Test engineering rapid development method and system based on intelligent template
Through the rapid development method of smart template test engineering, the predefined code template library and template recommendation system are used to solve the problems of low efficiency and poor reusability in manual code writing in chip test engineering development, and achieve fast and efficient code generation and iteration.
Patent Information
- Application Number
- CN202411684378.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-22
- Publication Date
- 2025-04-11
AI Technical Summary
During the chip test engineering development process, developers need to write code manually, which is inefficient and error-prone, and it is difficult to achieve reusability and iteration of the code.
Using a rapid development method of test engineering based on intelligent templates, through the predefined code template library and template recommendation system, developers can directly call recommended functional code templates and feature configuration files based on user needs characteristics to reduce manual writing and configuration errors.
It improves the efficiency of the code generation process, reduces manual configuration errors, ensures the reusability and iteration speed of the code, and reduces the requirements for developers' technical knowledge reserves.
Smart Images
Figure CN119806614A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of ATE equipment testing, and in particular to a method and system for rapid development of a test project based on an intelligent template. Background Art
[0002] During the chip test engineering development process, developers need to manually write code for specific test equipment. This development model requires developers to have a full understanding of the characteristics of specific test equipment and has high requirements for developers' technical knowledge reserves. During the development process, code needs to be manually written and configured, which is inefficient and prone to errors. During the development process, the development lacks intelligent tool support, and it is difficult to provide reusable code templates based on specific needs and specific test equipment characteristics. After the development is completed, due to memory loss or differences in technical ideas between different developers, the manually written code is difficult to tune according to the actual operation situation after completion, which in turn affects the efficiency of subsequent development and version iteration. Summary of the invention
[0003] In response to the defects in the prior art, this application proposes a development method based on intelligent templates. Through the predefined code template library and template recommendation, developers do not need to write code from scratch. Instead, they can directly call the function code templates and feature configuration files recommended by the recommendation system according to user demand characteristics, reducing duplication of labor and improving the efficiency of the code generation process; the recommendation system directly recommends function code templates and feature configuration files according to user demand characteristics, reducing the risk of errors in manual configuration; standardized function code templates and feature configuration files ensure that the code can be reused between different projects and developers; even if the developers have different styles or ideas, they can use function code and feature configuration files to achieve consistency, thereby shortening the time for subsequent iterations.
[0004] To solve the above problems, the present application provides a method for rapid development of test engineering based on intelligent templates, which is applied to a recommendation system and includes the following steps:
[0005] S101. Initialization: Initialize the recommendation system and load the predefined code template library; the predefined code template library includes function code templates and feature configuration files;
[0006] S102. Obtaining user demand characteristics: The recommendation system receives user demand characteristics input by the user through a graphical interface or command, and pre-processes the user demand characteristics;
[0007] S103. Template recommendation: The recommendation system matches the function code templates and feature configuration files in the predefined code library according to the user's demand characteristics, and displays the recommendation in the graphical interface;
[0008] S104. Tuning: The recommendation system collects user feedback and modifications to the recommended function code templates and feature configuration files, and optimizes the recommendation system based on the feedback and modifications.
[0009] In a possible embodiment, in S103, the recommendation system recommends the function code template and the feature configuration file through a collaborative filtering algorithm, a content-based recommendation algorithm, or a hybrid recommendation algorithm.
[0010] In a possible embodiment, the following steps are also included:
[0011] The recommendation system collects users' historical usage data and feedback information, and makes personalized recommendations based on the historical usage data and feedback information.
[0012] In a possible embodiment, the user demand characteristics include test type information, device value information, and text feature information.
[0013] In a possible embodiment, in S102, preprocessing includes using word embedding or TF-IDF encoding on text feature information to generate a feature vector for machine learning processing.
[0014] In a possible embodiment, the device numerical information includes: device model, test frequency, and response time.
[0015] In a possible embodiment, in S102, preprocessing includes: performing data cleaning and standardization on the user demand characteristics to remove irrelevant information and structure the user demand characteristics.
[0016] In a possible embodiment, the recommendation system further includes an automatic testing module and a version control module;
[0017] The automatic testing module generates a test script that matches the functional code template according to the user's demand characteristics to automatically execute the recommended functional code template;
[0018] The version control module is used to automatically save the modified function code template and feature configuration file each time the user modifies the function code template and feature configuration file.
[0019] In a possible embodiment, the automatic testing module supports test environment configuration, and the test environment configuration includes: automatic configuration of a unit test environment, an integrated test environment, and a system test environment.
[0020] The present application also provides a test engineering rapid development system based on intelligent templates, including:
[0021] An initialization module is used to initialize the recommendation system and load a predefined code template library; wherein the predefined code template library includes a function code template and a feature configuration file;
[0022] A user demand feature acquisition module is used to receive user demand features input by the user through the recommendation system's graphical interface or commands, and pre-process the user demand features;
[0023] The template recommendation module is installed in the recommendation system to match the function code templates and feature configuration files in the predefined code library according to the user's demand characteristics, and display the recommendations in the graphical interface;
[0024] The tuning module is used to collect user feedback and modifications to the recommended function code templates and feature configuration files, and optimize the recommendation system based on the feedback and modifications.
[0025] Compared with the prior art, this application has the following advantages and beneficial effects:
[0026] It provides a rapid development method for test projects based on intelligent templates; through the recommendation system, it matches recommended function code templates and feature configuration files from the predefined code template library according to user feature requirements, so that developers can quickly generate code according to needs, reduce the amount of manual code, and effectively improve development efficiency; the recommendation system matches and recommends according to user feature requirements, reduces the error rate of manual configuration, and improves the accuracy and reliability of the code; through the predefined code template library, developers do not need to have a broad understanding and in-depth understanding of the characteristics of the test equipment to quickly generate applicable test code templates, reducing the requirements for developers' technical knowledge reserves; at the same time, it recommends standardized function code templates and feature configuration files to eliminate the difficulty of others reusing code due to different ideas; based on feedback and modification optimization recommendations, the reusability, code iteration speed and recommendation accuracy are improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.
[0028] Figure 1 A flowchart of a test engineering rapid development method based on intelligent templates provided in this application;
[0029] Figure 2 A schematic diagram of the operation of a test engineering rapid development system based on intelligent templates provided in this application.
[0030] Description of reference numerals:
[0031] 1. Initial module; 2. Recommendation system; 201. Template recommendation module; 3. Predefined code template library; 301. Feature configuration file; 302. Function code template; 4. User demand acquisition module; 5. Tuning module; 6. User. DETAILED DESCRIPTION
[0032] In the following, various embodiments of the present disclosure will be described more fully. The present disclosure may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of the present disclosure to the specific embodiments disclosed herein, but rather the present disclosure should be understood to cover all adjustments, equivalents and / or alternatives that fall within the spirit and scope of the various embodiments of the present disclosure.
[0033] Hereinafter, the terms "include" or "may include" used in various embodiments of the present disclosure indicate the presence of disclosed functions, operations, or elements, and do not limit the addition of one or more functions, operations, or elements. In addition, as used in various embodiments of the present disclosure, the terms "include", "have", and their cognates are intended only to indicate specific features, numbers, steps, operations, elements, components, or a combination of the foregoing, and should not be understood as first excluding the presence of one or more other features, numbers, steps, operations, elements, components, or a combination of the foregoing or the possibility of adding one or more features, numbers, steps, operations, elements, components, or a combination of the foregoing.
[0034] In various embodiments of the present disclosure, the expression "or" or "at least one of A or / and B" includes any combination or all combinations of the words listed at the same time. For example, the expression "A or B" or "at least one of A or / and B" may include A, may include B, or may include both A and B.
[0035] The expressions (such as "first", "second", etc.) used in the various embodiments of the present disclosure may modify the various constituent elements in the various embodiments, but may not limit the corresponding constituent elements. For example, the above expressions do not limit the order and / or importance of the elements. The above expressions are only used for the purpose of distinguishing one element from other elements. For example, the first user device and the second user device indicate different user devices, although both are user devices. For example, without departing from the scope of the various embodiments of the present disclosure, the first element may be referred to as the second element, and similarly, the second element may also be referred to as the first element.
[0036] It should be noted that if it is described that one component element is “connected” to another component element, the first component element may be directly connected to the second component element, and a third component element may be “connected” between the first component element and the second component element. Conversely, when one component element is “directly connected” to another component element, it can be understood that there is no third component element between the first component element and the second component element.
[0037] The term “user” used in various embodiments of the present disclosure may indicate a person using an electronic device or a device (eg, an artificial intelligence electronic device) using the electronic device.
[0038] The terms used in the various embodiments of the present disclosure are only used for the purpose of describing specific embodiments and are not intended to limit the various embodiments of the present disclosure. As used herein, the singular form is intended to also include the plural form, unless the context clearly indicates otherwise. Unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as the meanings commonly understood by ordinary technicians in the field to which the various embodiments of the present disclosure belong. The terms (such as the terms defined in the generally used dictionary) will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized meaning or an overly formal meaning, unless clearly defined in the various embodiments of the present disclosure.
[0039] Embodiment 1:
[0040] like Figure 1 As shown, this embodiment provides a test engineering rapid development method based on intelligent templates, which is applied to a recommendation system and includes the following steps:
[0041] S101. Initialization: Initialize the recommendation system and load the predefined code template library; the predefined code template library includes function code templates and feature configuration files;
[0042] S102. Obtaining user demand characteristics: The recommendation system receives user demand characteristics input by the user through a graphical interface or command, and pre-processes the user demand characteristics;
[0043] S103. Template recommendation: The recommendation system matches the function code templates and feature configuration files in the predefined code library according to the user's demand characteristics, and displays the recommendation in the graphical interface;
[0044] S104. Tuning: The recommendation system collects user feedback and modifications to the recommended function code templates and feature configuration files, and optimizes the recommendation system based on the feedback and modifications.
[0045] In this embodiment, a rapid development method for test projects based on intelligent templates is provided. The method uses a recommendation system to match recommended function code templates and feature configuration files from a predefined code template library according to user feature requirements. Developers can quickly generate code according to requirements, reduce the amount of manual coding, and effectively improve development efficiency. The recommendation system matches and recommends according to user feature requirements, reduces the error rate of manual configuration, and improves the accuracy and reliability of the code. Through the predefined code template library, developers do not need to have a broad understanding and in-depth understanding of the characteristics of the test equipment to quickly generate applicable test code templates, reducing the requirements for the technical knowledge reserves of developers. At the same time, standardized function code templates and feature configuration files are recommended to eliminate the difficulty of others reusing code due to different ideas of writing code. Recommendations are optimized based on feedback and modifications, thereby improving reusability, code iteration speed, and recommendation accuracy.
[0046] During the implementation process, the recommendation system is first initialized to clear the residual setting commands and parameter configurations from the last practical recommendation system process to restore to the default state; the predefined code library is loaded in advance to prepare for calling the function code templates and feature configuration parameters therein; secondly, the recommendation system obtains the user demand characteristics entered by the development user from the graphical interface or command, and preprocesses the user demand characteristics; again, the corresponding function code modules and feature configuration files are matched in the predefined code library according to the user demand characteristics, and the recommendations are displayed in the graphical interface for the development user to directly select the application or make further optimization and modification on this basis; finally, the feedback and modifications of the development user on the selection of function code modules and feature configuration files are collected, and the feedback and modifications are associated with the user demand characteristics entered by the development user, so that the next time the same or similar user demand characteristics are encountered, the function code modules and feature configuration files selected or modified by the development user can be recommended accordingly.
[0047] Embodiment 2:
[0048] This embodiment is further implemented on the basis of implementation 1. In S103, the recommendation system recommends function code templates and feature configuration files through collaborative filtering algorithm, content-based recommendation algorithm, and hybrid recommendation algorithm.
[0049] The method also includes the following steps: the recommendation system collects the user's historical usage data and feedback information, and makes personalized recommendations based on the historical usage data and feedback information.
[0050] Among them, user demand characteristics include test type information, device value information, and text feature information.
[0051] In S102, preprocessing includes using word embedding or TF-IDF encoding on text feature information to generate a feature vector for machine learning processing.
[0052] The device numerical information includes: device model, test frequency, and response time.
[0053] In S102 , the preprocessing includes: performing data cleaning and standardization on the user demand characteristics to remove irrelevant information and structure the user demand characteristics.
[0054] The recommendation system also includes an automatic testing module and a version control module;
[0055] The automatic testing module generates a test script that matches the functional code template according to the user's demand characteristics to automatically execute the recommended functional code template;
[0056] The version control module is used to automatically save the modified function code template and feature configuration file each time the user modifies the function code template and feature configuration file.
[0057] The automatic testing module supports test environment configuration, which includes automatic configuration of unit test environment, integrated test environment and system test environment.
[0058] The rest of this embodiment is the same as that of Embodiment 1, so it will not be described again.
[0059] Embodiment 3:
[0060] like Figure 2 As shown, this embodiment provides a test engineering rapid development system based on intelligent templates, including:
[0061] An initialization module, used to initialize the recommendation system 2 and load the predefined code template library 3; wherein the predefined code template library 3 includes a function code template 302 and a feature configuration file 301;
[0062] The module 4 for obtaining user demand characteristics is used to receive the user demand characteristics input by the user 6 through the graphical interface or command of the recommendation system 2, and pre-process the user demand characteristics;
[0063] The template recommendation module 201 is installed in the recommendation system 2 and is used to match the function code template 302 and the feature configuration file 301 in the predefined code library according to the user's demand characteristics, and display the recommendation in the graphical interface;
[0064] The tuning module 5 is used to collect feedback and modifications made by the user 6 on the recommended function code template 302 and feature configuration file 301, and optimize the recommendation system 2 according to the feedback and modifications.
[0065] Embodiment 4:
[0066] This embodiment is implemented on the basis of Embodiment 3. In the template recommendation module 201, the recommendation system 2 recommends the function code template 302 and the feature configuration file 301 through a collaborative filtering algorithm, a content-based recommendation algorithm, and a hybrid recommendation algorithm.
[0067] The recommendation system 2 can also be used to collect historical usage data and feedback information of the user 6, and make personalized recommendations based on the historical usage data and feedback information.
[0068] User demand characteristics include test type information, device value information, and text feature information.
[0069] In the module 4 for obtaining user demand features: preprocessing includes using word embedding or TF-IDF encoding on text feature information to generate a feature vector for machine learning processing.
[0070] The device numerical information includes: device model, test frequency, and response time.
[0071] In the module 4 for obtaining user demand characteristics, preprocessing includes: data cleaning and standardization of user demand characteristics to remove irrelevant information and structure the user demand characteristics.
[0072] The recommendation system 2 also includes an automatic testing module and a version control module;
[0073] The automatic testing module generates a test script matching the function code template 302 according to the user requirement characteristics to automatically execute the recommended function code template 302;
[0074] The version control module is used to automatically save the modified function code template 302 and feature configuration file 301 each time the user 6 modifies the function code template 302 and feature configuration file 301 .
[0075] The automatic testing module supports test environment configuration, which includes automatic configuration of unit test environment, integrated test environment and system test environment.
[0076] The rest of this embodiment is the same as that of Embodiment 3, so it will not be described again.
[0077] Those skilled in the art will appreciate that the accompanying drawings are merely schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily required for implementing the present invention.
[0078] Those skilled in the art will appreciate that the modules in the device in the implementation scenario can be distributed in the device in the implementation scenario according to the implementation scenario description, or can be changed accordingly and located in one or more devices different from the implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple sub-modules.
[0079] The above serial numbers of the present invention are only for description and do not represent the advantages or disadvantages of the implementation scenarios.
[0080] The above disclosure is only a few specific implementation scenarios of the present invention, but the present invention is not limited thereto, and any changes that can be conceived by those skilled in the art should fall within the protection scope of the present invention.
Claims
1. A test engineering rapid development method based on intelligent templates, applied to the recommendation system, characterized in that: The following steps are involved: S101. Initialization: Initialize the recommendation system and load a predefined code template library; the predefined code template library includes a function code template and a feature configuration file; S102. Obtaining user demand characteristics: the recommendation system receives user demand characteristics input by the user through a graphical interface or a command, and preprocesses the user demand characteristics; S103. Template recommendation: The recommendation system matches the function code template and the feature configuration file in the predefined code library according to the user's demand characteristics, and displays the recommendation in a graphical interface; S104. Optimization: The recommendation system collects user feedback and modifications to the recommended function code template and feature configuration file, and optimizes the recommendation system based on the feedback and modifications.
2. According to claim 1, a test engineering rapid development method based on intelligent templates is characterized in that: In S103, the recommendation system recommends the function code template and the feature configuration file through a collaborative filtering algorithm, a content-based recommendation algorithm, or a hybrid recommendation algorithm.
3. According to claim 1, a test engineering rapid development method based on intelligent templates is characterized in that: The following steps are also included: The recommendation system collects historical usage data and feedback information of users, and makes personalized recommendations based on the historical usage data and the feedback information.
4. According to claim 1, a test engineering rapid development method based on intelligent templates is characterized in that: in, The user demand characteristics include test type information, device value information, and text feature information.
5. A test engineering rapid development method based on intelligent template according to claim 4, characterized in that: In S102, the preprocessing includes using word embedding or TF-IDF encoding on the text feature information to generate a feature vector for machine learning processing.
6. A test engineering rapid development method based on intelligent template according to claim 4, characterized in that: The device numerical information includes: device model, test frequency, and response time.
7. A test engineering rapid development method based on intelligent templates according to any one of claims 1 to 6, characterized in that: In S102, the preprocessing includes: performing data cleaning and standardization on the user demand characteristics to remove irrelevant information and structure the user demand characteristics.
8. A method for rapid development of test engineering based on intelligent templates according to claim 7, characterized in that: The recommendation system also includes an automatic testing module and a version control module; The automatic testing module generates a test script matching the function code template according to the user requirement characteristics to automatically execute the recommended function code template; The version control module is used for automatically saving the modified function code template and the modified feature configuration file each time the user modifies the function code template and the feature configuration file.
9. A method for rapid development of test engineering based on intelligent templates according to claim 8, characterized in that: The automatic testing module supports the test environment configuration, and the test environment configuration includes: automatic configuration of a unit test environment, an integrated test environment and a system test environment.
10. A test engineering rapid development system based on intelligent templates, characterized in that: include: An initialization module, used to initialize the recommendation system and load a predefined code template library; wherein the predefined code template library includes a function code template and a feature configuration file; A user demand feature acquisition module is used to receive user demand features input by a user through a graphical interface or command of the recommendation system, and pre-process the user demand features; A template recommendation module installed in the recommendation system is used to match the function code template and the feature configuration file in the predefined code library according to the user demand characteristics, and display the recommendation in a graphical interface; The tuning module is used to collect user feedback and modifications made to the recommended function code template and the feature configuration file, and optimize the recommendation system based on the feedback and modifications.