63 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 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 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 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 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 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.

The invention discloses a general code abstract automatic generation method for large model tool calling in an industrial brain. The method comprises the steps that a code initial abstract corresponding to a target tool code is generated; inputting the initial abstract and the input parameter type thereof into a large model, and generating candidate questions and calling parameters related to function tool calling; calculating a similarity score between the current candidate problem and the historical problem, and selecting the candidate problem with the minimum similarity score and less than a dynamic threshold value in the current round of iteration process as the current round of problem; calling a target function tool by using the problem and the calling parameter, running a function tool related code to output a running result, inputting the function tool code, the problem and the running result into the large model, and generating an analysis result of the calling; according to the method, function tool codes, problems and analysis results are input into a large model, a rewritten code abstract is generated, an adaptive termination mechanism is used for iterative optimization of an abstract instruction, and the accuracy and robustness of a large model calling tool are enhanced.

The invention relates to the technical field of log processing, in particular to a typed parameter prompt-based log analysis method, which specifically comprises the following steps of: firstly, automatically marking a type ontology, automatically identifying a parameter type through a regular expression rule, and generating a typed training label; secondly, virtual token extension and prototype embedding initialization are carried out, a virtual token is created for each parameter type, and prototype embedding is adopted for initialization; and finally, model fine tuning based on multi-loss joint training is carried out, and model fine tuning is completed through joint optimization of MLM loss, contrast learning loss and Focal loss. According to the method, on the premise that few sample learning ability is kept, semantic features of different types of parameters can be distinguished, manual intervention can be reduced to the maximum extent through a full-automatic type labeling mechanism, and therefore robustness and practicability of log analysis are improved.

This application discloses a network layer optimization method for computer technology. First, by defining the parameter structure and parameter types in a protocol buffer file, and second, by creating a target serialization function using the target protocol buffer file, the target serialization function can convert the data of the business layer according to the structure and type defined in the protocol buffer file, enabling accurate transmission over the network or correct storage. Next, the constructed network layer request service integrates the cgiUrl, parameter serialization function, and request function, providing a unified interface for the business layer to initiate network requests. Then, through a code optimization mechanism, eliminating unused code significantly reduces the code size of the network layer request service, thereby accelerating the code process initialization speed. Finally, by using the optimized network layer request service target code, the business code can more concisely and efficiently implement file management-related business logic.

A system and method for clustering computing interface calls. A method includes: determining a plurality of computing interface cluster definitions, the plurality of computing interface cluster definitions including a plurality of parameter type strings; and clustering a plurality of computing interface call instances into a plurality of clusters based on the plurality of computing interface cluster definitions, wherein a number of clusters among the plurality of clusters is fewer than a number of computing interface call instances among the plurality of computing interface call instances, wherein clustering the plurality of computing interface call instances includes determining a plurality of portions of the plurality of computing interface call instances which match types of parameters represented by respective parameter type strings of the plurality of parameter type strings.

The invention provides an SQL injection detection method and device, a storage medium and electronic device.The method comprises the steps that when an injection detection requirement for a target SQL statement is detected, the input parameter type of a target execution function is determined; based on the entry parameter type of the target execution function, determining a parameter detection strategy identifier of each parameter in the target SQL statement, one parameter detection strategy identifier being a white list processing identifier or a black list processing identifier; determining a processing strategy corresponding to each parameter based on the parameter detection strategy identifier of each parameter; processing strategies corresponding to all the parameters are adopted, parameter verification is conducted on the parameter values of all the parameters, parameter verification results of all the parameters are obtained, SQL injection detection results are determined based on the parameter verification results of all the parameters, and the SQL injection detection results are used for indicating whether SQL injection attacks exist in the target SQL statement or not. According to the embodiment of the invention, SQL injection detection can be conveniently carried out.