules. It provides a parameter reference function, which gives logic between parameters by managing the parameters.

The present invention relates to a method for extracting structured information from a Pascal-like binary program based on static analysis, which is as follows: (1) using scripts and other tools to preliminarily read basic properties in a binary file compiled from a Pascal-like program; (2) finding all functions that create class objects by obtaining construction feature functions and combining control flow analysis technology; (3) using the base object address as the base address and combining data analysis technology, recursively identifying the member object definition relationship and the inheritance relationship between classes in the binary file; (4) combining the results automatically generated by the script to confirm the corresponding construction function name and the corresponding parameter type and name; (5) based on the above analysis results, finding the corresponding class interface to ensure that the restored code logic is consistent with the original binary file behavior. This method achieves accurate restoration of the class structure, interface, and function, thereby improving the efficiency and accuracy of reverse analysis.

The embodiment of the invention provides a geometric modeling engine testing method and device, electronic equipment and a storage medium, and relates to the technical field of software test.The method comprises the steps that a command type instance used for testing a geometric modeling engine is registered in a testing system; test cases for the geometric modeling engine are determined, the test cases are executed through test scripts, test commands corresponding to the test cases and parameter sequences corresponding to the test commands are determined, and the parameter type of the parameter sequences is a first programming language; extracting a target command type instance matched with the test command from the registered command type instances according to the parameter sequence; analyzing the parameter sequence according to the function interface of the target command type instance to obtain the test parameter of which the parameter type is the second programming language, testing the geometric modeling engine according to the test parameter to obtain a corresponding test result, flexibly and efficiently analyzing and processing different types of parameter data, and improving the test efficiency. And the workload of program development and maintenance is reduced.

The invention discloses an intelligent database system and method for material and test data management, and belongs to the technical field of computer software. The system comprises a material management module which supports management and intelligent verification of material information with labels; the parameter management module supports dynamic creation of parameter types and parameters and configures labeling classification of'basic attributes', 'variable attributes' and'other attributes' for the parameters, and the'variable attributes' support association of a plurality of conditions; the experiment management module is used for inputting experiment data based on a parameter system and supporting template import; the data analysis module is used for comparing and displaying various attribute data of the selected experiment by adopting partition layout, and providing a chart drawing function for variable attributes; and the data query module supports advanced screening based on range combination of a plurality of basic attributes and visualizes a comparison result by using a histogram. According to the method, the problems that existing material management software is rigid in parameter, weak in data relevance and insufficient in analysis capability are solved.

The application discloses a knowledge-guided trusted API recommendation method based on a large language model, and the core idea of the method is to improve the trustworthiness of the LLM in the API recommendation task by using API knowledge. Specifically, in view of the untrustworthiness of the LLM in API recommendation, the application proposes knowledge-guided data enhancement to improve the ability of the LLM to establish the correlation between the user-specified type and the API sequence; proposes knowledge-guided beam search to guide the LLM to generate an API that actually exists and whose calling conditions can be met; and proposes knowledge-guided reordering to optimize the API sequence recommendation list, so that the API sequence that matches the interface parameter type is ranked more in front in the recommendation result. The application has the advantages that API recommendation can be realized under the constraint of the interface parameter type, and the trustworthiness of the large model in the API recommendation task can be improved through high-quality prior knowledge in the API knowledge graph.

1. The name of the design product: display screen panel with parameter setting graphical user interface. 2. The use of the design product: the design product is used for running programs, information display and human-computer interaction. 3. The design points of the design product: the content of the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the interface is used for user interaction for adjusting the hardware parameters of the electric skateboard; the interfaces of design 1 front view and design 2 front view are initial interfaces, and the user can select a certain parameter type in the middle of the initial interface for parameter adjustment. 7. Other situations that need to be explained: the design 1 interface usage state reference diagram is the reference interface of the design 1 front view interface in actual use, and the design 2 interface usage state reference diagram is the reference interface of the design 2 front view interface in actual use. 8. Other situations that need to be explained: the display screen panel can be used for electric skateboards and electric skateboard remote controllers.

The present invention discloses a method, system, device and storage medium for determining test parameters of a memory. The method includes: obtaining performance requirement information of the memory; determining a first parameter type according to the performance requirement information and a preset performance parameter table; performing a first performance test on the memory based on the first parameter type to obtain a first test result; when the first test result indicates that the performance value of the memory is greater than or equal to the performance expected value, configuring the first parameter type as the test parameter of the memory; when the first test result indicates that the performance value of the memory is less than the performance expected value, correcting the first parameter type to obtain a second parameter type; and configuring the second parameter type as the test parameter of the memory. It is possible to determine the corresponding parameter type according to the performance requirement of the memory, so that the test meets the performance requirement and improves the test efficiency.

The invention discloses a method for dynamically generating a function call agreement, a medium and electronic equipment. The method comprises the following steps: a receiving step: receiving a calling parameter and a preset key, the calling parameter comprising a parameter type and a parameter number; a generation step of generating a random number based on the secret key, the parameter type and the number by using a pseudo random number generation algorithm; a judging step: comparing the random number with a preset value, and entering a first registering step when the random number is greater than or equal to the preset value; and a first registering step: disorganizing the sequence of the plurality of registers, and storing the calling parameters into the corresponding registers. According to the method, the hook program can be interfered, and the development difficulty of malware such as plug-in software is greatly increased while the research and development cost is not increased and the software performance is not lost.

The invention relates to the technical field of simulator data processing, in particular to a JS script automatic generation method and system suitable for a swan NEXT simulator. The method comprises the following steps: starting the environment of a swan NEXT simulator, loading a preset JS script template, and obtaining a target method list in an interface set corresponding to a preset API; calling a preset injection tool to analyze a shared library file in the operating environment of the Noumong NEXT simulator, exporting a function symbol table of the shared library file, and extracting a target function address corresponding to the target method list; and determining an entry position, a parameter type, a return value type and stack information of the target function based on the target function address to form a function information set. According to the method, automatic script generation and dynamic function monitoring for the swan gap NEXT simulator are achieved, the target function can be accurately recognized, the system environment can be self-adapted, and therefore the accuracy, real-time performance and compatibility of test analysis are improved.