WO2019178967A1

WO2019178967A1 - Jmeter-based stress testing method and apparatus, and device and storage medium

Info

Publication number: WO2019178967A1
Application number: PCT/CN2018/092636
Authority: WO
Inventors: 蔡良
Original assignee: 平安科技（深圳）有限公司
Priority date: 2018-03-22
Filing date: 2018-06-25
Publication date: 2019-09-26
Also published as: CN108572916A; CN108572916B

Abstract

Disclosed are a Jmeter-based stress testing method and apparatus, and a device and a storage medium. The Jmeter-based stress testing method comprises: obtaining a target stress testing request, the target stress testing request comprising at least one original data identifier; obtaining a corresponding target self-defined function on the basis of the at least one original data identifier, the target self-defined function being a function that is not encapsulated by a class; encapsulating the target self-defined function as a BeanShell script file; initializing the BeanShell script file; and invoking the target self-defined function encapsulated in the BeanShell script file to perform stress testing. According to the Jmeter-based stress testing method, in a stress testing process, a desired target self-defined function can be directly invoked, thereby yielding the technical effect of one interpretation and repeated invoking and improving the throughput of a terminal/system while avoiding thread blocking.

Description

Jmeter-based pressure test method, device, device and storage medium

The present application is based on the Chinese Patent Application No. 201101239745.1, entitled "Jmeter-based Pressure Test Method, Apparatus, Apparatus, and Storage Medium", which is filed on March 22, 2018, and claims priority.

Technical field

The present application relates to the field of software testing, and in particular, to a Jmeter-based stress testing method, apparatus, device, and storage medium.

Background technique

There are a variety of tools for stress testing software on the market, and Jmeter is one of the more highly recommended stress testing tools. Jmeter can be used to simulate large loads on servers, networks, or objects, testing their strength from different stress classes to analyze overall performance. When using Jmeter for stress testing, it is usually necessary to write a program for auxiliary testing. The main programming methods are BeanShell and JSR223 scripts (Groovy and Javascript). However, no matter how it is programmed, there is often a system crash in stress testing. Traditionally, it is believed that due to memory leaks in BeanShell's Interpreter, conventional methods cannot support system crashes caused by prolonged stress tests. Jmeter official website recommended, when using BeanShell for long-term testing, you can open the option "Reset bsh.Interpreter before each call", that is, before each call to the BeanShell program, the interpreter is reset to release the front of the interpreter RAM. However, after the interpreter reset option is turned on, a large number of thread blocking is caused in the stress test, which greatly reduces the throughput of the terminal/system.

Summary of the invention

The embodiment of the present application provides a JMET-based stress testing method, apparatus, device, and storage medium to solve the problem that the terminal/system throughput rate is not high during the stress testing process.

In a first aspect, an embodiment of the present application provides a JMET-based stress testing method, including:

Obtaining a target stress test request, the target stress test request including at least one original data identifier;

And acquiring, according to the at least one original data identifier, a corresponding target custom function, where the target custom function is a function that is not encapsulated by the class;

Encapsulating the target custom function into a BeanShell script file;

Initializing the BeanShell script file;

Call the target custom function encapsulated in the BeanShell script file for stress testing.

In a second aspect, the embodiment of the present application provides a Jmeter-based pressure testing device, including:

a target stress test request obtaining module, configured to acquire a target stress test request, where the target stress test request includes at least one original data identifier;

a target custom function obtaining module, configured to acquire a corresponding target custom function based on at least one of the original data identifiers, wherein the target custom function is a function that is not encapsulated by a class;

a target custom function encapsulation module, configured to encapsulate the target custom function into a BeanShell script file;

An initialization module, configured to initialize the BeanShell script file;

The stress test module is used to invoke the target custom function encapsulated in the BeanShell script file for stress testing.

In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and computer readable instructions stored in the memory and executable on the processor, where the processor executes the computer The following steps are implemented when reading the instruction:

Encapsulating the target custom function into a BeanShell script file;

Initializing the BeanShell script file;

In a fourth aspect, the embodiment of the present application provides one or more non-volatile readable storage media storing computer readable instructions, when the computer readable instructions are executed by one or more processors, such that the one or Multiple processors perform the following steps:

Encapsulating the target custom function into a BeanShell script file;

Initializing the BeanShell script file;

The details of one or more embodiments of the present invention are set forth in the accompanying drawings and the description of the claims.

DRAWINGS

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the present application. Other drawings may also be obtained from those of ordinary skill in the art based on these drawings without the inventive labor.

1 is a flow chart of a Jmeter-based stress testing method in Embodiment 1 of the present application;

2 is a flow chart of a specific embodiment of step S20 of FIG. 1;

Figure 3 is a flow chart of a specific embodiment of step S30 of Figure 1;

4 is a flow chart of a specific embodiment of step S31 in FIG. 3;

Figure 5 is a flow chart of a specific embodiment of step S50 of Figure 1;

6 is a schematic diagram of a Jmeter-based pressure testing device in Embodiment 2 of the present application;

Figure 7 is a schematic diagram of a computer device in Embodiment 4 of the present application.

detailed description

The technical solutions in the embodiments of the present application are clearly and completely described in the following with reference to the drawings in the embodiments of the present application. It is obvious that the described embodiments are a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope are the scope of the present application.

This application uses the Jmeter test tool for stress testing. Among them, Jmeter is a Java-based stress testing tool developed by the Apache organization for stress testing software. Jmeter can be used to test static and dynamic resources such as static files, Java servlets, CGI scripts, Java objects, databases or FTP servers. Jmeter can be used to simulate large loads on servers, networks, or objects, testing their strength from different stress classes to analyze overall performance.

Example 1

Fig. 1 shows a flow chart of a Jmeter-based stress test method in this embodiment. The Jmeter-based stress test method can be applied to various terminals or systems to solve the problem that the terminal/system throughput rate is not high during the stress test. As shown in FIG. 1, the Jmeter-based stress test method includes the following steps:

S10: Acquire a target stress test request, where the target stress test request includes at least one original data identifier.

Among them, the stress test is a test process that simulates the software and hardware environment of the actual application and the system load of the user's use process, and runs the test software for a long time or a large load to test the performance, reliability or stability of the system under test. A target stress test request is a request for initiation of a stress test. The original data identifier refers to an identifier that distinguishes the data type of the original data that needs to be imported in the stress test. For example, the data type of the original data may be a GPS message, a CAN message, or an HTTP message. The original data identifier assigns different identifiers to the original data according to the type of the original data.

S20: Acquire a corresponding target custom function based on the at least one original data identifier, where the target custom function is a function that is not encapsulated by the class.

Some commonly used functions are built into Jmeter, which can be queried in the Jmeter->Options->Function Assistant dialog box, but these built-in functions are far from meeting the stress test requirements during partial stress testing. For example, in the stress test of the Internet of Vehicles, On-Board Diagnostic (OBD) is a mobile device with communication capabilities. The OBD is installed in the car, and can collect various data in the driving process of the car in real time, and send it to the background through the communication module. The computing platform in the background will calculate various data of the car (such as fuel consumption information, battery voltage, intake pipe temperature, current The vehicle speed, engine water temperature, engine speed, etc. are calculated. The data packets sent by OBD to the background mainly include: time point, latitude and longitude, speed, current fuel consumption and current mileage. OBD sends packets of the car's driving process through the TCP protocol, so it will contain multiple data packets in one flight mileage, and the time of each data packet increases linearly, and its latitude, longitude, speed and fuel consumption need to change dynamically. Therefore, time, latitude, longitude, latitude, speed, fuel consumption and mileage need to be programmed during the stress test of the Internet of Vehicles. Specifically, a custom function for generating data such as time point, latitude and longitude data, speed, mileage, fuel consumption, etc. is needed to pass in time point, latitude and longitude, mileage, fuel consumption and the like according to the standard message format, and then call the corresponding java program. Synthesize hexadecimal transmission messages.

Therefore, during the stress test, the corresponding custom function needs to be written according to the data type of the original data to ensure that the original data can be smoothly imported into the Jmeter test tool. After obtaining the target stress test request, the corresponding target custom function is obtained based on at least one original data identifier in the target stress test request. The number of the original data identifiers is consistent with the number of categories of the data types of the original data in the target stress test request. Specifically, in the terminal, a corresponding custom function has been written according to the commonly used or already tested data type, and is saved in the corresponding terminal. Therefore, in this step, at least one original data identifier in the target stress test request may be directly obtained to obtain a corresponding target custom function.

The target custom function is specifically a function that is not encapsulated by a class. Class encapsulation refers to encapsulating data and operations into an organic whole. Since private members in the class are hidden and only provide a limited interface to the outside, internal cohesion and low coupling with the outside can be guaranteed. Users don't have to know the specific implementation details, but just use the external interface to use the members of the class with specific access rights, which can enhance security and simplify programming. However, in the process of writing a custom function, if the corresponding target custom function is packaged in a class, in the stress test process, when the corresponding target custom function is continuously called, the class loading is continuously performed. In the process of class loading, locks are required, which inevitably leads to serious thread blocking and affects the throughput of the terminal/system. Therefore, the target custom function at this step is a function that is not encapsulated by the class.

S30: Encapsulate the target custom function into a BeanShell script file.

BeanShell is a small and free JAVA source code interpreter that supports object-oriented scripting language features. It can also be embedded in JAVA source code. It can dynamically execute JAVA source code and extend some features of the scripting language. When using Jmeter for stress testing, BeanShell will interpret the scripted function (BSHMethod) into the cache cache, which is stored in NameSpace.methods. NameSpace.methods is a HashTable object. For function names (without parameters, return values), value is a Vector list (value is a list, because Java has overloaded functions), and Vector is a BSHMethod object. When a script containing a function is executed repeatedly using a unique interpreter, The function is continually placed in the Vector list, causing memory leaks.

Moreover, BeanShell interprets the data type (Scripted Class, BSHType) in the script and puts it into the cache, which is stored in NameSpace.classManager.listeners (class path listener list, because the class needs to search in the class path), listeners are a The Vector list, the BSHType object wrapped in the WeakReference in the Vector, when a script containing the function is executed repeatedly using a unique interpreter, it will continuously store the data type BSHType referenced by the function to the Vector list represented by the listeners, which will also cause Memory leaks.

Since the BSHMethod in NameSpace.methods cannot be released, the class referenced by BSHMethod cannot be released in NameSpace.classManager.listeners, which eventually leads to memory leaks.

In the BeanShell script, the same function as the java class can be implemented by using method declarations and methods in the BeanShell script file, and the methods in the BeanShell script file can have dynamic (loose) parameters and return types. Therefore, in this step, you choose to encapsulate the target custom function into a BeanShell script file.

S40: Initialize the BeanShell script file.

After the target custom function is encapsulated into the BeanShell script file, the BeanShell script file is initialized. Specifically, the pre-processor in Jmeter can be used to initialize the BeanShell script file.

BeanShell.PreProcessor is a preprocessor in Jmeter that executes an algorithm and stores the result in a parameter. By encapsulating the target custom function into a BeanShell script file and initializing the BeanShell script file, the target custom function in the BeanShell script file can be interpreted in advance. Specifically, the BeanShell script file can be initialized in the jmeter.properties file. Illustratively, the initialization of the BeanShell script file is as follows:

Beanshell.preprocessor.init=XX/YY/ZZ/chushihua.bsh;

After the target custom function is packaged into a BeanShell script file, the BeanShell script file is initialized. In this way, in the subsequent stress test process, the required target custom function can be directly called directly, that is, the technical effect of the repeated interpretation can be achieved, and the memory leakage is not easily caused, thereby improving the throughput of the terminal/system. rate.

S50: Call the target custom function encapsulated in the BeanShell script file for stress testing.

After the BeanShell script file is initialized, you can call the target custom function encapsulated in the BeanShell script file for stress testing in the corresponding interface.

In a specific implementation, the target custom function encapsulated in the BeanShell script file is invoked for stress testing, and the stress test is performed by calling a corresponding target custom function encapsulated in the BeanShell script file based on the test parameters.

Among them, the test parameters refer to the parameters that need to be tested in the stress test project. Different test parameters will be imported through the corresponding target custom function to select the corresponding raw data. In different stress test items or types, the test methods may vary due to different test parameters or test requirements. Therefore, during the stress test, not all target custom functions need to be called. In this step, based on the test parameters, the required target custom function is called from the target custom function encapsulated in the BeanShell script file for stress testing. Since the target custom function has been explained in the initialization of the script file, even if the target custom function is called multiple times during the stress test, the target custom function will not be interpreted repeatedly, thus avoiding the memory. Give way.

In this embodiment, the corresponding target custom function is obtained based on the original data identifier in the target stress test request, and the function writing is not required to be repeated, thereby improving the efficiency of the test. Moreover, the target custom function is a function that is not encapsulated by the class, and the target custom function is encapsulated into a BeanShell script file, and the BeanShell script file is initialized to ensure that the required target can be directly in the subsequent stress test process. The custom function can be called, and the effect of repeated interpretation and repeated calling can be realized, and the throughput of the terminal/system is improved under the premise of avoiding thread blocking.

In a specific implementation, the corresponding target custom function is obtained based on the at least one original data identifier, as shown in FIG. 2, including the following steps:

S21: Obtain a custom function corresponding to the original data identifier in the list of the custom function based on the at least one original data identifier, as the target custom function.

Among them, the custom function list is a table for associating data identifiers and custom functions. Optionally, the list of custom functions includes data identifiers and custom functions (as shown in Table 1). After obtaining the original data identifier, the data identifier corresponding to the original data identifier is queried in the custom function list based on the original data identifier, so that the corresponding custom function is obtained as the target custom function.

Table 1 List of custom functions

S22: If any original data identifier exists, and the corresponding custom function is not obtained in the custom function list, a prompt message is sent.

If any original data identifier exists, the corresponding custom function cannot be obtained in the custom function list, indicating that the custom function corresponding to the original data identifier is not stored in the terminal/system. For example (see Table 1): If the original data in the target stress test request is identified as B, C, and D. For the original data identifiers B and C, the corresponding target custom functions Y and Z can be obtained in the list of custom functions. For the original data identifier D, there is no corresponding custom function in the custom function list.

At this point, the terminal/system will send a prompt message to remind the user that there is no corresponding custom function in the terminal/system for the original data identifier. Optionally, the prompt message includes an original data identifier of the corresponding custom function that is not obtained in the custom function list, so as to better remind the user.

S23: Obtain a new custom function input by the user as a target custom function.

After seeing the prompt message sent by the terminal, the user needs to write a corresponding new custom function according to the original data identifier. After the system obtains the newly added custom function, the new custom function is used as the corresponding The target custom function for the raw data identification.

In this embodiment, the corresponding target custom function is obtained through the custom function list, the data acquisition efficiency is improved, and when there is no corresponding custom function, a prompt message is sent to guide the user to write a corresponding new custom. Function to ensure the smooth progress of the stress test.

In a specific implementation, after the step of acquiring a new custom function input by the user as the target custom function, the Jmeter-based stress test method further includes: adding a new custom function and corresponding original data identifier. Associate and save to a list of custom functions.

In this step, after the user inputs a new custom function, the newly added custom function is associated with the corresponding original data identifier, and saved to the custom function list to ensure real-time update of the custom function list. In order to ensure that the original data identifier appears in the next test, the corresponding target custom function can be directly obtained, thereby improving the efficiency of the stress test.

In one embodiment, the target custom function is packaged into a BeanShell script file, as shown in FIG. 3, including the following steps:

S31: Acquire an existing stress test item, and obtain an average number of calls per target custom function based on the existing stress test item.

Among them, the existing stress test project refers to the stress test project that has been completed. In a stress test project, the number of calls for each custom function is different, so you can get the target custom function by querying the call of the corresponding custom function in the existing stress test project. The number of calls.

Optionally, the average number of calls per target custom function can be obtained by obtaining the number of calls of each target custom function in each existing stress test item and summing the number of these calls. .

S32: Encapsulate the target custom function with the average number of calls greater than the preset number into a BeanShell script file.

In the actual stress test, only the target custom function with a higher number of calls will have a greater impact on the operation of the system. Therefore, a preset number of times can be set to determine which of the custom functions used in the existing stress test items, which custom functions have an average number of calls in the existing stress test items greater than a preset number of times, and this part of the custom function The target custom function is encapsulated into a BeanShell script file. The preset number of times can be set according to historical test results or actual needs.

In this embodiment, the average number of calls of each target custom function is obtained by obtaining and calculating the number of calls of each target custom function in the existing stress test item, and then the average number of calls is greater than the preset number of times. The target custom function is packaged into a BeanShell script file, which reduces the burden on the terminal/system and further improves the throughput.

In one embodiment, the target stress test request also includes a target stress test type. The target stress test type refers to the test type corresponding to the target stress test request.

In this embodiment, an existing stress test item is obtained, including: obtaining an existing stress test item of the same type of stress test item as the target stress test.

The stress test project can be divided into different types according to different test conditions and test requirements. The test process of the same type of stress test project is relatively similar. The accuracy of the data is improved by obtaining the existing stress test items of the same type as the target stress test type and obtaining the average number of calls per target custom function based on the existing stress test items of the same type as the target stress test type.

In this embodiment, the average number of calls of the target custom function is calculated by acquiring an existing pressure test item having the same type as the target stress test in the existing stress test item, thereby ensuring the accuracy of the data.

In one embodiment, the existing stress test items include existing stress test types.

For different existing stress test items, existing stress test items can be classified according to different types, and different types of existing stress test items can be distinguished by existing stress test types.

In this embodiment, the average number of calls per target custom function is counted based on the existing stress test item, as shown in FIG. 4, including the following steps:

S311: Count the number of times each target custom function is called in each existing stress test item.

The number of calls of each target custom function in each existing stress test item is obtained by querying the call of the corresponding custom function in the existing stress test item.

S312: Set a corresponding weight for each existing stress test item based on the correlation between the existing stress test type and the target stress test type.

The stress test project can be divided into different types according to different test conditions and test requirements. The test process of the same type of stress test project is relatively similar. Therefore, a corresponding weight can be set for each existing stress test item based on the correlation between the existing stress test type and the target stress test type. The higher the relevance, the higher the corresponding weight. In one embodiment, the weight of the existing stress test item of the same type as the target pressure test type can be set to a, and the weight of the existing stress test item of the other type different from the target stress test type is set to 0.5a. .

S313: weighting and summing the number of calls of each target custom function in different existing stress test items based on the weight of each existing stress test item, and obtaining an average of each target custom function. The number of calls.

After obtaining the number of calls for each target custom function in each existing stress test item, and according to the weights set for each existing stress test item, each target custom function is different. The number of calls in the stress test project is weighted and averaged, that is, the average number of calls per target custom function is obtained.

In this embodiment, a corresponding weight is set for each existing stress test item according to the correlation between the existing stress test type and the target stress test type, and each target is calculated according to the set weight value. The average number of calls to the custom function further ensures the accuracy of the data.

In one embodiment, the target custom function encapsulated in the BeanShell script file is invoked for stress testing, as shown in FIG. 5, and the following steps are also included:

S51: Start the counter and count the number of iterations of the target custom function.

Traditionally, when using BeanShell for long-term testing in the Jmeter test harness, the option "Reset bsh.Interpreter before each call" is turned on, which resets the interpreter before each call to the BeanShell program to release the interpreter. The memory used before. However, after the interpreter is reset, the corresponding class needs to be reloaded each time, and the process of class loading causes a large amount of blocking of the thread. That is, by re-executing the interpreter, the memory can be freed, but the thread is relatively blocked, resulting in an inability to increase the throughput.

In this step, the number of iterations of the target custom function during the stress test is counted by starting the counter in the Jmeter. Specifically, in Jmeter, the counter allows the user to create a counter that can be referenced within the thread group. This counter allows the user to configure a starting point, a maximum value and a corresponding number of increments, after which the counter starts at the starting point and continues to the maximum value according to the number of increments. Then, start over and continue to cycle until the end of the stress test. Therefore, during the stress test, the corresponding counter can be configured for each target custom function to count the number of iterations of the target custom function during the stress test.

S52: If the number of iterations of any target custom function is greater than an iteration threshold, the interpreter is reset.

The counter counts the number of iterations of each target custom function during the stress test. If the number of iterations of any target custom function is greater than the iteration threshold, the interpreter is reset to free memory and avoid memory leaks.

In this embodiment, the number of iterations of each target custom function is counted by using a counter. If the number of iterations of any target custom function is greater than the iteration threshold, the interpreter is reset to avoid memory leakage and further avoid thread blocking. Improve the throughput of the terminal/system.

It should be understood that the size of the sequence of the steps in the above embodiments does not mean that the order of execution is performed. The order of execution of each process should be determined by its function and internal logic, and should not be construed as limiting the implementation process of the embodiments of the present application.

Example 2

Fig. 6 is a block diagram showing the principle of a Jmeter-based pressure testing device corresponding to the Jmeter-based pressure testing method in the first embodiment. As shown in FIG. 6, the Jmeter-based stress testing device includes a target stress test request acquisition module 10, a target custom function acquisition module 20, a target custom function packaging module 30, an initialization module 40, and a stress test module 50. The implementation functions of the target stress test request acquisition module 10, the target custom function acquisition module 20, the target custom function encapsulation module 30, the initialization module 40, and the stress test module 50 correspond to the Jmeter-based stress test method in Embodiment 1. The steps are one-to-one correspondence, and the details are not described in detail in order to avoid redundancy.

The target stress test request acquisition module 10 is configured to obtain a target stress test request, and the target stress test request includes at least one original data identifier.

The target custom function obtaining module 20 is configured to obtain a corresponding target custom function based on the at least one original data identifier, wherein the target custom function is a function that is not encapsulated by the class.

The target custom function encapsulation module 30 is configured to encapsulate the target custom function into a BeanShell script file.

The initialization module 40 is configured to initialize the BeanShell script file.

The stress test module 50 is configured to invoke a target custom function encapsulated in the BeanShell script file for stress testing.

Preferably, the target custom function acquisition module 20 includes a target custom function acquisition unit 21, a prompt message transmission unit 22, and a new custom function acquisition unit 23.

The target custom function obtaining unit 21 is configured to obtain, according to the at least one original data identifier, a custom function corresponding to the original data identifier in the custom function list as the target custom function.

The prompt message sending unit 22 is configured to send a prompt message if any original function is not obtained in the custom function list if any original data identifier exists.

A new custom function obtaining unit 23 is configured to obtain a newly added custom function input by the user as a target custom function.

Preferably, the target custom function obtaining module 20 further includes a new custom function associating unit 24.

A new custom function association unit 24 is added to associate the newly added custom function with the corresponding original data identifier and save it to the custom function list.

Preferably, the target custom function encapsulation module 30 includes an average call count acquisition unit 31 and a target custom function encapsulation unit 32.

The average call count obtaining unit 31 is configured to acquire an existing stress test item, and obtain an average number of calls of each target custom function based on the existing stress test item.

The target custom function encapsulating unit 32 is configured to encapsulate the target custom function whose average number of calls is greater than the preset number of times into a BeanShell script file.

Preferably, the target stress test request further includes a target stress test type. The average call count obtaining unit 31 is further configured to acquire an existing stress test item of the same type of the target stress test in the existing stress test item.

Preferably, existing stress test items include existing stress test types. The average call count acquisition unit 31 includes a call count count sub-unit 311, a weight value setting sub-unit 312, and an average call count acquisition sub-unit 313.

The call count statistics sub-unit 311 is configured to count the number of calls of each target custom function in each existing stress test item.

The weight setting sub-unit 312 is configured to set a corresponding weight for each existing stress test item based on the correlation between the existing stress test type and the target stress test type.

The average call count acquisition sub-unit 313 is configured to perform weighted summation and average the call times of each target custom function in different existing stress test items based on the weight of each existing stress test item, and obtain an average value The average number of calls per target custom function.

Preferably, the stress test module 50 includes an iteration count statistic unit 51 and an interpreter reset unit 52.

The iteration count statistic unit 51 is configured to start a counter and count the number of iterations of the target custom function.

The interpreter reset unit 52 is configured to reset the interpreter if the number of iterations of any of the target custom functions is greater than an iteration threshold.

Example 3

The embodiment provides one or more non-volatile readable storage media having computer readable instructions that, when executed by one or more processors, cause the one or more processors to execute The steps of the Jmeter-based stress test method in Embodiment 1 are not repeated here to avoid repetition. Alternatively, when the computer readable instructions are executed by one or more processors, causing the one or more processors to implement the functions of the modules/units in the Jmeter based stress testing device of Embodiment 2, to avoid duplication, I won't go into details here.

It is to be understood that the non-volatile readable storage medium may include any entity or device capable of carrying the computer readable instruction code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, only Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier signals, and telecommunications signals.

Example 4

FIG. 7 is a schematic diagram of a computer device according to an embodiment of the present application. As shown in FIG. 7, computer device 60 of this embodiment includes a processor 61, a memory 62, and computer readable instructions 63 stored in memory 62 and executable on processor 61. The processor 61 performs the steps of the Jmeter-based stress test method of Embodiment 1 described above when executing the computer readable instructions 63, such as steps S10 to S50 shown in FIG. Alternatively, when the processor 61 executes the computer readable instructions 63, the functions of the modules/units in the foregoing device embodiments are implemented, such as the target stress test request acquisition module 10, the target custom function acquisition module 20, and the target self shown in FIG. The functions of function encapsulation module 30, initialization module 40, and stress test module 50 are defined.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the division of each functional unit and module described above is exemplified. In practical applications, the above functions may be assigned to different functional units as needed. The module is completed by dividing the internal structure of the device into different functional units or modules to perform all or part of the functions described above.

The above-mentioned embodiments are only used to explain the technical solutions of the present application, and are not limited thereto; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still implement the foregoing embodiments. The technical solutions described in the examples are modified or equivalently replaced with some of the technical features; and the modifications or substitutions do not deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in Within the scope of protection of this application.

Claims

A Jmeter-based stress testing method, comprising:

Obtaining a target stress test request, the target stress test request including at least one original data identifier;

And acquiring, according to the at least one original data identifier, a corresponding target custom function, where the target custom function is a function that is not encapsulated by the class;

Encapsulating the target custom function into a BeanShell script file;

Initializing the BeanShell script file;

Call the target custom function encapsulated in the BeanShell script file for stress testing.
The Jmeter-based stress testing method according to claim 1, wherein the obtaining the corresponding target custom function based on the at least one of the original data identifiers comprises the following steps:

Obtaining, according to the at least one of the original data identifiers, a custom function corresponding to the original data identifier in the custom function list, as a target custom function;

If any of the original data identifiers are present, a corresponding custom function is not obtained in the custom function list, and a prompt message is sent;

Get the new custom function entered by the user as the target custom function.
The Jmeter-based stress testing method according to claim 2, wherein after the step of acquiring a newly added custom function input by the user as a target custom function, the stress testing method further comprises:

The newly added custom function is associated with the corresponding original data identifier and saved in the custom function list.
The Jmeter-based stress testing method according to claim 1, wherein the encapsulating the target custom function into a BeanShell script file comprises the following steps:

Obtain an existing stress test project, and obtain an average number of calls per target custom function based on an existing stress test project;

A target custom function with an average number of calls greater than a preset number of times is packaged into the BeanShell script file.
The Jmeter-based stress testing method according to claim 4, wherein the target stress test request further comprises a target stress test type;

The obtaining the existing stress test item comprises: acquiring an existing stress test item of the same type of the stress test item and the target stress test type.
The Jmeter-based stress testing method according to claim 4, wherein said existing stress test item comprises an existing stress test type;

The calculating the average number of calls of each target custom function based on the existing stress test item includes the following steps:

Counting the number of calls per target custom function in each of the existing stress test items;

And setting a corresponding weight for each of the existing stress test items based on the correlation between the existing stress test type and the target stress test type;

Weighting and summing the number of calls of each of the target custom functions in different existing stress test items based on the weight of each of the existing stress test items, and obtaining an average of each of the target targets Defines the average number of calls to the function.
The Jmeter-based stress testing method according to claim 5, wherein the target custom function encapsulated in the BeanShell script file is used to perform a stress test, and the stress testing method further includes:

Starting a counter to count the number of iterations of the target custom function;

If the number of iterations of any of the target custom functions is greater than the iteration threshold, the interpreter is reset.
A Jmeter-based pressure testing device, comprising:

a target stress test request obtaining module, configured to acquire a target stress test request, where the target stress test request includes at least one original data identifier;

a target custom function obtaining module, configured to acquire a corresponding target custom function based on at least one of the original data identifiers, wherein the target custom function is a function that is not encapsulated by a class;

a target custom function encapsulation module, configured to encapsulate the target custom function into a BeanShell script file;

An initialization module, configured to initialize the BeanShell script file;

The stress test module is used to invoke the target custom function encapsulated in the BeanShell script file for stress testing.
A computer device comprising a memory, a processor, and computer readable instructions stored in the memory and operative on the processor, wherein the processor executes the computer readable instructions as follows step:

Obtaining a target stress test request, the target stress test request including at least one original data identifier;

And acquiring, according to the at least one original data identifier, a corresponding target custom function, where the target custom function is a function that is not encapsulated by the class;

Encapsulating the target custom function into a BeanShell script file;

Initializing the BeanShell script file;

Call the target custom function encapsulated in the BeanShell script file for stress testing.
The computer device according to claim 9, wherein the obtaining the corresponding target custom function based on the at least one of the original data identifiers comprises the following steps:

Obtaining, according to the at least one of the original data identifiers, a custom function corresponding to the original data identifier in the custom function list, as a target custom function;

If any of the original data identifiers are present, a corresponding custom function is not obtained in the custom function list, and a prompt message is sent;

Get the new custom function entered by the user as the target custom function.
A computer apparatus according to claim 10, wherein said processor executes said computer readable instructions after said step of obtaining a newly added custom function input by a user as a target custom function The following steps:

The newly added custom function is associated with the corresponding original data identifier and saved in the custom function list.
The computer device according to claim 9, wherein the encapsulating the target custom function into a BeanShell script file comprises the following steps:

Obtain an existing stress test project, and obtain an average number of calls per target custom function based on an existing stress test project;

A target custom function with an average number of calls greater than a preset number of times is packaged into the BeanShell script file.
The computer apparatus according to claim 12, wherein said target stress test request further comprises a target stress test type;

The obtaining the existing stress test item comprises: acquiring an existing stress test item of the same type of the stress test item and the target stress test type.
The computer apparatus according to claim 12, wherein said existing stress test item comprises an existing stress test type;

The calculating the average number of calls of each target custom function based on the existing stress test item includes the following steps:

Counting the number of calls per target custom function in each of the existing stress test items;

And setting a corresponding weight for each of the existing stress test items based on the correlation between the existing stress test type and the target stress test type;

Weighting and summing the number of calls of each of the target custom functions in different existing stress test items based on the weight of each of the existing stress test items, and obtaining an average of each of the target targets Defines the average number of calls to the function.
The computer device according to claim 13, wherein said calling a custom function encapsulated in a BeanShell script file performs stress testing, and further comprising:

Starting a counter to count the number of iterations of the target custom function;

If the number of iterations of any of the target custom functions is greater than the iteration threshold, the interpreter is reset.
One or more non-transitory readable storage mediums storing computer readable instructions, when executed by one or more processors, cause the one or more processors to perform the following steps:

Obtaining a target stress test request, the target stress test request including at least one original data identifier;

And acquiring, according to the at least one original data identifier, a corresponding target custom function, where the target custom function is a function that is not encapsulated by the class;

Encapsulating the target custom function into a BeanShell script file;

Initializing the BeanShell script file;

Call the target custom function encapsulated in the BeanShell script file for stress testing.
The non-volatile readable storage medium of claim 16, wherein the obtaining the corresponding target custom function based on the at least one of the original data identifiers comprises the following steps:

Obtaining, according to the at least one of the original data identifiers, a custom function corresponding to the original data identifier in the custom function list, as a target custom function;

If any of the original data identifiers are present, a corresponding custom function is not obtained in the custom function list, and a prompt message is sent;

Get the new custom function entered by the user as the target custom function.
The non-volatile readable storage medium according to claim 17, wherein said computer readable instruction is followed by said step of acquiring a newly added custom function input by a user as a target custom function When the plurality of processors are executed, the one or more processors are further configured to perform the following steps:

The newly added custom function is associated with the corresponding original data identifier and saved in the custom function list.
The non-volatile readable storage medium of claim 16, wherein the encapsulating the target custom function into a BeanShell script file comprises the following steps:

Obtain an existing stress test project, and obtain an average number of calls per target custom function based on an existing stress test project;

A target custom function with an average number of calls greater than a preset number of times is packaged into the BeanShell script file.
The non-volatile readable storage medium of claim 19, wherein the target stress test request further comprises a target stress test type;

The obtaining the existing stress test item comprises: acquiring an existing stress test item of the same type of the stress test item and the target stress test type.