CN112799966B - Method, system, equipment and medium for generating test data in batches by extensible plug-in - Google Patents
Method, system, equipment and medium for generating test data in batches by extensible plug-in Download PDFInfo
- Publication number
- CN112799966B CN112799966B CN202110330387.7A CN202110330387A CN112799966B CN 112799966 B CN112799966 B CN 112799966B CN 202110330387 A CN202110330387 A CN 202110330387A CN 112799966 B CN112799966 B CN 112799966B
- Authority
- CN
- China
- Prior art keywords
- data
- plug
- batches
- data generation
- generation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/445—Program loading or initiating
- G06F9/44521—Dynamic linking or loading; Link editing at or after load time, e.g. Java class loading
- G06F9/44526—Plug-ins; Add-ons
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/60—Software deployment
- G06F8/61—Installation
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Computer Hardware Design (AREA)
- Quality & Reliability (AREA)
- Stored Programmes (AREA)
Abstract
The invention discloses a method, a system, equipment and a medium for generating test data in batches by extensible plug-ins. The method for generating the test data in batches by using the extensible plug-in comprises the following steps: formulating data generation interface specifications and data type enumeration, processing form variables, generating data, packaging results, reading a function list, rendering the function form, and mapping database fields and functions to obtain a data generation model; installing a plug-in, enabling a main application program to load the plug-in and a data generation model; and reading input parameters of the data generation model, generating data in batches, converting the data generated in batches into SQL statements, and executing SQL in batches. The extensible plug-in batch generation test data system comprises: a data model generation module; a plug-in loading module; and a data generation module. The invention also provides equipment and a medium for generating the test data in batches by using the extensible plug-in.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method, a system, equipment and a medium for generating test data in batches by using extensible plug-ins.
Background
In the mobile internet era, the requirement on the iteration speed of the product is higher and higher, and the defects of the traditional development mode are found in a large amount and concentrated in the test stage, so that the test period is too long, and the on-line time of the product is delayed. Therefore, many test management tools and automated test tools are available in the market to assist the left shift of the test work, and before the automated test, data preparation before the execution of the test script is needed.
The automatic test is divided into various types, such as interface test, UI test and performance test. Different test types have different requirements on test data, and if interface test is carried out, a small amount of data is prepared for a tested interface; if UI test and performance test are carried out, a large amount of data is prepared for one business process or module, especially the performance test, and the prepared data amount is often up to millions.
With the wide application of automated testing, the work of manually preparing test data by testers is increasingly inattentive due to low efficiency, high error rate and incapability of flexibly coping with various business scenes, and in addition, the risk of data leakage exists when data is intercepted from a production environment and imported into the test environment.
The problems of the prior art are summarized as follows:
1. currently, there are two main ways to prepare test data: firstly, manually constructing by relying on a tester; and secondly, intercepting part of data of the production environment, and introducing the data into a test environment for use after cleaning and desensitization. The former method is time-consuming, labor-consuming and inefficient, and is very prone to errors especially when constructing data of complex structures; the latter approach requires very high and somewhat inadvertent cleaning and desensitization tools for the data, with the potential for serious consequences of data leakage.
2. The millions of data generation relying on manual completion is completely unrealistic, and even using some random data generation tools has efficiency problems, thereby causing very high time cost.
Disclosure of Invention
Based on this, an object of the present invention is to provide a method, a system, a device, and a medium for generating test data in batches by using extensible plug-ins, which are based on a data generation tool of data generation rules that can be quickly and flexibly extended by java and spring technologies, and a set of standard plug-in data generation models and plug-in loading flows are defined for the data generation rules, so that a user can extend the data generation rules that satisfy a specific service scenario by writing a simple extension plug-in package without changing any code in a main application program of the data generation tool.
In a first aspect, the present invention provides a method for generating test data in batches by using extensible plug-ins, including:
formulating data generation interface specifications and data type enumeration, processing form variables, generating data, packaging results, reading a function list, rendering the function form, and mapping database fields and functions to obtain a data generation model;
installing a plug-in, enabling a main application program to load the plug-in and a data generation model;
and reading input parameters of the data generation model, generating data in batches, converting the data generated in batches into SQL statements, and executing SQL in batches.
In an embodiment of the foregoing technical solution, the formulating a data generation interface specification includes: defining an interface IGenerater for data generation based on java;
the data type enumeration comprises: one or more of a Boolean value type, a string type, an integer type, a floating point number type, a date type, a time type, a date and time type, a year type, and a long integer type;
the processing of the form variables comprises: the form variables are encapsulated, passed, read, and converted.
In an embodiment of the foregoing technical solution, the reading the function list includes: defining a FuncDesc annotation based on java, wherein the annotation describes a Chinese name of a data generation rule, an English unique limited keyword and a data type which can be matched with generated data, and the annotation is used for marking that an implementation class of an IGenerator is a data rule generation class; reading all the Java classes marked by FuncDesc based on the spring IOC to obtain a function list;
the rendering of the function form comprises: and reading a function list based on HTML and JavaScript, and reading and rendering an input form of the function from a getFormDefinitions method corresponding to each function.
In an embodiment of the foregoing technical solution, the mapping the database field with the function includes: based on HTML and JavaScript, database table fields are obtained, a function corresponding to each database field is selected, and input parameters of the function are filled in.
In one embodiment, the installation insert includes: when the main application program is deployed, installing a plug-in of a data generation rule into a.b.directory under a peer directory of the main application program;
the enabling of the host application to load the plug-in includes: based on java and spring, after the main application program is started, acquiring all plug-in jar packets in the-/lib directory, loading the plug-in jar packets into a memory, and reading all implementation classes of the IGeneraters by using a ServiceLoader provided in the java;
the loading data generation model comprises: based on java and Spring IOC, all the implementation classes read to all IGenerators are instantiated and loaded into the Spring IOC container using the BeanFactory tool provided by the Spring IOC container.
In an embodiment of the foregoing technical solution, the reading input parameters of the data generation model and generating data in batch includes: and the main application program reads the input parameters of the data generation model, calls a generation method in the IGenerator interface, and directly generates data in batches according to the input data generation amount.
In an embodiment of the foregoing technical solution, the converting the batch-generated data into the SQL statement includes: based on java, converting the batch generated data into SQL sentences of a corresponding database;
the batch execution SQL comprises the following steps: JDBC-based, batch-wise insertion of data into a database using a batch-wise approach.
In a second aspect, the present invention provides an extensible plug-in batch generation test data system, including:
the data model generation module is configured and used for formulating data generation interface specifications and data type enumeration, processing form variables, generating data, packaging results, reading a function list, rendering the function form, and mapping database fields and functions to obtain a data generation model;
the plug-in loading module is configured for installing a plug-in, so that the plug-in is loaded by the main application program and the data generation model is loaded;
and the data generation module is used for reading the input parameters of the data generation model, generating data in batches, converting the data generated in batches into SQL statements, and executing SQL in batches.
In a third aspect, the present invention further provides an extensible plug-in batch generation test data device, including:
a memory for storing one or more programs;
a processor for running the program stored in the memory to implement the extensible plug-in batch generation test data method according to any one of the above.
In a fourth aspect, the present invention also provides a computer readable storage medium storing at least one program which, when executed by a processor, implements the extensible plug-in batch generation test data method according to any of the above.
Compared with the prior art, the method, the system, the equipment and the medium for generating the test data in batches by using the extensible plug-in have the beneficial effects that:
the method, the system, the equipment and the medium for generating the test data in batches by using the extensible plug-ins can realize that different data generation functions are expanded by a user according to own business requirements under the condition of not changing a main application program, so that reasonable data generation rules are formulated aiming at different database field types/business scenes, million-level meaningful random data are inserted into a database at a speed far better than that of manual work, and the database data initialization efficiency is greatly improved.
For a better understanding and practice, the invention is described in detail below with reference to the accompanying drawings.
Drawings
FIG. 1 is a block diagram of an exemplary flow of the extensible plug-in batch generation of test data method of the present invention.
FIG. 2 is a block diagram of the extensible plug-in batch production test data system of the present invention.
Detailed Description
The terms of orientation of up, down, left, right, front, back, top, bottom, and the like, referred to or may be referred to in this specification, are defined relative to their configuration, and are relative concepts. Therefore, it may be changed according to different positions and different use states. Therefore, these and other directional terms should not be construed as limiting terms.
The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The terminology used in the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
Referring to FIG. 1, FIG. 1 is a block diagram illustrating an exemplary process of a method for generating test data in extensible plug-in batches according to the present invention.
In a first aspect, the present invention provides a method for generating test data in batches by using extensible plug-ins, including:
s1, data model generation:
and formulating data generation interface specifications and data type enumeration, processing form variables, generating data, packaging results, reading a function list, rendering the function form, and mapping database fields and functions to obtain a data generation model.
Specifically, in the above S1, the formulating the data generation interface specification includes: and defining an interface IGenerator for data generation based on java.
The interface IGenerator mainly comprises:
(1) the getFormDefinitions method is used for obtaining an input parameter form definition of the data generation interface, wherein the input parameter form definition defines input and output parameters of each data generation rule, form configuration of rendering of the input parameters on a front-end page and data types of the input and output parameters.
(2) The generation method is used for receiving the input parameters, calculating the input parameters according to the business requirements corresponding to the current data generation rule and converting the input parameters into output parameters.
Then, the type of input/output data supported by the data generation interface is specified based on java and HTML.
The data type enumeration comprises: a Boolean value type, a string type, an integer type, a floating point number type, a date type, a time type, a date time type, a year type, a long integer type.
The processing of the form variables comprises: the form variables are encapsulated, passed, read, and converted.
The packaging data uses a standard JSON syntax specification, so that the data can be conveniently transmitted across language platforms; an extraction method for resolving and formulating all data types defined in data type enumeration from JSON is provided in an abstract generator of an abstract implementation class of an IGenerator.
And then, generating data, packaging the result, and converting the input parameters into output after calculating according to the business requirements corresponding to the current data generation rule.
The read function list includes: defining a FuncDesc annotation based on java, wherein the annotation describes a Chinese name of a data generation rule, an English unique limited keyword and a data type which can be matched with generated data, and the annotation is used for marking that an implementation class of an IGenerator is a data rule generation class; based on the spring IOC, reading all the Java classes marked by FuncDesc, and acquiring a function list.
The rendering of the function form comprises: and reading a function list based on HTML and JavaScript, and reading and rendering an input form of the function from a getFormDefinitions method corresponding to each function.
The mapping the database field with the function comprises: based on HTML and JavaScript, database table fields are obtained, a user freely selects a function corresponding to each database field, and input parameters of the functions are filled in.
S2, plug-in loading:
and installing the plug-in, so that the plug-in is loaded by the main application program, and the data generation model is loaded.
In S2, the installation plug-in includes: when the operation and maintenance personnel deploy the main application program, the plug-in of the data generation rule is installed in the/lib directory under the peer directory of the main application program.
The enabling of the host application to load the plug-in includes: based on java and spring, after the main application program is started, all the plug-in jar packets in the-/lib directory are obtained, then the plug-in jar packets are loaded into the memory, and all the implementation classes of the IGeneraters are read by using the ServiceLoader provided in the java.
The loading data generation model comprises: based on java and Spring IOC, all the implementation classes read to all IGenerators are instantiated and loaded into the Spring IOC container using the BeanFactory tool provided by the Spring IOC container.
S3, data generation:
and reading input parameters of the data generation model, generating data in batches, converting the data generated in batches into SQL statements, and executing SQL in batches.
In S3, the reading the input parameters of the data generating model and generating data in batch includes: and the main application program reads the input parameters of the data generation model, calls a generation method in the IGenerator interface, and directly generates data in batches according to the input data generation amount.
The converting the batch generated data into the SQL statement comprises the following steps: and converting the batch generated data into SQL sentences of the corresponding database based on java.
The batch execution SQL comprises the following steps: JDBC-based, batch-wise insertion of data into a database using a batch-wise approach.
Through the process, the process of inserting million-level meaningful random data into the database can be efficiently completed.
Referring further to fig. 2, fig. 2 is a block diagram of the scalable plug-in batch test data generation system according to the present invention.
In a second aspect, the present invention provides an extensible plug-in batch generation test data system, including:
the data model generation module is configured and used for formulating data generation interface specifications and data type enumeration, processing form variables, generating data, packaging results, reading a function list, rendering the function form, and mapping database fields and functions to obtain a data generation model;
the plug-in loading module is configured for installing a plug-in, so that the plug-in is loaded by the main application program and the data generation model is loaded;
and the data generation module is used for reading the input parameters of the data generation model, generating data in batches, converting the data generated in batches into SQL statements, and executing SQL in batches.
In a third aspect, the present invention further provides an extensible plug-in batch generation test data device, including:
a memory for storing one or more programs;
and the processor is used for operating the program stored in the memory so as to realize the method for generating the test data in the extensible plug-in batch mode.
The device may also preferably include a communication interface for communicating with external devices and for interactive transmission of data.
It should be noted that the memory may include a high-speed RAM memory, and may also include a nonvolatile memory (nonvolatile memory), such as at least one disk memory.
In a specific implementation, if the memory, the processor and the communication interface are integrated on a chip, the memory, the processor and the communication interface can complete mutual communication through the internal interface. If the memory, the processor and the communication interface are implemented independently, the memory, the processor and the communication interface may be connected to each other through a bus and perform communication with each other.
In a fourth aspect, the present invention further provides a computer-readable storage medium storing at least one program which, when executed by a processor, implements the extensible plug-in batch generation test data method as described above.
It should be appreciated that the computer-readable storage medium is any data storage device that can store data or programs which can thereafter be read by a computer system. Examples of the computer readable storage medium include read-only memory, random-access memory, CD-ROMs, HDDs, DVDs, magnetic tapes, optical data storage devices, and the like. The computer readable storage medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.
Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, Radio Frequency (RF), etc., or any suitable combination of the foregoing.
In some embodiments, the computer-readable storage medium may be non-transitory.
Compared with the prior art, the method, the system, the equipment and the medium for generating the test data in batches by using the extensible plug-in have the beneficial effects that:
the method, the system, the equipment and the medium for generating the test data in batches by using the extensible plug-ins can realize that different data generation functions are expanded by a user according to own business requirements under the condition of not changing a main application program, so that reasonable data generation rules are formulated aiming at different database field types/business scenes, million-level meaningful random data are inserted into a database at a speed far better than that of manual work, and the database data initialization efficiency is greatly improved.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention.
Claims (10)
1. A method for generating test data in batches by extensible plug-in is characterized by comprising the following steps:
formulating data generation interface specifications and data type enumeration, processing form variables, generating data, packaging results, reading a function list, rendering the function form, and mapping database fields and functions to obtain a data generation model;
installing a plug-in, enabling a main application program to load the plug-in and a data generation model;
and reading input parameters of the data generation model, generating data in batches, converting the data generated in batches into SQL statements, and executing SQL in batches.
2. The method of claim 1, wherein the formulating the data generation interface specification comprises: defining an interface IGenerater for data generation based on java;
the data type enumeration comprises: one or more of a Boolean value type, a string type, an integer type, a floating point number type, a date type, a time type, a date and time type, a year type, and a long integer type;
the processing of the form variables comprises: the form variables are encapsulated, passed, read, and converted.
3. The method of claim 2, wherein reading the function list comprises: defining a FuncDesc annotation based on java, wherein the annotation describes a Chinese name of a data generation rule, an English unique limited keyword and a data type which can be matched with generated data, and the annotation is used for marking that an implementation class of an IGenerator is a data rule generation class; reading all the Java classes marked by FuncDesc based on the spring IOC to obtain a function list;
the rendering of the function form comprises: and reading a function list based on HTML and JavaScript, and reading and rendering an input form of the function from a getFormDefinitions method corresponding to each function.
4. The method of claim 3, wherein mapping database fields to functions comprises: based on HTML and JavaScript, database table fields are obtained, a function corresponding to each database field is selected, and input parameters of the function are filled in.
5. The method of claim 4, wherein the installing the plug-in comprises: when the main application program is deployed, installing a plug-in of a data generation rule into a.b.directory under a peer directory of the main application program;
the enabling of the host application to load the plug-in includes: based on java and spring, after the main application program is started, acquiring all plug-in jar packets in the-/lib directory, loading the plug-in jar packets into a memory, and reading all implementation classes of the IGeneraters by using a ServiceLoader provided in the java;
the loading data generation model comprises: based on java and Spring IOC, all the implementation classes read to all IGenerators are instantiated and loaded into the Spring IOC container using the BeanFactory tool provided by the Spring IOC container.
6. The method for generating test data in batches by using extensible plug-ins according to claim 5, wherein the reading of input parameters of a data generation model generates data in batches, and the method comprises the following steps: and the main application program reads the input parameters of the data generation model, calls a generation method in the IGenerator interface, and directly generates data in batches according to the input data generation amount.
7. The extensible plug-in batch generation test data method of claim 6, wherein converting the batch generated data into SQL statements comprises: based on java, converting the batch generated data into SQL sentences of a corresponding database;
the batch execution SQL comprises the following steps: JDBC-based, batch-wise insertion of data into a database using a batch-wise approach.
8. An extensible plug-in batch generation test data system, comprising:
the data model generation module is configured and used for formulating data generation interface specifications and data type enumeration, processing form variables, generating data, packaging results, reading a function list, rendering the function form, and mapping database fields and functions to obtain a data generation model;
the plug-in loading module is configured for installing a plug-in, so that the plug-in is loaded by the main application program and the data generation model is loaded;
and the data generation module is used for reading the input parameters of the data generation model, generating data in batches, converting the data generated in batches into SQL statements, and executing SQL in batches.
9. An extensible plug-in batch generation test data device, comprising:
a memory for storing one or more programs;
a processor for executing the program stored in the memory to implement the extensible plug-in batch generation test data method of any of claims 1-7.
10. A computer-readable storage medium storing at least one program which, when executed by a processor, implements the extensible plug-in batch generation test data method of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110330387.7A CN112799966B (en) | 2021-03-29 | 2021-03-29 | Method, system, equipment and medium for generating test data in batches by extensible plug-in |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110330387.7A CN112799966B (en) | 2021-03-29 | 2021-03-29 | Method, system, equipment and medium for generating test data in batches by extensible plug-in |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112799966A CN112799966A (en) | 2021-05-14 |
| CN112799966B true CN112799966B (en) | 2021-06-29 |
Family
ID=75815889
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110330387.7A Active CN112799966B (en) | 2021-03-29 | 2021-03-29 | Method, system, equipment and medium for generating test data in batches by extensible plug-in |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112799966B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113742361B (en) * | 2021-08-25 | 2024-05-28 | 西藏宁算科技集团有限公司 | Method and system for storing JSON data by using SQL under JS development environment |
| CN114416531A (en) * | 2021-12-23 | 2022-04-29 | 税友信息技术有限公司 | Test data generation method, device, equipment and medium |
| CN114385271B (en) * | 2022-03-22 | 2022-06-03 | 北京云枢创新软件技术有限公司 | Command execution system based on plug-in |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106326122A (en) * | 2016-08-23 | 2017-01-11 | 北京精密机电控制设备研究所 | Software unit test case management system |
| US10678666B1 (en) * | 2011-09-07 | 2020-06-09 | Innovative Defense Technologies, LLC | Method and system for implementing automated test and retest procedures in a virtual test environment |
| CN111382064A (en) * | 2018-12-28 | 2020-07-07 | 北京搜狗科技发展有限公司 | Test method, test device, test medium and electronic equipment |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111813653B (en) * | 2020-05-28 | 2023-07-04 | 杭州览众数据科技有限公司 | Data exception testing method and automatic testing tool related to field content |
| CN112115042A (en) * | 2020-08-12 | 2020-12-22 | 浙江大学 | Software testing method and system based on acquisition and playback |
-
2021
- 2021-03-29 CN CN202110330387.7A patent/CN112799966B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10678666B1 (en) * | 2011-09-07 | 2020-06-09 | Innovative Defense Technologies, LLC | Method and system for implementing automated test and retest procedures in a virtual test environment |
| CN106326122A (en) * | 2016-08-23 | 2017-01-11 | 北京精密机电控制设备研究所 | Software unit test case management system |
| CN111382064A (en) * | 2018-12-28 | 2020-07-07 | 北京搜狗科技发展有限公司 | Test method, test device, test medium and electronic equipment |
Non-Patent Citations (1)
| Title |
|---|
| 基于电信系统的自动化测试平台设计与实现;于涛;《电信技术》;20190630;第56-59页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112799966A (en) | 2021-05-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112799966B (en) | Method, system, equipment and medium for generating test data in batches by extensible plug-in | |
| CN111209203B (en) | Model verification method based on source code | |
| CN106648556A (en) | Front end and back end integrated development testing method and device | |
| CN110309065B (en) | Concurrent execution method, device and equipment of test tasks and storage medium | |
| CN114741070A (en) | Code generation method and device, electronic equipment and storage medium | |
| CN107562459B (en) | Management system, interface generating/displaying/operating method, medium, and terminal | |
| CN114610640B (en) | Fuzzy test method and system for trusted execution environment of Internet of things | |
| CN116502273B (en) | Dynamic data desensitization method, device and equipment based on data blood edges | |
| CN113127357B (en) | Unit test method, apparatus, device, storage medium, and program product | |
| CN112346775B (en) | Index data general processing method, electronic device and storage medium | |
| EP2511841A2 (en) | System and method for generation of cim-based power system circuit models | |
| CN107797805B (en) | Code packaging method and device and computer readable storage medium | |
| EP4075263A1 (en) | Dependency graph generation method and apparatus, device, storage medium, and program product | |
| CN117892665B (en) | Modeling simulation method, device, medium and equipment based on circuit system level model | |
| CN106301976A (en) | A kind of intelligent substation schedule information automated testing method | |
| CN104750468A (en) | Server side topological data conversion method and device | |
| CN113050935A (en) | Method and device for generating mixed object, computing equipment and computer readable storage medium | |
| CN117743145A (en) | Test script generation method and device based on coding template and processing equipment | |
| CN117290233A (en) | Method, system and equipment for custom generation of identification card number based on JMeter | |
| CN106301833A (en) | A kind of transformer station schedule information method of testing | |
| CN108334313A (en) | Continuous integrating method, apparatus and code management system for large-scale SOC research and development | |
| CN114995331A (en) | Bladed platform and PLC hardware-in-loop test communication method, medium and equipment | |
| CN108399196A (en) | The sql automatic execution methods and system of database sql sentence Auto-Generation Tools | |
| CN103677846A (en) | SQLite database development kit and development method thereof | |
| CN114385493A (en) | Performance test method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: Method, system, equipment and medium for generating test data in batch by extensible plug-in Effective date of registration: 20211111 Granted publication date: 20210629 Pledgee: Bank of China Limited by Share Ltd. Guangzhou Tianhe branch Pledgor: Jiajia Technology Co.,Ltd. Registration number: Y2021440000337 |
|
| PE01 | Entry into force of the registration of the contract for pledge of patent right |