Pressure test processing method and device

Abstract

The present disclosure provides a stress test processing method, which is applied to the field of financial technology, and the method includes: in response to a received automatic test instruction, triggering N stress tests of the test object in M ​​test scenarios, wherein M is an integer greater than 1 and N is an integer not less than M; monitoring the preset performance indicators associated with the test object during each stress test to obtain N groups of performance indicator data; for the N groups of performance indicator data, associating the performance indicator data corresponding to each of the test scenarios to obtain the associated performance indicator data; generating a stress test report for the test object based on the associated performance indicator data. The present disclosure also provides a stress test processing device, an electronic device, and a computer storage medium.

Description

Technical Field

[0001] The present disclosure relates to the field of financial technology, and in particular to a stress testing processing method, system and device. Background Art

[0002] With the rapid development of computer technology, more and more diverse Internet technologies are being applied to the financial field. The financial field has higher standards for the security and real-time performance of business operations. Stress testing is one of the important means to ensure the security of financial business operations and improve the real-time performance of financial business operations.

[0003] In the process of implementing the technical solution disclosed in the present invention, the inventor discovered that in the relevant stress testing technology, the stress testing operation relies on manually configuring the stress testing scenario. In addition, with the increase in performance scenarios in the financial field and the improvement in the accuracy requirements of performance indicators, the amount of performance indicator data sampled during the stress testing process is often large, and the correlation between different performance indicator data is weak. When analyzing the stress testing results based on the performance indicator data, there are problems such as large data analysis workload and low analysis efficiency, all of which will affect the efficiency of the stress testing and damage the effect of the stress testing. Summary of the invention

[0004] One aspect of the present disclosure provides a stress test processing method, including: in response to a received automatic test instruction, triggering N stress tests of a test object in M ​​test scenarios, wherein M is an integer greater than 1 and N is an integer not less than M; monitoring preset performance indicators associated with the test object during each of the stress tests to obtain N groups of performance indicator data; for the N groups of performance indicator data, associating the performance indicator data corresponding to each of the test scenarios to obtain associated performance indicator data; and generating a stress test report for the test object based on the associated performance indicator data.

[0005] Optionally, in response to the received automatic test instruction, triggering N stress tests on the test object in M ​​test scenarios includes: in response to the received automatic test instruction, obtaining M groups of test parameters for stress testing the test object, the test parameters including test scenario parameters and test flow parameters; based on the test scenario parameters in each of the test parameters, determining M test scenarios for stress testing the test object; based on the test flow parameters in each of the test parameters, determining the test flow value associated with each of the M test scenarios; and performing N stress tests on the test object according to the test flow value associated with each of the M test scenarios.

[0006] Optionally, determining M test scenarios for stress testing the test object based on the test scenario parameters in each of the test parameters includes: determining at least one operation event for stress testing the test object in each of the M test scenarios based on the test scenario parameters in each of the test parameters; determining the test flow value associated with each of the M test scenarios based on the test flow parameters in each of the test parameters includes: determining the concurrency number associated with each of the operation events in each of the test scenarios based on the test flow parameters in each of the test parameters.

[0007] Optionally, for the N groups of performance indicator data, the performance indicator data corresponding to each of the test scenarios are associated to obtain the associated performance indicator data, including: performing attribute feature extraction for the M test scenarios to obtain scene attribute features associated with each of the test scenarios; performing attribute feature extraction for the N groups of performance indicator data to obtain test attribute features associated with each of the performance indicator data; using the scene attribute features associated with each of the test scenarios to filter the test attribute features to obtain test attribute features corresponding to each of the test scenarios; and according to the test attribute features corresponding to each of the test scenarios, associating the performance indicator data corresponding to each of the test scenarios to obtain the associated performance indicator data.

[0008] Optionally, the extracting of attribute features for the M test scenarios to obtain scenario attribute features associated with each of the test scenarios includes: extracting attribute features for each of the test scenarios to determine operation event features associated with each of the test scenarios as the scenario attribute features; the extracting of attribute features for the N groups of performance indicator data to obtain test attribute features associated with each of the performance indicator data includes: extracting attribute features for each of the performance indicator data to determine event attribute features of at least one operation event performed during the corresponding stress test as the test attribute features.

[0009] Optionally, after obtaining the associated performance indicator data, it also includes: selecting preset performance indicators from the associated performance indicator data for recombining to obtain combined performance indicator data associated with each of the test scenarios; generating a stress test report for the test object based on the associated performance indicator data, including: generating a stress test report for the test object based on the single performance indicator data and combined performance indicator data associated with each of the test scenarios.

[0010] Optionally, after obtaining the associated performance indicator data, it also includes: filtering the associated performance indicator data according to a preset joint threshold associated with at least two performance indicators to obtain filtered associated performance indicator data; generating a stress test report for the test object based on the associated performance indicator data, including: generating a stress test report for the test object based on the filtered associated performance indicator data corresponding to each of the test scenarios.

[0011] Another aspect of the present disclosure provides a stress test processing device, including: a first processing module, used to trigger N stress tests of the test object in M ​​test scenarios in response to a received automatic test instruction, wherein M is an integer greater than 1 and N is an integer not less than M; a second processing module, used to monitor the preset performance indicators associated with the test object in each of the stress test processes to obtain N groups of performance indicator data; a third processing module, used to associate the performance indicator data corresponding to each of the test scenarios with respect to the N groups of performance indicator data to obtain associated performance indicator data; and a fourth processing module, used to generate a stress test report for the test object based on the associated performance indicator data.

[0012] Optionally, the first processing module includes: a first processing unit, used to obtain M groups of test parameters for stress testing the test object in response to the received automatic test instruction, the test parameters including test scenario parameters and test flow parameters; a second processing unit, used to determine M test scenarios for stress testing the test object based on the test scenario parameters in each of the test parameters; a third processing unit, used to determine the test flow value associated with each of the M test scenarios based on the test flow parameters in each of the test parameters; and performing N stress tests on the test object according to the test flow value associated with each of the M test scenarios.

[0013] Optionally, the first processing unit includes: a first processing sub-unit, used to determine at least one operation event for stress testing the test object in each of the M test scenarios based on the test scenario parameters in each of the test parameters; the second processing unit includes: a second processing sub-unit, used to determine the concurrency number associated with each of the operation events in each of the test scenarios based on the test traffic parameters in each of the test parameters.

[0014] Optionally, the third processing module includes: a fourth processing unit, used to extract attribute features for the M test scenarios to obtain scenario attribute features associated with each of the test scenarios; a fifth processing unit, used to extract attribute features for the N groups of performance indicator data to obtain test attribute features associated with each of the performance indicator data; using the scenario attribute features associated with each of the test scenarios to filter the test attribute features to obtain test attribute features corresponding to each of the test scenarios; and a sixth processing unit, used to associate the performance indicator data corresponding to each of the test scenarios according to the test attribute features corresponding to each of the test scenarios to obtain the associated performance indicator data.

[0015] Optionally, the fourth processing unit includes: a third processing sub-unit, used to extract attribute features for each of the test scenarios, and determine the operation event features associated with each of the test scenarios as the scenario attribute features; the fifth processing unit includes: a fourth processing sub-unit, used to extract attribute features for each of the performance indicator data, and determine the event attribute features of at least one operation event performed during the corresponding stress test as the test attribute features.

[0016] Optionally, the device also includes a fifth processing module, which is used to select preset performance indicators from the associated performance indicator data for recombination after obtaining the associated performance indicator data, so as to obtain combined performance indicator data associated with each of the test scenarios; the fourth processing module is also used to generate a stress test report for the test object based on the single performance indicator data and combined performance indicator data associated with each of the test scenarios.

[0017] Optionally, the device also includes a sixth processing module, which is used to filter and process the associated performance indicator data after obtaining the associated performance indicator data according to a preset joint threshold associated with at least two performance indicators to obtain filtered associated performance indicator data; the fourth processing module is also used to generate a stress test report for the test object based on the filtered associated performance indicator data corresponding to each of the test scenarios.

[0018] Another aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method of an embodiment of the present disclosure.

[0019] Another aspect of the present disclosure provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the method of an embodiment of the present disclosure.

[0020] Another aspect of the present disclosure provides a computer program product, including a computer program, wherein when the computer program is executed by a processor, the method of the embodiment of the present disclosure is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] For a more complete understanding of the present disclosure and its advantages, reference will now be made to the following description taken in conjunction with the accompanying drawings, in which:

[0022] Figure 1 The system architecture of the stress test processing method and device according to the embodiment of the present disclosure is schematically shown;

[0023] Figure 2 A flowchart of a stress test processing method according to an embodiment of the present disclosure is schematically shown;

[0024] Figure 3 A flowchart schematically shows another stress test processing method according to an embodiment of the present disclosure;

[0025] Figure 4 A flowchart of another stress test processing method according to an embodiment of the present disclosure is schematically shown;

[0026] Figure 5 A block diagram of a pressure test processing device according to an embodiment of the present disclosure is schematically shown;

[0027] Figure 6 A block diagram of an electronic device according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0028] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0029] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "include", "comprising", etc. used herein indicate the existence of features, operations, operations and / or components, but do not exclude the existence or addition of one or more other features, operations, operations or components.

[0030] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0031] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0032] Some block diagrams and / or flow charts are shown in the accompanying drawings. It should be understood that some boxes or combinations thereof in the block diagrams and / or flow charts can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable stress test processing device, so that these instructions can create a device for implementing the functions / operations described in these block diagrams and / or flow charts when executed by the processor. The technology of the present disclosure can be implemented in the form of hardware and / or software (including firmware, microcode, etc.). In addition, the technology of the present disclosure can take the form of a computer program product on a computer-readable storage medium storing instructions, which can be used by an instruction execution system or in combination with an instruction execution system.

[0033] With the rapid development of computer technology, more and more diverse Internet technologies (such as big data technology, distributed technology, blockchain technology, artificial intelligence technology, etc.) are being applied to the financial field. With the increasing popularity of personal terminals, more and more users are handling financial services through Internet terminals, and the number of online banking users has expanded dramatically. Since the financial field has strict requirements on the security and real-time operation of business, higher standards are required for the business environment performance of online banks. Simulating stress testing of the business environment of online banks is one of the important means to ensure the security of financial business operations and improve the real-time operation of financial business.

[0034] In the process of implementing the technical solution disclosed in the present invention, the inventors found that in the relevant stress testing technology, the stress testing operation relies on manually configuring the stress testing scenario, which increases the workload of the stress testing and affects the efficiency of the stress testing. In addition, with the increase in performance scenarios in the financial field and the improvement in the accuracy requirements of performance indicators, the amount of performance indicator data sampled during the stress testing process is often large, and the correlation between different performance indicator data is weak. When analyzing the stress testing results based on the performance indicator data, there are problems such as large data analysis workload and low analysis efficiency, making it difficult to timely and effectively determine whether the stress testing results meet the system testing requirements.

[0035] In order to overcome the defects of strong dependence on manual operation, large test workload and low test efficiency in related stress testing technologies, the embodiments of the present disclosure provide a stress testing processing method and a processing device capable of applying the method. In the method, first, in response to the received automatic test instructions, N stress tests of the test object in M ​​test scenarios are triggered, where M is an integer greater than 1 and N is an integer not less than M. Then, the preset performance indicators associated with the test object in each stress test process are monitored to obtain N groups of performance indicator data, and for the N groups of performance indicator data, the performance indicator data corresponding to each test scenario are associated to obtain the associated performance indicator data. Finally, a stress test report for the test object is generated based on the associated performance indicator data.

[0036] Figure 1 The system architecture of the stress test processing method and device according to the embodiment of the present disclosure is schematically shown. It should be noted that: Figure 1 What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0037] like Figure 1 As shown, the system architecture 100 may include a test request end 101, a network 102, a stress test processing platform 103, and a business platform (multiple of which are shown in the figure, such as business platforms 104, 105, and 106). The network 102 is a medium for providing a communication link between the test request end 101, the stress test processing platform 103, and the business platform (such as business platforms 104, 105, and 106). The network 102 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0038] The stress test processing platform 103 receives the automatic test instruction from the test request end 101, and the test request end 101 may include an application development platform 1011 and an operation and maintenance management platform 1012. Specifically, the automatic test instruction may be generated by the application developer through the user end in the application development platform 1011, or may be automatically triggered by the application development platform 1011 based on a preset time interval. In addition, the automatic test instruction may also be generated by the operation and maintenance management personnel through the user end in the operation and maintenance management platform 1012, or may be automatically triggered by the operation and maintenance management platform 1012 based on a preset time interval.

[0039] The stress test processing platform 103 can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud computing, network services, and middleware services.

[0040] The business platforms (such as business platforms 104, 105, 106) constitute the test objects in the stress testing operation. By simulating and triggering real user operations in the business platforms (such as business platforms 104, 105, 106), it is determined whether the operating status of the business platforms meets the preset status requirements, and the stress testing results for the business platforms are obtained.

[0041] Specifically, the stress test processing platform 103 responds to the automatic test instructions received from the test request end 101, triggers N stress tests of the test object (such as business platforms 104, 105, 106) in M ​​test scenarios, where M is an integer greater than 1 and N is an integer not less than M, and monitors the preset performance indicators associated with the test object during each stress test to obtain N groups of performance indicator data, and then, for the N groups of performance indicator data, associates the performance indicator data corresponding to each test scenario to obtain the associated performance indicator data, and finally, the stress test processing platform 103 generates a stress test report for the test object (such as business platforms 104, 105, 106) based on the associated performance indicator data, and returns the stress test report to the test request end 101.

[0042] It should be noted that the stress test processing method and device of the embodiment of the present disclosure can be used in the financial field, and can also be used in any field other than the financial field. The present disclosure will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0043] Figure 2 A flow chart of a stress test processing method according to an embodiment of the present disclosure is schematically shown. Figure 2 As shown, method 200 may include operations S210 to S240.

[0044] In operation S210 , in response to the received automatic test instruction, N stress tests of the test object in M ​​test scenarios are triggered, where M is an integer greater than 1 and N is an integer not less than M.

[0045] Next, in operation S220, preset performance indicators associated with the test object during each stress test are monitored to obtain N groups of performance indicator data.

[0046] Next, in operation S230, the N groups of performance indicator data are associated with the performance indicator data corresponding to each test scenario to obtain associated performance indicator data.

[0047] Next, in operation S240, a stress test report for the test object is generated according to the associated performance indicator data.

[0048] The specific process of each step of the pressure test processing method of this embodiment is described in detail below.

[0049] In operation S210 , in response to the received automatic test instruction, N stress tests of the test object in M ​​test scenarios are triggered, where M is an integer greater than 1 and N is an integer not less than M.

[0050] In this embodiment, specifically, the stress test processing platform receives an automatic test instruction from a test request end, which may be an application development platform or an operation and maintenance management platform. The automatic test instruction may be a test instruction issued by a user port in the test request end, or a test instruction automatically triggered and generated by the test request end based on a preset time interval. The automatic test instruction indicates a test object to be stress tested, which may specifically be an application software or functional component in a financial service platform, such as a transaction page of an online banking application.

[0051] In response to the received automatic test instruction, the stress test processing platform triggers N stress tests on the test object in M ​​test scenarios, where M is an integer greater than 1 and N is an integer not less than M. Specifically, first, the stress test processing platform can obtain M groups of test parameters, each test parameter in the M groups of test parameters includes a test scenario parameter and a test flow parameter for performing a stress test on the test object, and M is an integer greater than 1. Then, the stress test processing platform triggers N stress tests on the test object in the corresponding M test scenarios based on the obtained M groups of test parameters.

[0052] The test scenario parameter in the test parameter indicates the test scenario used to perform stress testing on the test object, and the test flow parameter indicates the test flow value used to perform stress testing on the test object in the corresponding test scenario. Specifically, the test scenario parameter indicates the operation event information used to perform stress testing on the test object in the corresponding test scenario, and the operation event information includes, for example, the operation event name, the operation event code, the operation event type, the operation event execution order and other information, wherein the operation event type may include, for example, login operation, query operation, purchase operation, account opening operation, withdrawal operation, recharge operation, transfer operation, selling operation and other types. Correspondingly, the test flow parameter indicates the concurrent number of operation events used to perform stress testing on the test object in the corresponding test scenario, and the concurrent number may specifically be the number of operation event requests that the test object processes simultaneously within a preset time period. Exemplarily, 1,000 users are simulated to log in to the online banking transaction page at the same time, and the concurrent number associated with the login operation is 1,000.

[0053] The test scenario parameters can be obtained by analyzing the real user behavior data in the business analysis system. The test scenario parameters can restore the user behavior data in the real business scenario. By analyzing the real user behavior data in the business analysis system, the user behavior concurrency in the real business scenario is obtained, and the analysis results are used as the empirical value of the concurrent number of operation events for stress testing the test object. In addition, the test traffic parameters can also indicate the concurrency duration of the operation events used to stress test the test object and the concurrency per unit time.

[0054] Next, in operation S220, preset performance indicators associated with the test object during each stress test are monitored to obtain N groups of performance indicator data.

[0055] In this embodiment, specifically, the business performance indicator data and / or hardware performance indicator data associated with the test object during N stress tests are monitored to obtain N groups of performance indicator data. Among them, the business performance indicator data include, for example, the number of operation event request responses, the number of concurrent responses, the response time, the response throughput, etc., and the hardware performance indicator data include, for example, the CPU occupancy rate, the memory occupancy rate, etc.

[0056] After obtaining N groups of performance indicator data, optionally, normalization processing and denoising processing are performed on the N groups of performance indicator data. Specifically, according to the preset normalization dimension associated with each performance indicator, the corresponding performance indicator data is converted to a specified order of magnitude. According to the mean and variance of the N groups of performance indicator data, filtering processing is performed on the corresponding performance indicator data to remove performance indicator data records with deviations greater than preset conditions. In addition, abnormal data in the N groups of performance indicator data can also be identified by an anomaly detection algorithm. The anomaly detection algorithm can, for example, include anomaly detection based on historical mean, anomaly detection based on touch height algorithm, sample normalization calculation of Mahalanobis distance, etc. This design is conducive to timely identification of abnormal performance indicator data and to improving the efficiency of analysis of performance indicator data.

[0057] Next, in operation S230, for the N groups of performance indicator data, the performance indicator data corresponding to each test scenario is associated to obtain associated performance indicator data.

[0058] In this embodiment, specifically, for the N groups of performance indicator data obtained, different performance indicator data corresponding to the same test scenario are associated to obtain performance indicator data associated with each test scenario. According to the test scenario information during the stress test, the performance indicator data is associated, and this design is conducive to improving the correlation between the performance indicator data and improving the analysis efficiency of the performance indicator data. Further, this is conducive to reducing the workload of the stress test and improving the efficiency of the stress test.

[0059] When performing association processing on performance indicator data, attribute features can be extracted for each test scenario in the M test scenarios to obtain scenario attribute features associated with each test scenario, and the scenario attribute features indicate the operation event information performed during the stress test. Also, attribute features can be extracted for each performance indicator data in the N groups of performance indicator data to obtain test attribute features associated with each performance indicator data, and the test attribute features can also indicate the operation event information performed during the stress test. The test attribute features of the N groups of performance indicator data are screened using the scenario attribute features associated with each test scenario to obtain the test attribute features corresponding to each test scenario. Finally, the performance indicator data corresponding to each test scenario is associated according to the test attribute features corresponding to each test scenario to obtain the associated performance indicator data.

[0060] Next, in operation S240, a stress test report for the test object is generated according to the associated performance indicator data.

[0061] In this embodiment, specifically, the performance indicator data associated with each test scenario can be statistically processed to generate statistical data associated with each test scenario, and then generate a stress test report for the test object. The statistical data associated with each test scenario may include, for example, the maximum value, mean value, normal distribution value, etc. of the performance indicator data. In addition, the target indicator data associated with the test object can also be obtained, and the target indicator data includes reference data corresponding to different stress test standards. The target indicator data corresponding to the same stress test standard is compared with the performance indicator data obtained from the actual test to obtain a comparison result, and a stress test report for the test object is output based on the comparison result.

[0062] Optionally, after obtaining the associated performance indicator data, preset performance indicators can be selected from the associated performance indicator data for recombining to obtain combined performance indicator data associated with each test scenario. And, based on the single performance indicator data and combined performance indicator data associated with each test scenario, a stress test report for the test object is generated. Single performance indicators in the performance indicator data whose similarity is higher than a preset threshold are combined, or single performance indicators in the performance indicator data that can be used to indicate the same functional characteristics are combined to obtain a combined performance indicator. Exemplarily, the number of request responses, the number of concurrent responses, and the response throughput in the performance indicator data are weighted and merged to obtain a combined performance indicator for characterizing the concurrent response capability of the test object. This design can effectively reduce the workload of analyzing performance indicator data, which is conducive to improving the efficiency of analyzing performance indicator data, and thus is conducive to improving the efficiency of automated stress testing.

[0063] In addition, after obtaining the associated performance indicator data, the associated performance indicator data can be screened according to the preset joint threshold associated with at least two performance indicators to obtain screened associated performance indicator data, and a stress test report for the test object can be generated according to the screened associated performance indicator data corresponding to each test scenario. Exemplarily, in the performance indicator data associated with the concurrent login test scenario, the performance indicator data with a response throughput greater than a first preset threshold and a response time less than a second preset threshold are screened to obtain screened associated performance indicator data, wherein the first preset threshold and the second preset threshold constitute a preset joint threshold associated with at least two performance indicators.

[0064] Through the disclosed embodiment, in response to the received automatic test instruction, N stress tests of the test object in M ​​test scenarios are triggered, where M is an integer greater than 1 and N is an integer not less than M; the preset performance indicators associated with the test object in each stress test process are monitored to obtain N groups of performance indicator data; for the N groups of performance indicator data, the performance indicator data corresponding to each test scenario are associated to obtain the associated performance indicator data; and, based on the associated performance indicator data, a stress test report for the test object is generated. This design can effectively enhance the correlation between performance indicator data, by associating the performance indicator data corresponding to each test scenario to obtain the associated performance indicator data, and generating a stress test report for the test object based on the associated performance indicator data, which can effectively reduce the workload of analyzing performance indicator data during the stress test, is conducive to improving the analysis efficiency of performance indicator data, and is conducive to improving the efficiency of automated stress testing and improving the effect of stress testing. Based on the test scenario dimension management and analysis of performance indicator data, stress test results associated with different test scenarios can be obtained, which can effectively improve the readability and reference of stress test results.

[0065] Figure 3 The flowchart of another stress test processing method according to an embodiment of the present disclosure is schematically shown. Figure 3 As shown, operation S210 may include operations S310 to S340.

[0066] In operation S310, in response to the received automatic test instruction, M groups of test parameters for performing a stress test on a test object are obtained, where the test parameters include test scenario parameters and test traffic parameters.

[0067] Next, in operation S320, based on the test scenario parameters in each test parameter, M test scenarios for performing a stress test on the test object are determined.

[0068] Next, in operation S330, based on the test traffic parameter in each test parameter, a test traffic value associated with each of the M test scenarios is determined.

[0069] Next, in operation S340, N pressure tests are performed on the test object according to the test flow value associated with each of the M test scenarios.

[0070] The specific process of each step of the pressure test processing method of this embodiment is described in detail below.

[0071] In this embodiment, specifically, the test scenario parameters in the M groups of test parameters indicate M test scenarios for stress testing the test object, and further, at least one operation event for stress testing the test object in each of the M test scenarios can be determined based on the test scenario parameters in each test parameter. The test flow parameter in the M groups of test parameters indicates the test flow value for stress testing the test object, specifically indicating the concurrency number associated with each operation event in each test scenario.

[0072] The test scenario parameters include single-scenario test parameters and multi-scenario test parameters. When determining at least one operation event for stress testing the test object according to the test scenario parameters, a single operation event for stress testing the test object in the corresponding test scenario can be determined according to the single-scenario test parameters in the test scenario parameters; and / or, multiple operation events for stress testing the test object in the corresponding test scenario can be determined according to the multi-scenario test parameters in the test scenario parameters. A corresponding concurrent number ratio is preset for each operation event in the aforementioned multiple operation events, and the concurrent number ratio is determined based on the real user behavior data in the business analysis system.

[0073] When the multi-scenario test parameter indicates multiple operation events for stress testing the test object, a corresponding concurrency ratio is preset for each of the multiple operation events, and the concurrency ratio is determined based on the real user behavior data in the business analysis system. The higher the corresponding concurrency ratio, the higher the importance or application frequency of the operation event.

[0074] Considering that in actual applications, stress tests are often performed on important functions or common components of the object to be tested. Therefore, a higher test priority can be preset for operation events with a large concurrency ratio. That is, when the multi-scenario test parameters indicate multiple operation events in the corresponding test scenario, the concurrency ratio associated with any operation event is positively correlated to the test priority for the operation event. In the case where the received automatic test instruction contains test priority information, at least one operation event for stress testing the test object can be determined based on the test priority information and the concurrency ratio associated with each operation event in the multiple operation events.

[0075] After determining M test scenarios for stress testing the test object and determining the test flow value for stress testing in each test scenario, the stress test implementation framework is called to generate an automatic test script for each test scenario according to at least one operation event associated with each test scenario and the number of concurrent operations associated with each operation event. Then, the automatic test script is executed cyclically, and the preset performance indicators associated with the test object are monitored during each execution process to obtain N groups of performance indicator data.

[0076] Specifically, the automatic test script is executed cyclically to pass each operation event of the corresponding concurrent number to the execution center of the test object through the preset event response link. After capturing the operation event request, the execution center returns the event response result to the stress test processing platform through the event response link, thereby realizing N test execution processes for the test object. During each test execution process, the preset performance indicators associated with the test object are monitored to obtain N groups of performance indicator data, and the performance data analysis results are obtained by analyzing the performance indicator data, and a stress test report for the test is generated according to the performance data analysis results.

[0077] Figure 4 A flowchart of another stress test processing method according to an embodiment of the present disclosure is schematically shown. Figure 4 As shown, operation S230 may include operations S410 to S440.

[0078] In operation S410, attribute feature extraction is performed for M test scenes to obtain scene attribute features associated with each test scene.

[0079] Next, in operation S420, attribute feature extraction is performed on the N groups of performance indicator data to obtain test attribute features associated with each performance indicator data.

[0080] Next, in operation S430, the test attribute features are screened using the scenario attribute features associated with each test scenario to obtain the test attribute features corresponding to each test scenario.

[0081] Next, in operation S440, the performance indicator data corresponding to each test scenario is associated according to the test attribute characteristics corresponding to each test scenario to obtain the associated performance indicator data.

[0082] The specific process of each step of the pressure test processing method of this embodiment is described in detail below.

[0083] In this embodiment, specifically, attribute feature extraction is performed for each test scenario, and operation event features associated with each test scenario are determined to serve as scene attribute features of each test scenario. Each test scenario involves a large number of configuration parameters to ensure the authenticity and reliability of the test scenario. Therefore, each test scenario may contain a large number of attribute features, but in actual applications, not all attribute features can play a role in distinguishing test scenarios. Taking the test scenario of multiple users concurrently logging into an online banking transaction page as an example, the attribute features associated with the test scenario include multiple, such as user login accounts, login nodes, login devices, login verification methods, etc. However, these attribute features cannot be used to distinguish the corresponding test scenarios. Determine the operation event features associated with the test scenario, and the operation event features may specifically be concurrent login operation features, such as login methods, concurrent login numbers, concurrent login duration, and other attribute features. The concurrent login operation features constitute the scene attribute features of the test scenario, which can be used to distinguish this test scenario from other test scenarios (such as concurrent payment scenarios).

[0084] Attribute feature extraction is performed for each performance indicator data, and the event attribute feature of at least one operation event performed during the corresponding stress test is determined as the test attribute feature associated with each performance indicator data. During each stress test, by simulating a user triggering a specific operation on the test object, it is determined whether the test object can normally respond to the operation event request, and the performance limit state and the performance optimal state of the test object in the test environment of concurrent operation event requests are determined. Therefore, based on the N groups of performance indicator data obtained by monitoring, the event attribute feature of at least one operation event performed during the corresponding stress test can be identified as the test attribute feature associated with the performance indicator data.

[0085] Because the scenario attribute characteristics associated with each test scenario and the test attribute characteristics associated with each performance indicator data all contain the event attribute characteristics of at least one operation event simulated and triggered during the stress test, the scenario attribute characteristics associated with each test scenario can be used to screen the test attribute characteristics that match the scenario attribute characteristics, and then obtain the performance indicator data associated with each test scenario, thereby realizing the management and analysis of performance indicator data based on the test scenario granularity. This design is conducive to improving the correlation between performance indicator data and can effectively improve the analysis efficiency of performance indicator data.

[0086] Figure 5 A block diagram of a pressure test processing device according to an embodiment of the present disclosure is schematically shown.

[0087] like Figure 5 As shown, the apparatus 500 includes a first processing module 501 , a second processing module 502 , a third processing module 503 and a third processing module 504 .

[0088] Among them, the first processing module 501 is used to trigger N stress tests of the test object in M ​​test scenarios in response to the received automatic test instructions, wherein M is an integer greater than 1 and N is an integer not less than M; the second processing module 502 is used to monitor the preset performance indicators associated with the test object during each stress test process to obtain N groups of performance indicator data; the third processing module 503 is used to associate the performance indicator data corresponding to each test scenario with respect to the N groups of performance indicator data to obtain the associated performance indicator data; the fourth processing module 504 is used to generate a stress test report for the test object based on the associated performance indicator data.

[0089] Through the disclosed embodiment, in response to the received automatic test instruction, N stress tests of the test object in M ​​test scenarios are triggered, where M is an integer greater than 1 and N is an integer not less than M; the preset performance indicators associated with the test object in each stress test process are monitored to obtain N groups of performance indicator data; for the N groups of performance indicator data, the performance indicator data corresponding to each test scenario are associated to obtain the associated performance indicator data; and, based on the associated performance indicator data, a stress test report for the test object is generated. This design can effectively enhance the correlation between performance indicator data, by associating the performance indicator data corresponding to each test scenario to obtain the associated performance indicator data, and generating a stress test report for the test object based on the associated performance indicator data, which can effectively reduce the workload of analyzing performance indicator data during the stress test, is conducive to improving the analysis efficiency of performance indicator data, and is conducive to improving the efficiency of automated stress testing and improving the effect of stress testing. Based on the test scenario dimension management and analysis of performance indicator data, stress test results associated with different test scenarios can be obtained, which can effectively improve the readability and reference of stress test results.

[0090] As a feasible manner, the first processing module includes: a first processing unit, used to obtain M groups of test parameters for stress testing the test object in response to a received automatic test instruction, the test parameters including test scenario parameters and test flow parameters; a second processing unit, used to determine M test scenarios for stress testing the test object based on the test scenario parameters in each test parameter; a third processing unit, used to determine the test flow value associated with each test scenario in the M test scenarios based on the test flow parameters in each test parameter; and perform N stress tests on the test object according to the test flow value associated with each test scenario in the M test scenarios.

[0091] As a feasible approach, the first processing unit includes: a first processing sub-unit, used to determine at least one operation event for stress testing the test object in each of M test scenarios based on the test scenario parameters in each test parameter; the second processing unit includes: a second processing sub-unit, used to determine the concurrency number associated with each operation event in each test scenario based on the test traffic parameters in each test parameter.

[0092] As a feasible approach, the third processing module includes: a fourth processing unit, used to extract attribute features for M test scenarios to obtain scenario attribute features associated with each test scenario; a fifth processing unit, used to extract attribute features for N groups of performance indicator data to obtain test attribute features associated with each performance indicator data; using the scenario attribute features associated with each test scenario to screen the test attribute features to obtain test attribute features corresponding to each test scenario; a sixth processing unit, used to associate the performance indicator data corresponding to each test scenario according to the test attribute features corresponding to each test scenario to obtain the associated performance indicator data.

[0093] As a feasible approach, the fourth processing unit includes: a third processing sub-unit, used to extract attribute features for each test scenario, and determine the operation event features associated with each test scenario as scenario attribute features; the fifth processing unit includes: a fourth processing sub-unit, used to extract attribute features for each performance indicator data, and determine the event attribute features of at least one operation event performed during the corresponding stress test as test attribute features.

[0094] As a feasible approach, the device also includes a fifth processing module, which is used to, after obtaining the associated performance indicator data, select preset performance indicators from the associated performance indicator data for recombination to obtain combined performance indicator data associated with each test scenario; the fourth processing module is also used to: generate a stress test report for the test object based on the single performance indicator data and combined performance indicator data associated with each test scenario.

[0095] As a feasible approach, the device also includes a sixth processing module, which is used to filter and process the associated performance indicator data after obtaining the associated performance indicator data according to a preset joint threshold associated with at least two performance indicators to obtain filtered associated performance indicator data; the fourth processing module is also used to generate a stress test report for the test object based on the filtered associated performance indicator data corresponding to each test scenario.

[0096] It should be noted that in the embodiments of the present disclosure, the implementation of the device part is the same as or similar to the implementation of the method part, and will not be repeated here.

[0097] According to any one or more of the modules of the embodiments of the present disclosure, or at least part of the functions of any one of them, can be implemented in one module. According to any one or more of the modules of the embodiments of the present disclosure, it can be split into multiple modules for implementation. According to any one or more of the modules of the embodiments of the present disclosure, it can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware of any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in any appropriate combination of any of them. Or according to one or more of the modules of the embodiments of the present disclosure, it can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be performed.

[0098] For example, any multiple of the first processing module 501, the second processing module 502, the second processing module 503, and the second processing module 504 can be combined in one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first processing module 501, the second processing module 502, the second processing module 503, and the second processing module 504 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware or in an appropriate combination of any of them. At least one of the first processing module 501 , the second processing module 502 , the second processing module 503 , and the second processing module 504 may be at least partially implemented as a computer program module, and when the computer program module is executed, a corresponding function may be performed.

[0099] Figure 6 A block diagram of an electronic device 600 suitable for implementing the processing method and processing device according to an embodiment of the present disclosure is schematically shown. Figure 6 The electronic device 600 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0100] like Figure 6As shown, the electronic device 600 according to an embodiment of the present disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0101] In RAM 603, various programs and data required for the operation of electronic device 600 are stored. Processor 601, ROM 602 and RAM 603 are connected to each other via bus 604. Processor 601 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 602 and / or RAM 603. It should be noted that the program can also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in one or more memories.

[0102] According to an embodiment of the present disclosure, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the I / O interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 608 including a hard disk, etc.; and a communication portion 609 including a network interface card such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0103] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0104] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0105] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 602 and / or RAM 603 described above and / or one or more memories other than ROM 602 and RAM 603.

[0106] An embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains a program code for executing the method provided by the embodiment of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the method for detecting file upload vulnerabilities provided by the embodiment of the present disclosure.

[0107] When the computer program is executed by the processor 601, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0108] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 609, and / or installed from a removable medium 611. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0109] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0110] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0111] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Without departing from the scope of the present disclosure, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A stress test processing method, comprising: In response to the received automatic test instruction, triggering N stress tests of the test object in M ​​test scenarios, where M is an integer greater than 1 and N is an integer not less than M; Monitoring preset performance indicators associated with the test object during each of the stress tests to obtain N groups of performance indicator data; For the N groups of performance indicator data, the performance indicator data corresponding to each of the test scenarios are associated to obtain the associated performance indicator data, The N groups of performance indicator data are associated with the performance indicator data corresponding to each of the test scenarios to obtain the associated performance indicator data, including: Extracting attribute features for the M test scenes to obtain scene attribute features associated with each of the test scenes; Extracting attribute features of the N groups of performance indicator data to obtain test attribute features associated with each of the performance indicator data; Filtering the test attribute features using the scenario attribute features associated with each of the test scenarios to obtain the test attribute features corresponding to each of the test scenarios; According to the test attribute characteristics corresponding to each of the test scenarios, the performance indicator data corresponding to each of the test scenarios are associated to obtain the associated performance indicator data; A stress test report for the test object is generated based on the associated performance indicator data.

2. The method according to claim 1, wherein: The triggering of N stress tests of the test object in M ​​test scenarios in response to the received automatic test instruction includes: In response to the received automatic test instruction, obtaining M groups of test parameters for performing a stress test on the test object, the test parameters including test scenario parameters and test flow parameters; Determine, based on the test scenario parameters in each of the test parameters, M test scenarios for performing stress testing on the test object; Determining a test flow value associated with each of the M test scenarios based on a test flow parameter in each of the test parameters; According to the test flow value associated with each test scenario in the M test scenarios, N pressure tests are performed on the test object.

3. The method according to claim 2, wherein: The determining, based on the test scenario parameters in each of the test parameters, M test scenarios for performing a stress test on the test object includes: Determining, based on a test scenario parameter in each of the test parameters, at least one operation event for performing a stress test on the test object in each of the M test scenarios; The determining, based on the test flow parameter in each of the test parameters, a test flow value associated with each of the M test scenarios comprises: Based on the test traffic parameter in each of the test parameters, the concurrency number associated with each of the operation events in each of the test scenarios is determined.

4. The method according to claim 1, wherein: The extracting attribute features for the M test scenes to obtain scene attribute features associated with each of the test scenes includes: Extracting attribute features for each of the test scenarios, and determining operation event features associated with each of the test scenarios as the scenario attribute features; The extracting of attribute features for the N groups of performance indicator data to obtain test attribute features associated with each of the performance indicator data includes: Attribute feature extraction is performed for each of the performance indicator data to determine event attribute features of at least one operation event performed during the corresponding stress test process to serve as the test attribute features.

5. The method according to claim 1, wherein: After obtaining the associated performance indicator data, the method further includes: Selecting preset performance indicators from the associated performance indicator data and recombining them to obtain combined performance indicator data associated with each of the test scenarios; Generating a stress test report for the test object according to the associated performance indicator data includes: A stress test report for the test object is generated based on the single performance indicator data and the combined performance indicator data associated with each of the test scenarios.

6. The method according to any one of claims 1 to 5, wherein: After obtaining the associated performance indicator data, the method further includes: According to a preset joint threshold value associated with at least two performance indicators, the associated performance indicator data is screened to obtain screened associated performance indicator data; Generating a stress test report for the test object according to the associated performance indicator data includes: A stress test report for the test object is generated based on the screened associated performance indicator data corresponding to each of the test scenarios.

7. A pressure test processing device, comprising: A first processing module, configured to trigger N stress tests of the test object in M ​​test scenarios in response to a received automatic test instruction, wherein M is an integer greater than 1 and N is an integer not less than M; A second processing module is used to monitor the preset performance indicators associated with the test object during each stress test process to obtain N groups of performance indicator data; The third processing module is used to associate the N groups of performance indicator data with the performance indicator data corresponding to each of the test scenarios to obtain the associated performance indicator data. Wherein, the third processing module includes: A fourth processing unit, configured to extract attribute features for the M test scenes to obtain scene attribute features associated with each of the test scenes; A fifth processing unit is used to extract attribute features for the N groups of performance indicator data, obtain test attribute features associated with each of the performance indicator data, and screen the test attribute features using scenario attribute features associated with each of the test scenarios to obtain test attribute features corresponding to each of the test scenarios; A sixth processing unit, configured to associate the performance indicator data corresponding to each of the test scenarios according to the test attribute characteristics corresponding to each of the test scenarios to obtain the associated performance indicator data; The fourth processing module is used to generate a stress test report for the test object according to the associated performance indicator data.

8. An electronic device comprising: one or more processors; as well as a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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