Test result analysis method, system and device, medium and program product

Abstract

The invention provides a test result analysis method, system and device, a medium and a program product, and the test result analysis method comprises the steps: carrying out the performance test of a target test object based on a preset performance test method, and obtaining a performance test value of the target test object; determining a performance analysis result of the target test object based on the performance test value, a performance baseline of the target test object and an expected change direction of the performance test value; the expected change direction is used for indicating the size relation between the expected performance test value and the performance baseline; the performance analysis result is used for indicating the performance change trend of the target test object. The efficiency and accuracy of test result analysis can be improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a test result analysis method, system, device, medium and program product. Background Art

[0002] In the process of software development and maintenance, software performance testing is a key link to ensure that the software runs stably and efficiently. Currently, the software to be tested can be performance tested through preset test cases to obtain performance test results (such as software response time, throughput, and resource utilization). By analyzing the software performance test results, it can be determined whether the software performance meets the requirements or software defects can be discovered.

[0003] At present, the existing test result analysis methods mainly analyze the performance test results manually. However, because the performance test result analysis usually involves a large amount of data analysis, human judgment, etc., it is easy to cause the omission or misjudgment of important information. Therefore, the existing test result analysis methods have the problems of low efficiency and poor accuracy. Summary of the invention

[0004] The present application provides a test result analysis method, system, device, medium and program product, which can improve the efficiency and accuracy of test result analysis.

[0005] In a first aspect, the present application provides a test result analysis method, the method comprising:

[0006] Based on a preset performance testing method, a performance test is performed on a target test object to obtain a performance test value of the target test object;

[0007] Based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value, a performance analysis result of the target test object is determined; the performance analysis result is used to indicate the performance change trend of the target test object; the expected change direction is used to indicate the expected size relationship between the performance test value and the performance baseline.

[0008] Optionally, determining the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value includes:

[0009] Based on the performance test value and the performance baseline, determining a deviation amount of the performance test value from the performance baseline;

[0010] In response to the deviation being outside a preset deviation range, the performance analysis result is determined based on the deviation and the expected change direction.

[0011] Optionally, a first preset deviation on a first boundary of the preset deviation range is a negative value, and a second preset deviation on a second boundary of the preset deviation range is a positive value, and determining the performance analysis result based on the deviation and the expected change direction includes:

[0012] In response to the deviation being greater than the second preset deviation, and the expected change direction being used to indicate that the performance test value is expected to be greater than the performance baseline, determining that the performance analysis result is used to characterize a performance improvement of the target test object;

[0013] or,

[0014] In response to the deviation being less than the first preset deviation, and the expected change direction indicating that the performance test value is expected to be less than the performance baseline, determining the performance analysis result to characterize the performance improvement of the target test object.

[0015] Optionally, determining the performance analysis result based on the deviation and the expected change direction includes:

[0016] In response to the deviation being less than the first preset deviation, and the expected change direction being used to indicate that the performance test value is expected to be greater than the performance baseline, determining that the performance analysis result is used to characterize a performance degradation of the target test object;

[0017] or,

[0018] In response to the deviation being greater than the second preset deviation, and the expected change direction indicating that the performance test value is expected to be less than the performance baseline, determining the performance analysis result is used to characterize the performance degradation of the target test object.

[0019] Optionally, the method further includes:

[0020] In response to the deviation being within the preset deviation range, determining that the performance analysis result is used to characterize that the performance of the target test object is unchanged.

[0021] Optionally, before determining the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value, the method further includes:

[0022] Based on the performance test value, determining the performance test variance of the target test object;

[0023] The determining of the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value includes:

[0024] When the performance test variance is within a preset variance range, a performance analysis result of the target test object is determined based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value.

[0025] In a second aspect, the present application provides a test result analysis method, the method comprising:

[0026] Receive a test instruction for instructing to perform a performance test on a target test object; the test instruction includes: a performance baseline of the target test object, and an expected change direction; the expected change direction is used to indicate a magnitude relationship between an expected performance test value and the performance baseline;

[0027] Based on a preset performance testing method, a performance test is performed on the target test object to obtain a performance test value of the target test object;

[0028] Determine a performance analysis result of the target test object based on the performance test value, the performance baseline, and the expected change direction; the performance analysis result is used to indicate a performance change trend of the target test object;

[0029] Output a test report; the test report includes: the performance analysis result.

[0030] Optionally, the target test object is a target operating system or a target application program.

[0031] In a third aspect, the present application provides a test result analysis device, the device comprising:

[0032] A testing module, used to perform a performance test on a target test object based on a preset performance testing method, and obtain a performance test value of the target test object;

[0033] A processing module is used to determine a performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value; the performance analysis result is used to indicate the performance change trend of the target test object; the expected change direction is used to indicate the size relationship between the expected performance test value and the performance baseline.

[0034] In a fourth aspect, the present application provides a test result analysis device, the device comprising:

[0035] A receiving module, used to receive a test instruction for instructing to perform a performance test on a target test object; the test instruction includes: a performance baseline of the target test object, and an expected change direction; the expected change direction is used to indicate a magnitude relationship between an expected performance test value and the performance baseline;

[0036] A testing module, used to perform a performance test on the target test object based on a preset performance testing method to obtain a performance test value of the target test object;

[0037] A processing module, configured to determine a performance analysis result of the target test object based on the performance test value, the performance baseline, and the expected change direction; the performance analysis result is used to indicate a performance change trend of the target test object;

[0038] The output module is used to output a test report; the test report includes: the performance analysis result.

[0039] In a fifth aspect, the present application provides a performance testing system, the performance testing system comprising: a client, and a server;

[0040] The client is used to receive a test instruction and send the test instruction to the server; the test instruction is used to instruct to perform a performance test on a target test object; the test instruction includes: a performance baseline of the target test object, and an expected change direction; the expected change direction is used to indicate the size relationship between an expected performance test value and the performance baseline;

[0041] The server is used to perform a performance test on the target test object based on a preset performance test method to obtain a performance test value of the target test object; determine a performance analysis result of the target test object based on the performance test value, the performance baseline, and the expected change direction; output a test report through the client; the test report includes: the performance analysis result; the performance analysis result is used to indicate the performance change trend of the target test object.

[0042] In a sixth aspect, the present application provides an electronic device, comprising: a processor and a memory; the processor is communicatively connected to the memory;

[0043] The memory stores computer-executable instructions;

[0044] The processor executes the computer-executable instructions stored in the memory to implement the method as described in any one of the first aspect and / or the second aspect.

[0045] In a seventh aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method as described in any one of the first aspect and / or the second aspect.

[0046] In an eighth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the method described in any one of the first aspect and / or the second aspect.

[0047] The test result analysis method, system, device, medium and program product provided by the present application can automatically determine the performance analysis result of the target test object based on the performance test value, the performance baseline, and the expected change direction of the performance test value after the target test object is subjected to automated performance testing based on the preset performance test method to obtain the performance test value. Through the above method, the performance analysis result is automatically determined based on the performance test value, the performance baseline and the expected change direction, without the need for manual analysis of the test results, thereby improving the efficiency of the test result analysis, and by reducing the reliance on human judgment and human experience, the accuracy of the test result analysis is improved. In addition, through the above performance baseline and expected change direction, the quantitative analysis of the performance test value is realized, which reduces the subjective analysis differences between different manual workers, thereby also improving the consistency of the test result analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0049] Figure 1 A flow chart of a test result analysis method provided in this application;

[0050] Figure 2 A schematic flow chart of a method for determining a performance analysis result based on an expected change direction of a performance test value provided in the present application;

[0051] Figure 3 A flow chart of a test result analysis method provided in this application;

[0052] Figure 4 A schematic diagram of the architecture of a performance testing system provided for this application;

[0053] Figure 5 A functional schematic diagram of a test task module provided for this application;

[0054] Figure 6 A functional schematic diagram of a baseline management module provided for this application;

[0055] Figure 7 A functional schematic diagram of an execution module provided for this application;

[0056] Figure 8 A functional schematic diagram of a result analysis module provided in this application;

[0057] Fig. 9 A schematic diagram of the structure of a test result analysis device provided in this application;

[0058] Fig.10 A schematic diagram of the structure of another test result analysis device provided by the present application;

[0059] Fig.11 A schematic diagram of the hardware structure of an electronic device provided in this application.

[0060] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0062] By performing performance testing on the software, you can ensure that the software runs stably and efficiently under high load conditions. The analysis of performance test results is the basis for determining whether the software can run stably and efficiently.

[0063] At present, the analysis of performance test results is mainly done manually. However, because the analysis of performance test results usually involves a large amount of data analysis, the existing methods of manually analyzing test results have the problem of low efficiency. When the efficiency of test result analysis is low, it will lead to the problem of being unable to analyze the test results in real time, which may easily lead to the omission or misjudgment of important information. Furthermore, the manual analysis of test results relies on human judgment and the accumulation of human experience, which will lead to highly subjective analysis results and lack of consistency and accuracy of the analysis results.

[0064] Taking into account the above-mentioned problems existing in the existing test result analysis methods, the present application proposes an automated test result analysis method, which does not require manual analysis of the test results, improves the efficiency of the test result analysis, and reduces the reliance on human judgment and human experience, thereby improving the analysis consistency and accuracy of the test results.

[0065] Optionally, the execution subject of the test result analysis method provided by the present application can be, for example, any electronic device with processing capabilities such as a server or a terminal device. Alternatively, the execution subject of the test result analysis method can also be, for example, a performance testing system (or a performance testing platform). Among them, the performance testing system can, for example, be partially (or completely) deployed in a server or a server cluster or a cloud environment, and the present application does not limit this. In some embodiments, the cloud service platform can also provide users with the test result analysis method described in any embodiment of the present application by providing performance testing services.

[0066] The following uses the performance test system as an example to describe the technical solution of the present application in detail in combination with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0067] Figure 1 A flow chart of a test result analysis method provided in this application. Figure 1 As shown, the method may include the following steps:

[0068] S101. Based on a preset performance testing method, a performance test is performed on a target test object to obtain a performance test value of the target test object.

[0069] Exemplarily, the target test object may be, for example, an operating system (e.g., an operating system of a mobile phone or a computer), or computer software such as an application (Application, APP). It should be understood that the present application does not limit the type of the target test object. For example, the target test object may also be a section of code to be tested.

[0070] Exemplarily, the above-mentioned performance testing method may be pre-configured in the performance testing system. Optionally, the performance testing method may be any existing performance testing method capable of performing automated testing on the target test object. For example, the performance testing method may include: according to the test task, the priority of the test case, etc., calling the test case to perform performance testing on the target test object to obtain the performance test value.

[0071] Exemplarily, the above-mentioned performance test value may refer to a performance test value obtained by performing a performance test on any test item of the target test object. Among them, the test items of different target test objects may be the same or different, and the present application does not limit this. Exemplarily, the above-mentioned test items may be, for example, response time, throughput, resource utilization, error rate, etc. Correspondingly, taking the test item of response time as an example, the above-mentioned performance test value may be, for example, the response time of the target test object obtained by performing a performance test on the target test object through the test case of "used to test the response time of the target test object".

[0072] Optionally, the performance testing system may, for example, respond to a test instruction triggered by a user to instruct the target test object to perform a performance test, execute the preset performance testing method, perform a performance test on the target test object, and obtain the process of the performance test value of the target test object. Alternatively, the performance testing system may, for example, also periodically execute the preset performance testing method, perform a performance test on the target test object, and obtain the process of the performance test value of the target test object.

[0073] S102: Determine a performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value.

[0074] Optionally, the above performance baseline may refer to, for example, a reference value of a performance indicator of a target test object in a given test condition (also referred to as a test environment). Exemplarily, the test condition may include, for example: the machine on which the target test object is deployed (for example, if the target test object is an operating system, the computer on which the operating system is deployed may be the test condition of the operating system), the network environment in which the target test object is located, etc. It should be understood that the performance baselines corresponding to different test items may be different or the same.

[0075] In some embodiments, the performance baseline may be, for example, a performance baseline pre-stored in the performance testing system. For example, the performance testing system may determine the performance baseline corresponding to the test item of the target test object based on a mapping relationship among the target test object, the test item, and the performance baseline.

[0076] Exemplarily, the mapping relationship among the target test object, the test items and the performance baseline may be as shown in the following Table 1:

[0077] Table 1

[0078]

[0079] For example, if the target test object is test object 1 and the test item is test item 2, as shown in Table 1, the performance baseline may be performance baseline 12.

[0080] Alternatively, in some embodiments, the performance testing system may also obtain performance test values ​​based on historical tests of the target test object to determine the performance baseline of the target test object. For example, the performance testing system may use the average of multiple historical performance test values ​​of the test item of the target test object as the performance baseline of the target test object. Alternatively, the performance testing system may determine the best performance test value that can characterize the performance of the test item of the target test object from multiple historical performance test values ​​of the test item of the target test object as the performance baseline of the target test object.

[0081] Optionally, the above-mentioned expected change direction can be used to indicate the size relationship between the expected performance test value and the performance baseline. It should be understood that the expected change directions corresponding to different test items may be different or the same. For example, taking the three test items of response time, throughput and error rate as an example, the expected change direction corresponding to the response time may be, for example, the expected performance test value is less than the performance baseline (that is, the shorter the response time, the better the performance of the target test object). In addition, the expected change direction corresponding to the error rate may also be, for example, the expected performance test value is less than the performance baseline (that is, the lower the error rate, the better the performance of the target test object). The expected change direction corresponding to the throughput may be, for example, the expected performance test value is greater than the performance baseline (that is, the higher the throughput, the better the performance of the target test object).

[0082] Exemplarily, the performance testing system can determine the expected change direction corresponding to the test item of the target test object through the identification of the target test object, the identification of the test item, and the mapping relationship between the identification of the test object, the identification of the test item, and the expected change direction. Exemplarily, the performance testing system can receive in advance the mapping relationship between the identification of the test object, the identification of the test item, and the expected change direction configured by the user.

[0083] The above performance analysis results can be used to indicate the performance change trend of the target test object. For example, the performance change trend can be performance degradation (ie, performance deterioration) or performance improvement (ie, performance improvement).

[0084] As a possible implementation, the performance testing system may, for example, compare the size relationship between the performance test value and the performance baseline. Then, it is determined whether the size relationship between the performance test value and the performance baseline is the same as the size relationship between the expected performance test value and the performance baseline indicated by the above-mentioned expected change direction. If they are the same, the performance testing system may, for example, determine that the performance analysis result can be used to indicate an improvement in the performance of the target test object. If they are different, the performance testing system may, for example, determine that the performance analysis result can be used to indicate a decrease in the performance of the target test object.

[0085] In this embodiment, after the target test object is subjected to automated performance testing based on a preset performance testing method to obtain a performance test value, the performance analysis result of the target test object can be automatically determined based on the performance test value, the performance baseline, and the expected change direction of the performance test value. Through the above method, the performance analysis result is automatically determined based on the performance test value, the performance baseline, and the expected change direction, without the need for manual analysis of the test results, thereby improving the efficiency of the test result analysis, and by reducing the reliance on human judgment and human experience, the accuracy of the test result analysis is improved. In addition, through the above performance baseline and expected change direction, a quantitative analysis of the performance test value is achieved, which reduces the subjective analysis differences between different humans, thereby also improving the consistency of the test result analysis.

[0086] The following is a detailed description of how the performance test system determines the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value:

[0087] As a possible implementation, Figure 2 A flow chart of a method for determining performance analysis results based on the expected change direction of performance test values ​​provided in this application. Figure 2 As shown, the method may include the following steps:

[0088] S201. Based on a performance test value and a performance baseline, determine a deviation amount of the performance test value from the performance baseline.

[0089] Optionally, the above deviation can be used to characterize the deviation between the performance test value and the performance baseline. Exemplarily, the larger the deviation, the more the performance test value deviates from the performance baseline. The smaller the deviation, the less the performance test value deviates from the performance baseline.

[0090] Exemplarily, the performance test system may, for example, subtract the performance test value from the performance baseline to obtain a difference, divide the difference by the performance baseline, and divide the difference by the performance baseline to obtain a quotient as the deviation of the performance test value from the performance baseline. For example, refer to the following formula (1):

[0091] Deviation = (performance test value - performance baseline) / performance baseline (1)

[0092] In some embodiments, the deviation can be expressed as a percentage, for example, assuming that the deviation obtained by the above formula (1) is 0.02, it can be converted into a percentage, that is, 2%.

[0093] S202: In response to the deviation being outside a preset deviation range, determine a performance analysis result based on the deviation and an expected change direction.

[0094] Exemplarily, the preset deviation range can be used to characterize the variation range of the deviation when the performance of the target test object is stable. Exemplarily, the performance test system can determine the preset deviation range corresponding to the test item of the target test object through the identification of the target test object, the identification of the test item, and the mapping relationship between the identification of the test object, the identification of the test item and the preset deviation range.

[0095] Exemplarily, the mapping relationship between the identification of the test object, the identification of the test item and the preset deviation range may be as shown in the following Table 2:

[0096] Table 2

[0097]

[0098] Taking the target test object as test object 1 and the test item as test item 2 as an example, as shown in Table 2, the preset deviation range may be preset deviation range 12.

[0099] Taking the example that the first preset deviation on the first boundary of the preset deviation range is a negative value, and the second preset deviation on the second boundary of the preset deviation range is a positive value (that is, the minimum value in the preset deviation range is the first preset deviation, the maximum value in the preset deviation range is the second preset deviation, and the values ​​in the preset deviation range are all greater than the above-mentioned first preset deviation and less than the second preset deviation), in some embodiments, the performance testing system can, for example, determine the above-mentioned performance analysis results based on the size relationship between the deviation and the first preset deviation or the second preset deviation, and the expected change direction.

[0100] For example, the performance testing system may determine that the performance analysis result is used to characterize the performance improvement of the target test object in response to the deviation being greater than the second preset deviation and the expected change direction indicating that the expected performance test value is greater than the performance baseline.

[0101] When the above-mentioned deviation is greater than the above-mentioned second preset deviation, it means that the deviation is outside the preset deviation range, and because the expected change direction is used to indicate that the expected performance test value is greater than the performance baseline, it means that the larger the performance test value is, the better the performance of the target test object is. Therefore, under the expected change direction, when the deviation is greater than the above-mentioned second preset deviation, it means that the performance test value is much better than expected, that is, the performance testing system can determine the performance analysis results to characterize the performance improvement of the target test object.

[0102] For example, taking the above deviation amount as a percentage, the preset deviation amount range can also be expressed as a percentage range. Taking 5% as an example (that is, the first preset deviation is -5%, and the second preset deviation is +5%), if the deviation is greater than +5%, and the expected change direction is used to indicate that the expected performance test value is greater than the performance baseline, then the performance testing system can determine that the above performance analysis results are used to characterize the performance improvement of the target test object.

[0103] Alternatively, the performance testing system may also determine, in response to the deviation being less than a first preset deviation and the expected change direction indicating that the expected performance test value is less than the performance baseline, that the performance analysis result is used to characterize the performance improvement of the target test object.

[0104] When the above-mentioned deviation is less than the above-mentioned first preset deviation, it means that the deviation is outside the preset deviation range, and because the expected change direction is used to indicate that the expected performance test value is less than the performance baseline, it means that the smaller the performance test value, the better the performance of the target test object. Therefore, under the expected change direction, when the deviation is less than the above-mentioned first preset deviation, it means that the performance test value is much better than expected, that is, the performance testing system can determine the performance analysis results to characterize the performance improvement of the target test object.

[0105] For example, the preset deviation range is still Taking 5% as an example, if the deviation is less than -5%, and the expected change direction is used to indicate that the expected performance test value is less than the performance baseline, the performance testing system can determine that the above performance analysis results are used to characterize the performance improvement of the target test object.

[0106] In some embodiments, the performance testing system may also determine a performance analysis result for characterizing a performance degradation of a target test object in response to a deviation less than a first preset deviation and an expected change direction indicating that an expected performance test value is greater than a performance baseline.

[0107] When the above-mentioned deviation is less than the above-mentioned first preset deviation, it means that the deviation is outside the preset deviation range, and because the expected change direction is used to indicate that the expected performance test value is greater than the performance baseline, the smaller the performance test value is, the worse the performance of the target test object is. Therefore, under the expected change direction, when the deviation is less than the above-mentioned first preset deviation, it means that the performance test value is far worse than expected, that is, the performance testing system can determine the performance analysis results to characterize the performance degradation of the target test object.

[0108] For example, the preset deviation range is still Taking 5% as an example, if the deviation is less than -5%, and the expected change direction is used to indicate that the expected performance test is greater than the performance baseline, the performance testing system can determine that the above performance analysis results are used to characterize the performance degradation of the target test object.

[0109] Alternatively, the performance testing system may also determine, in response to a deviation greater than a second preset deviation and an expected change direction indicating that an expected performance test value is less than a performance baseline, that a performance analysis result is used to characterize a performance degradation of a target test object.

[0110] When the above-mentioned deviation is greater than the above-mentioned second preset deviation, it means that the deviation is outside the preset deviation range, and because the expected change direction is used to indicate that the expected performance test value is less than the performance baseline, it means that the larger the performance test value is, the worse the performance of the target test object is. Therefore, under the expected change direction, when the deviation is greater than the above-mentioned second preset deviation, it means that the performance test value is far worse than expected, that is, the performance testing system can determine the performance analysis results to characterize the performance degradation of the target test object.

[0111] For example, the preset deviation range is still Taking 5% as an example, if the deviation is greater than +5%, and the expected change direction is used to indicate that the expected performance test is less than the performance baseline, the performance testing system can determine that the above performance analysis results are used to characterize the performance degradation of the target test object.

[0112] In some embodiments, if the deviation is within a preset deviation range, indicating that the performance test value is close to the performance baseline, the performance testing system can determine that the performance analysis result used to characterize the target test object has not changed.

[0113] Exemplarily, taking the first boundary of the above-mentioned preset deviation range as the above-mentioned first preset deviation, and the second boundary as the above-mentioned second preset deviation, the performance testing system can, for example, determine that the deviation is within the preset deviation range when the above-mentioned deviation is greater than or equal to the first preset deviation, and less than or equal to the second preset deviation.

[0114] Through the above method, when the deviation is within the preset deviation range, it can be determined that the performance of the target test object has not changed, thereby improving the flexibility of the test result analysis for the target test object.

[0115] In this embodiment, the deviation of the performance test value from the performance baseline can be determined through the performance test value and the performance baseline, and when the deviation is outside the preset deviation range, the performance analysis result is determined based on the deviation and the expected change direction, thereby realizing automated analysis of performance test results based on the performance test value and the expected change direction, realizing quantitative analysis of performance test results, and improving the consistency and standardization of test result analysis.

[0116] As another possible implementation method, before the performance testing system determines the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value, for example, the method may also first determine whether the performance test value is an outlier based on the performance test variance of the target test object, and when it is determined that the performance test value is not an outlier, execute the subsequent process of automatically determining the performance analysis result, so as to further improve the accuracy of the automated determination of the performance analysis result.

[0117] Optionally, the performance testing system may determine the performance testing variance of the target test object based on the performance testing value, for example.

[0118] It should be understood that the performance test system determines the performance test variance of the target test object based on the performance test value, for example, by referring to any existing variance calculation method. For example, the performance test system can obtain the performance test variance of the target test object based on the historical performance test value of the target test object and the performance test value.

[0119] Then, when the performance test variance is within a preset variance range, the performance test system may determine a performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value.

[0120] Optionally, the performance testing system may, for example, pre-receive the preset variance range configured by the user.

[0121] When the performance test variance is within the preset variance range, it indicates that the performance test value is within the normal value range, and the performance test system executes the subsequent process of automatically determining the performance analysis result, further improving the accuracy of the automatically determined performance analysis result.

[0122] In some embodiments, if the above-mentioned performance test variance is outside the preset variance range, it means that the above-mentioned performance test value makes the performance test result of the target test object too discrete, that is, the performance test value is not credible. Therefore, the performance test system may, for example, not perform the step of "determining the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value". Optionally, the performance test system may, for example, output a prompt message indicating a performance test abnormality when the above-mentioned performance test variance is outside the preset variance range.

[0123] Alternatively, in some embodiments, the performance testing system may not need to determine the performance test variance of the target test object. For example, the performance testing system may respond to a test instruction for instructing to perform a performance test on the target test object and execute the aforementioned step S101 and other steps to implement automated test result analysis.

[0124] The present application also provides another test result analysis method. The execution subject of the test result analysis method can be the same execution subject as the execution subject of the aforementioned test result analysis method, or can be a different execution subject, which is not limited by the present application.

[0125] The following takes the execution subject of the test result analysis method as a performance test system as an example to illustrate the test result analysis method:

[0126] Figure 3 A flow chart of a test result analysis method provided in this application. Figure 3 As shown, the method may include the following process, for example:

[0127] S301: Receive a test instruction for instructing to perform a performance test on a target test object.

[0128] The test instruction may include: a performance baseline of the target test object, and an expected change direction of the performance test value. The expected change direction may be used to indicate the magnitude relationship between the expected performance test value and the performance baseline.

[0129] Exemplarily, the performance testing system may receive the test instruction through an application programming interface (API) or a graphical user interface (GUI).

[0130] S302: Perform a performance test on a target test object based on a preset performance test method to obtain a performance test value of the target test object.

[0131] S303: Determine the performance analysis result of the target test object based on the performance test value, the performance baseline, and the expected change direction.

[0132] The performance analysis result is used to indicate the performance change trend of the target test object.

[0133] Optionally, the performance testing system executes the above steps S302 and S303 in an implementation manner, for example, by referring to the method described in any of the above embodiments, which will not be described in detail here.

[0134] S304: Output a test report.

[0135] The test report may include: the above-mentioned performance analysis results.

[0136] Exemplarily, the performance test system can output the test report by sending the test report to the user terminal. Alternatively, taking the performance test system including a client and the client being deployed on the user terminal as an example, the performance test system can output the test report by displaying the test report through the client.

[0137] In this embodiment, the performance test system can receive the performance baseline and the expected change direction, so that the performance test result analysis can be performed automatically based on the performance baseline and the expected change direction. Through the user's configuration of the above performance baseline and the expected change direction, the automated performance test result analysis is realized, the efficiency and accuracy of the test result analysis are improved, and the flexibility of the test result analysis is improved. Then, by outputting a test report including the performance analysis results, the user can view the test report in time, which improves the user experience.

[0138] Exemplarily, the target test object may be, for example, a target operating system or a target application program.

[0139] Taking the target test object as a target operating system as an example, the performance testing system can, for example, receive a test instruction for instructing to perform a performance test on the target operating system. The test instruction can include: a performance baseline of the target operating system, and an expected change direction of the performance test value. The expected change direction can be used to indicate the size relationship between the expected performance test value and the performance baseline. Then, the performance testing system can perform a performance test on the target operating system based on the preset performance testing method to obtain a performance test value of the target operating system.

[0140] The performance test system can determine the performance analysis result of the target operating system based on the performance test value, the performance baseline, and the expected change direction, and output a test report, wherein the performance analysis result is used to indicate the performance change trend of the target operating system.

[0141] Taking the target test object as a target application as an example, the performance testing system can, for example, receive a test instruction for instructing to perform a performance test on the target application. The test instruction can include: a performance baseline of the target application, and an expected change direction of the performance test value. The expected change direction can be used to indicate the size relationship between the expected performance test value and the performance baseline. Then, the performance testing system can perform a performance test on the target application based on the preset performance testing method to obtain a performance test value of the target application.

[0142] The performance testing system can determine the performance analysis result of the target application based on the performance test value, the performance baseline, and the expected change direction, and output a test report, wherein the performance analysis result is used to indicate the performance change trend of the target application.

[0143] Figure 4 This is a schematic diagram of the architecture of a performance testing system provided in this application. Figure 4 As shown, the performance testing system may include: a test task module, a baseline management module, an execution module and a result analysis module.

[0144] The test task module is mainly used to create test tasks and execute periodic plans. Among them, the creation of test tasks can, for example, support the creation of single tasks and batch tasks, as well as the creation of test plan tasks. The test plan can be used to define a series of automated actions in advance, and then the performance test system can periodically execute performance test tasks, such as regularly creating tasks, triggering task execution, etc.

[0145] The baseline management module can be used to establish a performance baseline and set the fluctuation range and expected direction of each indicator of the performance test suite in the baseline, so that automatic analysis of the performance test results can be performed later.

[0146] The task execution module can be used to uniformly schedule and execute test tasks, and perform serial, parallel, and single-machine cluster scheduling based on the test suite priority in the test task.

[0147] The result analysis module can be used to collect performance results, determine the baseline fluctuation range, and automatically generate test reports, and feed back the test reports to testers and developers.

[0148] Figure 5 This is a functional diagram of a test task module provided by this application. The test task module is mainly divided into two parts: test task creation and test plan execution. Figure 5 As shown, the test task creation can be divided into single task creation and multi-task creation. The test task module can execute the following process:

[0149] 1. Single task creation: supports multiple methods such as web page creation and API creation. For example, you can create tasks of different test types such as functional testing, performance testing, compatibility testing, and security testing. Web pages can also be created directly according to pre-configured templates, or using creation items of different test task (Job) types or templates. API creation, for example, can support the creation of batch test tasks.

[0150] 2. Multi-task creation: mainly implemented by test plan creation and API creation.

[0151] 3. Test plan: It can be a set of pre-written test tasks, including task creation, task execution, etc.

[0152] Figure 6 This is a functional diagram of a baseline management module provided in this application. Figure 6 As shown, baseline management includes functions such as establishing performance baselines, setting fluctuation ranges, and setting expected directions. The baseline management module can execute the following processes:

[0153] 1. Establish performance baselines: Users can create (add) baselines, edit baselines, query baselines, and delete baselines in baseline management, and can specify different versions of baselines based on different product development versions.

[0154] 2. Set the fluctuation range: The fluctuation range mainly includes two important indicators: the preset deviation range and the preset variance range. The preset deviation range can be determined based on the average value of historical performance test results, for example, and can be used to determine the quality of performance test values. The preset variance range (also called CV threshold) is the benchmark for variance judgment, which can be used to determine the degree of dispersion of performance test values ​​and avoid excessive deviation of performance test values.

[0155] 3. Set the expected direction (expected change direction): The expected direction can be divided into two directions: rising and falling. When the expected direction is rising, the larger the performance test value is within the reasonable preset variance range, the better. When the expected direction is falling, the smaller the performance test value is within the reasonable preset variance range, the better.

[0156] Figure 7 This is a functional diagram of an execution module provided by this application. Figure 7 As shown, the execution module can be used for unified scheduling and execution of test suites. During scheduling, for example, a scheduling strategy can be assigned according to the test suite's priority, serial and parallel operation mode, single machine or distributed operation architecture and other attributes. The execution module can, for example, execute the following process:

[0157] 1. Unified scheduling and execution of integrated test suites, for example, scheduling by job, i.e., a test task includes one or more test suites, and one or more test suites can be run at the same time. Or, scheduling by test suite, i.e., a test suite includes one or more test suite cases, and one or more test suite cases can be run at the same time. Or, scheduling by test suite case, i.e., running a single test suite case at a time.

[0158] 2. Arrange the test sequence reasonably according to the priority and dependency set by the user. Taking priority as an example, each test suite can have a corresponding priority, and the test suite with a higher priority will be scheduled first (such as Figure 7As shown in the figure, test suite 1 with priority 10 is executed before test suite 2 with priority 8, and test suite 2 with priority 8 is executed before test suite 4 with priority 3). Taking dependency as an example, there may be top-to-bottom dependencies between test suites and between test suite cases. During scheduling, they need to be sorted according to the dependencies to ensure that the dependent test suites are executed first.

[0159] 3. Support parallel and distributed test execution to improve test performance. Taking serial and parallel as an example, the test suites running in series will be added to the sequential queue and run in sequence, and the test suites running in parallel will be scheduled in parallel (such as Figure 7 As shown, the test suite 1 on a single machine is processed in parallel with the test suite 2 on a distributed cluster. Test suites 1, 3, and 4 can be executed serially. When allocating a test machine, a single test suite will be allocated to one test machine. When allocating a machine, a distributed test suite (such as test suite 2 and test suite 4) will be allocated a cluster containing multiple test machines.

[0160] Figure 8 This is a functional diagram of a result analysis module provided in this application. The result analysis module can be divided into test result collection, indicator result fluctuation determination, report automatic generation, feedback and other modules, and the specific examples can be as follows:

[0161] 1. Collect indicator results, such as collecting preset deviation ranges, preset variance ranges, execution logs, and other information.

[0162] 2. Determination of index results: First, the deviation is obtained by, for example, the aforementioned formula (1). Then, the performance analysis result is obtained based on the deviation, the preset deviation range, the preset variance range, etc.

[0163] The performance analysis results include, for example, performance improvement, performance degradation, normal performance, test invalidity, and failure to detect the performance baseline. Specifically, when the variance of the performance test value calculation is within a preset variance range, the performance test system may perform the following judgment:

[0164] If the deviation is greater than a second preset deviation and is expected to rise (ie, the expected change direction is used to indicate that the expected performance test value is greater than the performance baseline), then the performance analysis result is determined to characterize the performance improvement of the target test object.

[0165] If the deviation is less than the first preset deviation and is expected to decrease (ie, the expected change direction is used to indicate that the expected performance test value is less than the performance baseline), the performance analysis result is determined to be used to characterize the performance improvement of the target test object.

[0166] If the deviation is less than the first preset deviation and is expected to increase, the performance analysis result is determined to be used to characterize the performance degradation of the target test object.

[0167] If the deviation is greater than a second preset deviation and a decrease is expected, the performance analysis result is determined to characterize the performance decrease of the target test object.

[0168] After the performance analysis results are determined, the performance testing system can automatically generate a test report through a pre-specified test plan and send the test report to developers, testers, etc.

[0169] In this embodiment, by establishing a performance indicator baseline, this performance testing system records the standard performance indicators of the performance test suite and sets an allowable fluctuation range for each performance indicator, thereby providing a judgment standard based on quantitative data. By defining the expected change direction of each performance indicator, the system can compare the test results with the baseline and the expected direction after collecting them. If the test results are within the set baseline fluctuation range, or the fluctuation direction is consistent with the expected direction, the system automatically determines that the code change of the target test object is in the positive direction (that is, the performance of the target test object is improved), which helps to confirm and support the development progress. On the contrary, it is determined to be in the negative direction (that is, the performance of the target test object is reduced), so that potential problems of the target test object can be discovered and solved in time in the future. The automation platform supports batch testing and automatic judgment report generation, improves the efficiency of performance problem troubleshooting and resolution, and provides users with the ability to respond quickly. Through this automated judgment system, users can monitor and optimize the performance of the software, thereby reducing potential performance risks and improving the overall quality and user experience of the software.

[0170] Fig. 9 This is a schematic diagram of the structure of a test result analysis device provided in this application. Fig. 9 As shown, the test result analysis device 40 may include: a test module 41 and a processing module 42.

[0171] The testing module 41 is used to perform a performance test on a target test object based on a preset performance test method to obtain a performance test value of the target test object.

[0172] The processing module 42 is used to determine the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value, wherein the performance analysis result is used to indicate the performance change trend of the target test object.

[0173] Optionally, the processing module 42 is specifically used to determine the deviation of the performance test value from the performance baseline based on the performance test value and the performance baseline; in response to the deviation being outside a preset deviation range, determine the performance analysis result based on the deviation and the expected change direction.

[0174] Taking the case where the first preset deviation on the first boundary of the preset deviation range is a negative value, and the second preset deviation on the second boundary of the preset deviation range is a positive value as an example, optionally, the processing module 42 is specifically used to respond to the deviation being greater than the second preset deviation, and the expected change direction is used to indicate that the performance test value is expected to be greater than the performance baseline, and determine that the performance analysis result is used to characterize the performance improvement of the target test object. Alternatively, the processing module 42 is specifically used to respond to the deviation being less than the first preset deviation, and the expected change direction is used to indicate that the performance test value is expected to be less than the performance baseline, and determine that the performance analysis result is used to characterize the performance improvement of the target test object.

[0175] Optionally, the processing module 42 is specifically configured to determine, in response to the deviation being less than the first preset deviation, and the expected change direction being used to indicate that the performance test value is expected to be greater than the performance baseline, that the performance analysis result is used to characterize the performance degradation of the target test object. Alternatively, the processing module 42 is specifically configured to determine, in response to the deviation being greater than the second preset deviation, and the expected change direction being used to indicate that the performance test value is expected to be less than the performance baseline, that the performance analysis result is used to characterize the performance degradation of the target test object.

[0176] Optionally, the processing module 42 is further configured to, in response to the deviation being within the preset deviation range, determine that the performance analysis result is used to characterize that the performance of the target test object has not changed.

[0177] Optionally, the processing module 42 is further used to determine the performance test variance of the target test object based on the performance test value before determining the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value; and to determine the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value when the performance test variance is within a preset variance range.

[0178] The test result analysis device 40 provided in the present application is used to execute the aforementioned test result analysis method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail.

[0179] Fig.10 This is a schematic diagram of the structure of another test result analysis device provided by this application. Fig.10 As shown, the test result analysis device 50 may include: a receiving module 51, a testing module 52, a processing module 53 and an output module 54.

[0180] The receiving module 51 is used to receive a test instruction for instructing to perform a performance test on a target test object, wherein the test instruction includes: a performance baseline of the target test object, and an expected change direction of a performance test value.

[0181] The testing module 52 is used to perform a performance test on the target test object based on a preset performance testing method to obtain a performance test value of the target test object.

[0182] The processing module 53 is used to determine the performance analysis result of the target test object based on the performance test value, the performance baseline, and the expected change direction, wherein the performance analysis result is used to indicate the performance change trend of the target test object.

[0183] The output module 54 is used to output a test report, wherein the test report includes: the performance analysis result.

[0184] The test result analysis device 50 provided in the present application is used to execute the aforementioned test result analysis method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail.

[0185] Fig.11 A schematic diagram of the hardware structure of an electronic device provided in this application. Fig.11 The electronic device 60 shown includes a memory 61, a processor 62, and a communication interface 63. The memory 61, the processor 62, and the communication interface 63 are connected to each other in communication. For example, the memory 61, the processor 62, and the communication interface 63 can be connected to each other through a network connection. Alternatively, the electronic device 60 may further include a bus 64. The memory 61, the processor 62, and the communication interface 63 are connected to each other in communication through the bus 64. Fig.11 The electronic device 60 is a memory 61 , a processor 62 , and a communication interface 63 that are connected to each other via a bus 64 .

[0186] The memory 61 may be a read-only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM). The memory 61 may store a program. When the program stored in the memory 61 is executed by the processor 62, the processor 62 and the communication interface 63 are used to execute the test result analysis method described in any of the aforementioned embodiments. The memory may also store data required by the test result analysis method.

[0187] The processor 62 may be a general-purpose CPU, a microprocessor, an application-specific integrated circuit (ASIC), a graphics processing unit (GPU), or one or more integrated circuits.

[0188] The processor 62 may also be an integrated circuit chip with signal processing capability. In the implementation process, the test result analysis method of the present application may be completed by hardware integrated logic circuits or software instructions in the processor 62. The above-mentioned processor 62 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, and may implement or execute the methods, steps and logic block diagrams disclosed in the following embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in the following embodiments of the present application may be directly embodied as being executed by a hardware decoding processor, or may be executed by a combination of hardware and software modules in a decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 61, and the processor 62 reads the information in the memory 61, and completes the test result analysis method of the present application in combination with its hardware.

[0189] The communication interface 63 uses a transceiver module such as, but not limited to, a transceiver to implement communication between the electronic device 60 and other devices or a communication network. For example, a data set can be acquired through the communication interface 63 .

[0190] When the electronic device 60 includes a bus 64 , the bus 64 may include a path for transmitting information between various components of the electronic device 60 (eg, the memory 61 , the processor 62 , and the communication interface 63 ).

[0191] The present application also provides a performance testing system. The performance testing system may include: a client and a server.

[0192] The client may be used to receive a test instruction and send the test instruction to the server. The test instruction may be used to instruct a performance test to be performed on a target test object. The test instruction may include: a performance baseline of the target test object and an expected change direction. The expected change direction may be used to indicate a magnitude relationship between an expected performance test value and a performance baseline.

[0193] The above server can be used to perform a performance test on the target test object based on a preset performance test method to obtain a performance test value of the target test object. Then, the server can determine the performance analysis result of the target test object based on the performance test value, the performance baseline, and the expected change direction, and output a test report through the client. The test report includes: performance analysis results. The performance analysis results are used to indicate the performance change trend of the target test object.

[0194] Optionally, the server may, for example, execute a test result analysis method as described in any of the aforementioned embodiments, which will not be described in detail in this application.

[0195] The present application also provides a computer-readable storage medium, which may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes. Specifically, the computer-readable storage medium stores program instructions, and the program instructions are used for the methods in the above embodiments.

[0196] The present application also provides a program product, which includes an execution instruction, which is stored in a readable storage medium. At least one processor of the electronic device can read the execution instruction from the readable storage medium, and at least one processor executes the execution instruction so that the electronic device implements the test result analysis method provided by the various embodiments described above.

[0197] The term "plurality" in this article refers to two or more than two. The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the previous and next associated objects are in an "or" relationship; in the formula, the character " / " indicates that the previous and next associated objects are in a "division" relationship. In addition, it should be understood that in the description of this application, words such as "first" and "second" are only used for the purpose of distinguishing descriptions, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order.

[0198] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0199] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A test result analysis method, characterized in that: The method comprises: Based on a preset performance testing method, a performance test is performed on a target test object to obtain a performance test value of the target test object; Based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value, a performance analysis result of the target test object is determined; the performance analysis result is used to indicate the performance change trend of the target test object; the expected change direction is used to indicate the expected size relationship between the performance test value and the performance baseline.

2. The method according to claim 1, characterized in that The determining of the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value includes: Based on the performance test value and the performance baseline, determining a deviation amount of the performance test value from the performance baseline; In response to the deviation being outside a preset deviation range, the performance analysis result is determined based on the deviation and the expected change direction.

3. The method according to claim 2, characterized in that A first preset deviation on a first boundary of the preset deviation range is a negative value, and a second preset deviation on a second boundary of the preset deviation range is a positive value, and determining the performance analysis result based on the deviation and the expected change direction includes: In response to the deviation being greater than the second preset deviation, and the expected change direction being used to indicate that the performance test value is expected to be greater than the performance baseline, determining that the performance analysis result is used to characterize a performance improvement of the target test object; or, In response to the deviation being less than the first preset deviation, and the expected change direction indicating that the performance test value is expected to be less than the performance baseline, determining the performance analysis result to characterize the performance improvement of the target test object.

4. The method according to claim 3, characterized in that The determining the performance analysis result based on the deviation and the expected change direction includes: In response to the deviation being less than the first preset deviation, and the expected change direction being used to indicate that the performance test value is expected to be greater than the performance baseline, determining that the performance analysis result is used to characterize a performance degradation of the target test object; or, In response to the deviation being greater than the second preset deviation, and the expected change direction indicating that the performance test value is expected to be less than the performance baseline, determining the performance analysis result is used to characterize the performance degradation of the target test object.

5. The method according to any one of claims 2 to 4, characterized in that: The method further comprises: In response to the deviation being within the preset deviation range, determining that the performance analysis result is used to represent that the performance of the target test object is unchanged.

6. The method according to any one of claims 1 to 4, characterized in that: Before determining the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value, the method further includes: Based on the performance test value, determining the performance test variance of the target test object; The determining of the performance analysis result of the target test object based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value includes: When the performance test variance is within a preset variance range, a performance analysis result of the target test object is determined based on the performance test value, the performance baseline of the target test object, and the expected change direction of the performance test value.

7. A test result analysis method, characterized in that: The method comprises: Receive a test instruction for instructing to perform a performance test on a target test object; the test instruction includes: a performance baseline of the target test object, and an expected change direction; the expected change direction is used to indicate a magnitude relationship between an expected performance test value and the performance baseline; Based on a preset performance testing method, a performance test is performed on the target test object to obtain a performance test value of the target test object; Determine a performance analysis result of the target test object based on the performance test value, the performance baseline, and the expected change direction; the performance analysis result is used to indicate a performance change trend of the target test object; Output a test report; the test report includes: the performance analysis result.

8. The method according to claim 7, characterized in that The target test object is a target operating system or a target application program.

9. A performance testing system, characterized in that: The performance testing system comprises: a client, and a server; The client is used to receive a test instruction and send the test instruction to the server; the test instruction is used to instruct to perform a performance test on a target test object; the test instruction includes: a performance baseline of the target test object, and an expected change direction; the expected change direction is used to indicate the size relationship between an expected performance test value and the performance baseline; The server is used to perform a performance test on the target test object based on a preset performance test method to obtain a performance test value of the target test object; determine a performance analysis result of the target test object based on the performance test value, the performance baseline, and the expected change direction; and output a test report through the client; the test report includes: the performance analysis result; the performance analysis result is used to indicate the performance change trend of the target test object.

10. An electronic device, characterized in that: include: Processor and memory; The processor is communicatively connected to the memory; The memory stores computer instructions; The processor executes the computer instructions stored in the memory to implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

12. A computer program product, characterized in that The computer program product comprises a computer program, which implements the method according to any one of claims 1 to 8 when executed by a processor.

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