CN114625654A

CN114625654A - Test method and related equipment thereof

Info

Publication number: CN114625654A
Application number: CN202210278161.1A
Authority: CN
Inventors: 鄂乾宇; 曹思琪
Original assignee: Beijing Youzhuju Network Technology Co Ltd
Current assignee: Beijing Youzhuju Network Technology Co Ltd
Priority date: 2022-03-21
Filing date: 2022-03-21
Publication date: 2022-06-14

Abstract

The application discloses a test method and related equipment thereof, wherein the method comprises the following steps: after receiving an automatic test request triggered by a user for a test task to be processed, inquiring test scheduling reference information corresponding to an information index identifier from a pre-constructed analysis information index database by using the information index identifier of a test object carried by the automatic test request so as to enable the test scheduling reference information to show the minimum condition required to be reached when carrying out resource scheduling on the test task to be processed; determining the resource allocation and task parameters of the test task to be processed according to the test scheduling reference information and the current state of the resource pool; and finally, executing the test task to be processed according to the resource configuration and the task parameters thereof, so that the aim of automatically executing the test task to be processed can be fulfilled, thereby effectively avoiding adverse effects caused by artificially driving the test task and further effectively reducing the resource consumption in the test process.

Description

Test method and related equipment thereof

Technical Field

The present application relates to the field of computer technologies, and in particular, to a testing method and related devices.

Background

Currently, for some testing tasks, after a test case is designed and passes review, a tester performs testing step by step according to the procedures described in the test case, resulting in a comparison of actual results with expected results.

However, since the above-described test scheme is human-driven, the test scheme needs to consume a large amount of resources (e.g., human resources, etc.).

Disclosure of Invention

In order to solve the above technical problems, the present application provides a testing method and related devices thereof, which can effectively reduce resource consumption in a testing process.

In order to achieve the above purpose, the technical solutions provided in the embodiments of the present application are as follows:

the embodiment of the application provides a test method, which comprises the following steps:

receiving an automatic test request triggered by a user for a test task to be processed; the automatic test request carries an information index identification of a test object of the test task to be processed;

inquiring test scheduling reference information corresponding to the information index identification from a pre-constructed analysis information index database; the test scheduling reference information is used for representing the minimum condition required to be achieved when the resource scheduling is carried out on the test task to be processed;

determining the resource allocation of the test task to be processed and task parameters of the resource allocation according to the current state of a resource pool and the test scheduling reference information;

and executing the test task to be processed according to the resource allocation and the task parameters of the resource allocation.

In a possible implementation manner, the test scheduling reference information includes at least one of a lower inflection point of the number of times that a test task is repeatedly executed, a lower inflection point of the demand of the service resource to be tested, and a maximum value of the QPS per second query rate corresponding to the lower inflection point of the demand of the service resource to be tested.

In a possible implementation manner, the test scheduling reference information includes a lower inflection point of the number of times of repeatedly executing a test task, a lower inflection point of the demand of the service resource to be tested, and a QPS maximum value corresponding to the lower inflection point of the demand of the service resource to be tested;

the determining the resource allocation of the test task to be processed and the task parameter of the resource allocation according to the current state of the resource pool and the test scheduling reference information includes:

according to the current state of the resource pool and the low inflection point of the demand of the tested service resources, performing resource allocation processing on the test task to be processed to obtain the resource allocation of the test task to be processed;

and determining the task parameters of the resource configuration according to the lower inflection point of the repeated execution times of the test task and the QPS maximum value corresponding to the lower inflection point of the demand of the tested service resource.

In a possible implementation manner, the performing resource allocation processing on the to-be-processed test task according to the current state of the resource pool and the low inflection point of the demand of the service resource to be tested to obtain the resource configuration of the to-be-processed test task includes:

determining the current idle resource of the resource pool according to the current state of the resource pool;

and according to the current idle resource and the low inflection point of the demand of the tested service resource, performing resource allocation processing on the test task to be processed to obtain the resource allocation of the test task to be processed.

In one possible embodiment, the method further comprises:

acquiring the estimated task density; the pre-estimated task density is used for representing the number of test tasks which are predicted to be executed simultaneously during the execution period of the test tasks to be processed;

the resource allocation processing is performed on the test task to be processed according to the current idle resource and the low inflection point of the demand of the tested service resource to obtain the resource allocation of the test task to be processed, and the resource allocation processing comprises the following steps:

and according to the pre-estimated task density, the current idle resources and the low inflection point of the demand of the tested service resources, performing resource allocation processing on the test task to be processed to obtain the resource allocation of the test task to be processed.

In a possible implementation manner, the performing resource allocation processing on the to-be-processed test task according to the pre-estimated task density, the current idle resource, and the low inflection point of the demand of the to-be-tested service resource to obtain the resource configuration of the to-be-processed test task includes:

determining resource tension degree characterization data according to the estimated task density and the resource amount of the current idle resource;

and if the resource tension degree characterization data meet a preset resource tension condition, performing resource allocation processing on the test task to be processed from the current idle resource according to the low inflection point of the demand of the tested service resource to obtain the resource allocation of the test task to be processed.

In one possible embodiment, the method further comprises:

if the resource tension degree representation data does not meet the preset resource tension condition, inquiring first heightening information corresponding to the resource tension degree representation data under the low inflection point of the measured service resource requirement from a pre-constructed first mapping relation;

determining the amount of resources to be used by utilizing the first heightening information and the low inflection point of the demand of the service resources to be tested;

and according to the amount of the resources to be used, performing resource allocation processing on the test task to be processed from the current idle resources to obtain the resource allocation of the test task to be processed.

In one possible embodiment, the estimated task density is predicted by using execution description data of test tasks executed in a historical time period.

In a possible implementation manner, the determining the task parameter of the resource configuration according to the lower inflection point of the number of times of repeatedly executing the test task and the maximum QPS value corresponding to the lower inflection point of the demand of the service resource under test includes:

and if the resource configuration of the test task to be processed meets the preset lowest configuration condition, determining the lower inflection point of the repeated execution times of the test task and the maximum value of the QPS corresponding to the lower inflection point of the demand of the service resource to be tested as the task parameter of the resource configuration.

In one possible embodiment, the method further comprises:

if the resource allocation of the test task to be processed meets a preset heightening condition, comparing the resource allocation of the test task to be processed with the low inflection point of the demand of the service resource to be tested to obtain a resource richness degree representation value;

querying second increase information corresponding to the resource richness degree representation value under the QPS maximum value corresponding to the low inflection point of the repeated execution times of the test task and the low inflection point of the demand of the tested service resource from a second mapping relation which is constructed in advance;

and determining the task parameters of the resource configuration by using the second heightening information, the lower inflection point of the repeated execution times of the test task and the maximum QPS value corresponding to the lower inflection point of the demand of the tested service resource.

In one possible embodiment, the method further comprises: and after the test task to be processed is determined to be completed, updating the analysis information index database by using the execution description data of the test task to be processed.

An embodiment of the present application further provides a testing apparatus, including:

the device comprises a receiving unit, a processing unit and a processing unit, wherein the receiving unit is used for receiving an automatic test request triggered by a user aiming at a test task to be processed; the automatic test request carries an information index identification of a test object of the test task to be processed;

the query unit is used for querying test scheduling reference information corresponding to the information index identification from a pre-constructed analysis information index database; the test scheduling reference information is used for representing the minimum condition required to be reached when the resource scheduling is carried out on the test task to be processed;

a determining unit, configured to determine, according to a current state of a resource pool and the test scheduling reference information, a resource configuration of the test task to be processed and a task parameter of the resource configuration;

and the test unit is used for executing the test task to be processed according to the resource configuration and the task parameters of the resource configuration.

An embodiment of the present application further provides an apparatus, where the apparatus includes a processor and a memory: the memory is used for storing a computer program; the processor is used for executing any implementation mode of the testing method provided by the embodiment of the application according to the computer program.

The embodiments of the present application further provide a computer-readable storage medium, where the computer-readable storage medium is used to store a computer program, and the computer program is used to execute any implementation manner of the test method provided in the embodiments of the present application.

The embodiment of the present application further provides a computer program product, and when the computer program product runs on a terminal device, the terminal device is enabled to execute any implementation manner of the test method provided by the embodiment of the present application.

Compared with the prior art, the embodiment of the application has at least the following advantages:

in the technical scheme provided by the embodiment of the application, after an automatic test request triggered by a user for a test task to be processed is received, firstly, by using an information index identifier of a test object of the test task to be processed, which is carried by the automatic test request, test scheduling reference information corresponding to the information index identifier is inquired from a pre-constructed analysis information index database, so that the test scheduling reference information can show the minimum condition required to be achieved when resource scheduling is carried out on the test task to be processed; determining the resource allocation of the test task to be processed and task parameters of the resource allocation according to the test scheduling reference information and the current state of the resource pool; finally, the test task to be processed is executed according to the resource allocation and the task parameters of the resource allocation, so that the purpose of automatically executing the test task to be processed can be achieved, adverse effects (for example, a large amount of resources need to be consumed) caused by artificially driving the test task can be effectively avoided, and the resource consumption in the test process can be effectively reduced.

In addition, because the test scheduling reference information is used for indicating the minimum condition (especially, the minimum resource amount required to be used) required to be achieved when the resource scheduling is performed on the to-be-processed test task, the resource configuration and the task parameter thereof determined based on the test scheduling reference information can at least achieve the minimum condition, so that the resource configuration and the task parameter thereof can ensure that the to-be-processed test task is smoothly executed, and thus, the defect that the to-be-processed test task cannot be executed or fails to be executed due to insufficient resource scheduled on the to-be-processed test task can be effectively avoided, and the automatic execution effect on the to-be-processed test task can be improved.

In addition, because the resource allocation of the test task to be processed and the task parameters of the resource allocation are performed based on the current state of the resource pool, the resource allocation of the test task to be processed and the task parameters of the resource allocation better conform to the current state of the resource pool, so that the purposes of scheduling more resources to the test task to be processed when the resources are rich and scheduling less resources to the test task to be processed when the resources are deficient can be achieved, and the use effect (for example, the use rate and the like) of the resource pool is favorably improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative efforts.

Fig. 1 is a flowchart of a testing method provided in an embodiment of the present application;

fig. 2 is a schematic engineering architecture diagram of a test system according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a testing apparatus according to an embodiment of the present application.

Detailed Description

The inventor finds in research on test tasks that, in some cases (for example, situations such as test task peak time), a free resource of a resource pool may not meet resource scheduling requirements of all test tasks, and thus, a phenomenon that a large number of test tasks cannot be executed or execution fails due to insufficient resources allocated by the test tasks may occur.

Based on the above findings, in order to solve the technical problems shown in the background section, an embodiment of the present application provides a testing method, which may specifically include: after receiving an automatic test request triggered by a user for a test task to be processed, inquiring test scheduling reference information corresponding to an information index identifier from a pre-constructed analysis information index database by using the information index identifier of a test object of the test task to be processed carried by the automatic test request, so that the test scheduling reference information can show the minimum condition required to be reached when resource scheduling is carried out on the test task to be processed; determining the resource allocation of the test task to be processed and task parameters of the resource allocation according to the test scheduling reference information and the current state of the resource pool; finally, the test task to be processed is executed according to the resource allocation and the task parameters of the resource allocation, so that the purpose of automatically executing the test task to be processed can be achieved, adverse effects (for example, a large amount of resources need to be consumed) caused by artificially driving the test task can be effectively avoided, and the resource consumption in the test process can be effectively reduced.

In addition, because the test scheduling reference information is used for indicating the minimum condition (especially, the minimum resource amount required to be used) required to be achieved when the resource scheduling is performed on the to-be-processed test task, the resource configuration and the task parameter thereof determined based on the test scheduling reference information can at least achieve the minimum condition, so that the resource configuration and the task parameter thereof can ensure that the to-be-processed test task is smoothly executed, and thus, the phenomenon that the to-be-processed test task cannot be executed or fails to be executed due to insufficient resource scheduled on the to-be-processed test task can be effectively avoided, and the automatic execution effect on the to-be-processed test task can be improved.

In addition, the embodiment of the present application does not limit the execution subject of the test method, and for example, the test method provided by the embodiment of the present application may be applied to a data processing device such as a terminal device or a server. The terminal device may be a smart phone, a computer, a Personal Digital Assistant (PDA), a tablet computer, or the like. The server may be a stand-alone server, a cluster server, or a cloud server.

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Method embodiment one

Referring to fig. 1, a flowchart of a testing method provided in an embodiment of the present application is shown.

The test method provided by the embodiment of the application comprises the following steps of S1-S4:

s1: and receiving an automatic test request triggered by a user for the test task to be processed.

Wherein, the user refers to a trigger of the automatic test request; moreover, the user is not limited by the embodiment of the present application, and for example, the user may be a person (e.g., a tester, a reviewer, a programmer, etc.) related to the test task to be processed.

The pending test tasks are used to perform functional testing on a certain service under test (e.g., XXX software, YYY applications, etc.). That is, the above-mentioned "certain service under test" is the test object of the test task to be processed.

It should be noted that, the embodiments of the present application do not limit the above "to-be-processed test task"; in addition, the embodiment of the present application does not limit the above "certain service under test".

The automatic test request is used for requesting to automatically execute the test task to be processed; and the automatic test request carries the information index identification of the test object of the test task to be processed.

The above-mentioned "information index identifier" is used to uniquely identify the test object of the test task to be processed, so that some information related to the test object (for example, the following "test scheduling reference information") can be subsequently queried using the "information index identifier".

In addition, the embodiment of the present application does not limit the above "information index identifier," and for example, it may be a name of a test object of the test task to be processed. For another example, the "information index identifier" may be obtained by performing a numerical conversion process on the name of the test object of the test task to be processed.

It should be noted that the embodiment of the present application is not limited to the implementation of the numerical value conversion process, and for example, it may be implemented in any existing or future manner (e.g., word2vec) that can implement conversion from text to numerical value.

Based on the above-mentioned relevant content of S1, when the user wants to automatically execute the test task to be processed, the user may trigger an automatic test request on the test device for the test task to be processed, so that the test device can automatically execute the resource scheduling process and the task execution process for the test task to be processed based on the information index identifier carried by the automatic test request, so as to implement an automatic test process for the test object (e.g., XXX software, etc.) of the test task to be processed.

It should be noted that the "test device" refers to any data processing device (e.g., a terminal device or a server) for executing the test method provided by the embodiment of the present application.

S2: and inquiring test scheduling reference information corresponding to the information index identification from a pre-constructed analysis information index database.

The analysis information index database is used for recording test scheduling candidate information corresponding to a large number of candidate index identifications.

In addition, the embodiment of the present application is not limited to the "analysis information index database," and for example, the analysis information index database may specifically include a 1 st candidate index identifier and a 1 st test scheduling candidate information, a 2 nd candidate index identifier and a 2 nd test scheduling candidate information, … …, and a K th candidate index identifier and a K th test scheduling candidate information. Wherein, the kth candidate index identifier is used for uniquely representing the kth candidate service under test (e.g., ZZZ software, etc.). The kth test scheduling candidate information is used to represent the minimum condition that needs to be reached when performing a functional test for the kth candidate service under test (that is, when executing a test task for performing a functional test for the kth candidate service under test). K is a positive integer, K is less than or equal to K, and K is a positive integer.

It should be noted that the content of the "kth test scheduling candidate information" is similar to the content of the "test scheduling reference information" described below.

It can be seen that after the information index identifier of the test object of the test task to be processed is obtained, the information index identifier may be matched with K candidate index identifiers in the analysis information index database, so that when it is determined that the information index identifier is successfully matched with the vth candidate index identifier, the vth test scheduling candidate information corresponding to the vth candidate index identifier may be directly determined as the test scheduling reference information corresponding to the information index identifier. Wherein v is a positive integer, and v is equal to {1, 2, … …, K }.

In addition, the embodiment of the present application does not limit the above-mentioned construction process of the "analysis information index database", please refer to the following descriptionMethod embodiment twoThe relevant contents of the above-described "analysis information index database" are shown.

The above-mentioned "test scheduling reference information" is used to indicate the minimum condition (for example, the minimum value required to be reached by the number of times of repeated execution of the test task to be processed, the minimum resource requirement amount of the test task to be processed, and the like) required to be reached when the resource scheduling is performed on the test task to be processed.

In addition, the embodiment of the present application is not limited to the "test scheduling reference information", and for example, the "test scheduling reference information" may specifically include at least one of a lower inflection point of the number of times that the test task is repeatedly executed, a lower inflection point of the demand for the service resource to be tested, and a maximum value of a query rate per second (QPS) corresponding to the lower inflection point of the demand for the service resource to be tested.

The "lower inflection point of the number of times of repeatedly executing the test task" refers to a minimum value that needs to be reached by the number of times of repeatedly executing the test task to be processed, so that the test task to be processed just can meet test validity conditions of stability of test indexes, confidence of test results and the like under the "lower inflection point of the number of times of repeatedly executing the test task", and thus the validity of the test task can be ensured, and the occurrence of invalid tests can be avoided.

It can be seen that if the number of times of repeated execution actually used when executing the test task to be processed is lower than the "lower inflection point of the number of times of repeated execution of the test task", the actual test result for the test task to be processed cannot meet the requirement of the confidence of the test result, thereby causing the phenomenon of invalid test; however, if the number of times of repeated execution actually used when executing the test task to be processed is equal to or higher than the "lower inflection point of the number of times of repeated execution of the test task", the actual test result for the test task to be processed can meet the requirement of the confidence of the test result, so that the validity of the test task can be ensured.

Based on the above two sections, when the to-be-processed test task is automatically executed, the to-be-processed test task may be repeatedly executed for multiple times, so that subsequent multiple execution data (for example, data such as execution duration, whether the task is completed, actual resource usage, and the like) based on the to-be-processed test task may be analyzed, and thus adverse effects caused by accidental events may be effectively avoided, and an automatic execution effect for the to-be-processed test task may be improved.

The above "low inflection point of the measured service resource requirement" is used to indicate the minimum resource requirement of the measured service (i.e., the test object of the test task to be processed), so that the measured service can just meet the conditions that the measured service can be normally started and can stably and continuously receive the flow and the like under the "low inflection point of the measured service resource requirement", thereby ensuring the environmental validity and effectively avoiding the occurrence of environmental unavailability.

It can be seen that, if the actually allocated resource amount for the to-be-processed test task is lower than the "low inflection point of the resource demand for the service under test", the environment may be unavailable due to the failure to meet the boundary value of the resource amount of the service availability under test, thereby causing the execution failure of the test task; however, if the resource actually allocated to the test task to be processed is equal to or greater than the "low inflection point of the resource demand of the service to be tested", the resource boundary value of the availability of the service to be tested can be satisfied, so that the test object of the test task to be processed can be started normally and can stably and continuously receive the flow, and the environmental validity of the test task to be processed can be ensured.

The above-mentioned "maximum QPS value corresponding to the lower inflection point of the service-under-test resource requirement" is used to indicate the maximum QPS that can be accepted under the lowest resource requirement of the service-under-test (i.e., the test object of the test task to be processed), so as to ensure that the environment is not unavailable due to the too large QPS for the test. It should be noted that in the present application, QPS is understood as the number of test cases executed per second.

It can be seen that, when the resource actually allocated to the to-be-processed test task is equal to the "measured service resource demand low inflection point", if the actually used QPS when executing the to-be-processed test task is higher than the QPS maximum value corresponding to the "measured service resource demand low inflection point", the "resource actually allocated to the to-be-processed test task" may be insufficient due to an excessive test QPS, so that the environment is not available, and the test task is failed to be executed; if the actually used QPS is equal to the maximum QPS value corresponding to the low inflection point of the demand of the service resource to be tested when the test task to be processed is executed, the environment usability can be kept, and the maximum task concurrency can be achieved, so that the test efficiency can be effectively improved; if the actually used QPS when executing the pending test task is lower than the above-mentioned "QPS maximum value corresponding to the low inflection point of the service resource demand under test", it may result in resource under-utilization although environment availability can be maintained.

Based on the above-mentioned relevant content of S2, after the information index identifier of the test object of the test task to be processed is obtained, the test scheduling reference information corresponding to the information index identifier may be queried from the pre-constructed analysis information index database, so that the test scheduling reference information can indicate the minimum condition (for example, the minimum value of the number of times of repeatedly executing the test task, the minimum requirement of the resource amount, and the QPS that can be borne at the maximum under the minimum requirement of the resource amount) that needs to be reached when performing resource scheduling on the test task to be processed, so as to enable the resource allocated based on the test scheduling reference information to reach the minimum condition, thereby effectively avoiding the phenomenon of failed execution of the test task to be processed due to insufficient allocated resources, and thus effectively reducing the possibility of failed execution of the test task to be processed, and further, the automatic execution effect of the test task to be processed can be improved.

S3: and determining the resource allocation of the test task to be processed and the task parameters of the resource allocation according to the current state of the resource pool and the test scheduling reference information.

The resource pool is used for providing resources required to be used for the test task to be processed; the resource pool is not limited in the embodiments of the present application, and may include at least one cluster, for example. As another example, it may also include at least one server. For example, it may also comprise at least one container.

The "current state of the resource pool" is used to indicate the real-time usage of the resource pool (e.g., which resources are in use, which resources are in idle, etc.).

In addition, the acquisition time of the "current state of the resource pool" is later than the reception time of the automatic test request and earlier than the execution time of S3; in addition, the embodiment of the present application does not limit the acquisition time of the "current state of the resource pool". In addition, the embodiment of the present application does not limit the manner of acquiring the "current state of the resource pool" described above.

The above-mentioned "resource configuration of the test task to be processed" is used to indicate the resources allocated to the test task to be processed.

The above "resource configuration task parameter" is used to indicate some parameters related to the execution of the test task (for example, the maximum acceptable QPS of the resource configuration, the number of times of task repeated execution, and the like) regulated by the above "resource configuration of the test task to be processed".

In addition, the embodiment of the present application does not limit the "task parameter of resource configuration" described above, for example, it may include: at least one of a QPS that is maximally acceptable for the resource configuration, and a number of iterations of tasks that is maximally acceptable for the resource configuration.

In order to better understand the above "resource configuration of the test task to be processed" and "task parameters of the resource configuration", a possible implementation of S3 is described as an example.

As an example, when the above "test scheduling reference information" includes a low inflection point of the number of times that the test task is repeatedly executed, a low inflection point of the demand of the service resource to be tested, and a QPS maximum value corresponding to the low inflection point of the demand of the service resource to be tested, S3 may specifically include S31-S32:

s31: and according to the current state of the resource pool and the low inflection point of the demand of the tested service resource, performing resource allocation processing on the test task to be processed to obtain the resource allocation of the test task to be processed, so that the resource amount of the resource allocation can be not lower than the low inflection point of the demand of the tested service resource.

In the embodiment of the application, after the current state of the resource pool and the low inflection point of the demand of the service resource to be tested are obtained, the resource allocation processing can be performed on the test task to be processed by referring to the two information to obtain the resource allocation of the test task to be processed, so that the resource allocation can adapt to the current state of the resource pool as far as possible under the condition that the resource amount of the resource allocation is not lower than the low inflection point of the demand of the service resource to be tested, and the phenomenon that the execution of the test task to be processed fails due to insufficient resources allocated to the test task to be processed can be effectively avoided.

In addition, the embodiment of S31 is not limited in the examples of the present application, and for the sake of easy understanding, the following description is made in conjunction with two possible embodiments.

In a first possible implementation, S31 may specifically include S311 to S312:

s311: and determining the current idle resources of the resource pool according to the current state of the resource pool.

The current free resource is used for representing the resource in the free state in the resource pool.

In addition, the embodiment of the present application is not limited to the implementation of S311, and for example, the present application may be implemented by any existing or future idle resource determination method.

In addition, the embodiment of the present application does not limit the execution time of S311, as long as the execution time of S311 is guaranteed to be earlier than S312.

S312: and according to the current idle resources of the resource pool and the low inflection point of the demand of the tested service resources, performing resource allocation processing on the test task to be processed to obtain the resource allocation of the test task to be processed.

In the embodiment of the application, after the current idle resource of the resource pool is obtained, the resource allocation processing can be performed on the to-be-processed test task from the current idle resource by referring to the low-order inflection point of the demand of the to-be-processed service resource, so that the resource allocation can use the current idle resource of the resource pool as much as possible under the condition that the resource amount of the resource allocation is not lower than the low-order inflection point of the demand of the to-be-processed service resource, and thus, the phenomenon that the to-be-processed test task fails to be executed due to insufficient resources allocated for the to-be-processed test task can be effectively avoided.

Based on the related content in S311 to S312, after the current state of the resource pool is obtained, the current idle resource of the resource pool may be determined according to the current state; and then according to the low inflection point of the demand of the service resource to be tested, carrying out resource allocation processing on the test task to be processed in the current idle resource to obtain the resource allocation of the test task to be processed, so that the resource allocation can use the current idle resource of the resource pool as much as possible under the condition that the resource amount of the resource allocation is not lower than the low inflection point of the demand of the service resource to be tested, and the phenomenon that the execution of the test task to be processed fails due to insufficient resources allocated for the test task to be processed can be effectively avoided.

In fact, in some application scenarios, a large number of test tasks are typically performed simultaneously within the same time period. Based on this, the present application provides a second possible implementation manner of S31, which may specifically include steps 11 to 12:

step 11: and determining the current idle resources of the resource pool according to the current state of the resource pool.

Please refer to S311 above for the relevant content of step 11.

In addition, the execution time of step 11 is not limited in the embodiment of the present application, as long as the execution time of step 11 is guaranteed to be earlier than that of step 12.

Step 12: and according to the pre-estimated task density, the current idle resource and the low inflection point of the demand of the service resource to be tested, performing resource allocation processing on the test task to be processed to obtain the resource allocation of the test task to be processed.

The pre-estimated task density is used for representing the number of the testing tasks to be executed by the resource pool, especially the number of the testing tasks executed simultaneously during the execution period of the testing tasks to be processed.

In addition, the predicted task density can be predicted by using the execution description data of the test tasks executed in the historical time period. The execution description data is used to describe relevant information generated during the execution of a test task (e.g., information about whether the test task is completed, what the resource configuration is, the QPS regulated for the resource configuration, the execution time period, the execution duration, the number of times of task repeated execution, etc.).

It should be noted that the present embodiment does not limit the "historical time period" described above, and for example, it may be one month (or even longer) before the trigger time point of the above "automatic test request". The prediction process of the "predicted task density" is not limited in the embodiments of the present application, and may be implemented by any prediction analysis method that is currently available or will come in the future (for example, a method based on a machine learning model, a big data mining method, or the like).

In addition, the embodiment of the present application does not limit the acquisition time of the "estimated task density" as long as it is ensured that the execution is completed before the step 12 is executed.

The embodiment of the present application is not limited to the implementation of step 12, and for example, it may specifically include steps 121 to 126:

step 121: and determining the representation data of the resource tension degree according to the estimated task density and the resource quantity of the current idle resource.

The resource tension degree representation data is used for representing the resource tension degree of the current idle resource of the resource pool under the estimated task density, so that the resource tension degree representation data can reflect whether the current idle resource can meet the requirement of testing task resources under the estimated task density.

In addition, the embodiment of the present application does not limit the determination process of the "resource tension degree characterization data", for example, the resource tension degree characterization data is the resource amount of the current free resources divided by (estimated task density × average task resource demand). Wherein the average task resource requirement is used to represent an average of the amount of resources required to be used by the test task.

The embodiment of the present application does not limit the manner of acquiring the "average task resource requirement", and may be set, for example, first. As another example, it may also be: and performing big data analysis processing on the execution description data of the test tasks executed in the historical time period to obtain the average task resource requirement.

Step 122: judging whether the resource tension degree representation data meets a preset resource tension condition, if so, executing the following step 123; if not, the following steps 124-126 are performed.

The preset resource tension condition may be preset. For example, when the resource tension degree characterization data is larger, it indicates that the probability that the current idle resource of the resource pool meets the resource scheduling requirement of the test task under the estimated task density is smaller, and thus indicates that the resource is more tense, the preset resource tension condition may be: the resource tension level characterizing data is above a first threshold.

Based on the related content in step 122, after the resource tension representing data is obtained, it is determined whether the resource tension representing data meets a preset resource tension condition, and if the preset resource tension condition is met, it indicates that the resource tension phenomenon occurs in the current idle resource of the resource pool relative to the pre-estimated task density, so that in order to ensure that as many test tasks as possible are effectively executed, resource scheduling (that is, the resource allocation manner shown in step 123) may be performed according to the lowest resource allocation of each test task, so that as many test tasks as possible can be effectively executed; however, if the current idle resource is not satisfied, it indicates that the current idle resource of the resource pool is not in tension relative to the estimated task density, so in order to better complete the test tasks, the resource scheduling may be performed according to the better resource allocation of each test task (i.e., the resource allocation manner shown in steps 124-126), which not only can ensure that the test tasks are successfully completed, but also can ensure that the tasks are completed with higher quality (or faster speed), thereby being beneficial to improving the automatic execution effect of the test tasks.

Step 123: and according to the low inflection point of the tested service resource requirement, performing resource allocation processing on the test task to be processed from the current idle resource to obtain the resource allocation of the test task to be processed.

In the embodiment of the application, when the resource tension degree representation data is determined to meet the preset resource tension condition, can determine that the current idle resource of the resource pool is tense relative to the estimated task density, so that the resource allocation of the test task to be processed can be obtained by directly performing resource allocation processing on the test task to be processed from the current idle resource according to the low inflection point of the demand of the service resource to be tested, so that the resource amount of the resource allocation is equal to the low inflection point of the demand of the service resource to be tested, so that the test task to be processed just can meet the test validity requirements of stable test indexes and confidence of test results under the resource configuration, thus, the resource consumption can be reduced as much as possible on the premise of ensuring that the test task to be processed can be effectively executed, thereby, it can be effectively ensured that a large number of test tasks are effectively executed as much as possible during the execution of the test tasks to be processed.

Step 124: and inquiring first heightening information corresponding to the resource tension degree representation data under the low inflection point of the demand of the tested service resource from a first mapping relation which is constructed in advance.

The first mapping relation is used for recording candidate heightening information corresponding to a large number of resource tension degree representation values under various alternative service resource demand low-order inflection points; the first mapping relationship is not limited in the embodiment of the present application, and may include a corresponding relationship shown in table 1, for example.

TABLE 1 first mapping relationship

It should be noted that, for table 1, a represents the number of the resource tension degree characterization values; and B represents the number of low inflection points of the alternative service resource requirement.

Based on the related content of the first mapping relationship, after the resource tension degree characterization data is obtained, the to-be-used binary group (resource tension degree characterization data, a low-order inflection point of the measured service resource demand) and each candidate binary group (resource tension degree characterization value, a low-order inflection point of the candidate service resource demand) in the first mapping relationship may be matched, so that it is determined that the resource tension degree characterization data is equal to the h-th resource tension degree characterization value a_hAnd determining that the lower inflection point of the demand of the tested service resource is equal to the lower inflection point b of the demand of the g-th alternative service resource_gThen, the corresponding relation R can be directly expressed_h,gThe recorded candidate turn-up information C_h,gAnd determining first heightening information corresponding to the resource tension degree characterization data under the low inflection point of the demand of the tested service resource. Wherein h is a positive integer and belongs to {1, 2, 3, … …, A }; g is a positive integer, g is ∈ {1, 2, 3, … …，B}。

In addition, the embodiment of the present application does not limit the manner of obtaining the first mapping relationship, and may be preset, for example. As another example, it may also be: and carrying out big data analysis processing on the execution description data of the test tasks executed in the historical time period to obtain the first mapping relation.

The first heightening information is used for expressing the relative relation between the actually distributed resource amount aiming at the test task to be processed and the low inflection point of the demand of the tested service resource; the embodiment of the present application does not limit the "first turn-up information", and for example, the "first turn-up information" may be a ratio or an increased value of the resource amount.

Step 125: and determining the amount of the resources to be used by utilizing the first heightening information and the low inflection point of the demand of the tested service resources.

The resource amount to be used is used for representing the resource amount actually allocated aiming at the test task to be processed; and the amount of the resources to be used is not less than the above 'low inflection point of the demand of the measured service resources'.

In addition, the present embodiment does not limit the determination process of the amount of resources to be used (i.e., the implementation manner of step 125), and for ease of understanding, the following description is made with reference to two examples.

Example 1, when the above "first raising information" is used to indicate a proportional relationship between the actually allocated resource amount for the to-be-processed test task and the low inflection point of the demand of the service resource to be tested, step 125 may specifically be: and multiplying the first heightening information by a low inflection point of the demand of the service resource to be measured to obtain the amount of the resource to be used.

Example 2, when the above "first raising information" is used to indicate a difference relationship between an amount of actually allocated resources for the to-be-processed test task and a low inflection point of the demand of the service resource to be tested, step 125 may specifically be: and adding the first heightening information and the low inflection point of the demand of the service resource to be measured to obtain the amount of the resource to be used.

Step 126: and according to the amount of the resources to be used, performing resource allocation processing on the test task to be processed from the current idle resources to obtain the resource allocation of the test task to be processed.

In the embodiment of the present application, after the amount of resources to be used is obtained, resource allocation processing may be performed on the test task to be processed from the current idle resource according to the amount of resources to be used, so as to obtain resource allocation of the test task to be processed, and the amount of resources allocated by the resource is equal to the amount of resources to be used, so that the test task to be processed can be effectively executed under the resource allocation, and can also be executed with an execution effect (for example, an execution speed as fast as possible, etc.) as good as possible, which is favorable for improving an automatic execution effect of the test task to be processed.

Based on the related contents from step 121 to step 126, after the estimated task density and the current idle resource are obtained, it may be determined whether the resource is in short supply according to the estimated task density and the current idle resource; if the resource shortage is determined, the resource allocation processing can be directly carried out on the test task to be processed from the current idle resource according to the low inflection point of the demand of the service resource to be tested, so that the resource allocation of the test task to be processed is obtained, the test task to be processed can be executed according to the lowest resource allocation subsequently, the resource consumption can be reduced as much as possible on the premise that the test task to be processed can be effectively executed, and a large number of test tasks can be effectively executed as much as possible during the execution period of the test task to be processed; however, if the resource is determined not to be tense, the amount of the resource to be used may be determined first, so that the amount of the resource to be used is higher than the low inflection point of the demand of the measured service resource; and then according to the amount of the resources to be used, performing resource allocation processing on the test task to be processed from the current idle resources to obtain the resource allocation of the test task to be processed, so that the automatic execution effect (for example, the automatic execution efficiency and the like) of the test task to be processed can be improved.

Based on the related content of the second possible implementation manner of the above S31, after the current state of the resource pool is obtained, the resource tension degree may be determined by referring to the current state and the estimated task density; and then according to a resource allocation mode suitable for the resource shortage degree, performing resource allocation processing on the test task to be processed to obtain the resource allocation of the test task to be processed, so that the resource allocation can improve the automatic execution effect of the test task to be processed as much as possible on the premise of ensuring the effective execution of the test task to be processed, and thus, intelligent resource allocation can be performed on the test task to be processed according to different resource shortage degrees.

S32: and determining the task parameters of the resource allocation according to the lower inflection point of the repeated execution times of the test task and the QPS maximum value corresponding to the lower inflection point of the demand of the tested service resource.

As an example, S32 may specifically include S321-S326:

s321: judging whether the resource configuration of the test task to be processed meets the preset lowest configuration condition, if so, executing S322; if not, go to S323.

The preset lowest configuration condition is a condition met by the test task which is allocated with the lowest resource configuration; in addition, the preset minimum configuration condition is not limited in the embodiment of the present application, and for example, the preset minimum configuration condition may specifically be: the amount of resources is equal to the "lower inflection point of the number of repeated executions of the test task" above.

It can be seen that, after the resource configuration of the test task to be processed is obtained, it may be determined whether the resource amount of the resource configuration is equal to the above "lower inflection point of the number of times of repeatedly executing the test task", and if so, it indicates that the resource configuration is the lowest resource configuration of the test task to be processed, so that it may be determined that the resource configuration meets the preset lowest configuration condition, and therefore, the task parameter regulation and control manner (as shown in S322 below) corresponding to the preset lowest configuration condition may be directly adopted for regulation and control.

S322: and determining the lower inflection point of the repeated execution times of the test task and the maximum value of the QPS corresponding to the lower inflection point of the demand of the tested service resource as the task parameter of the resource configuration.

In the embodiment of the present application, when it is determined that the resource configuration of the test task to be processed meets the preset minimum configuration condition, it may be determined that the minimum resource configuration mode is adopted for the test task to be processed, so in order to adapt to the minimum resource configuration mode as much as possible, the maximum acceptable QPS and the number of times of task repeated execution under the "resource configuration of the test task to be processed" may be obtained by directly adjusting and controlling the maximum acceptable QPS recorded in the task parameter according to the lower inflection point of the number of times of repeated execution of the test task and the maximum QPS corresponding to the lower inflection point of the demand for the service resource to be tested, so that the maximum acceptable QPS recorded in the task parameter is the maximum QPS corresponding to the lower inflection point of the demand for the service to be tested ", and the maximum acceptable number of times of repeated execution of the task recorded in the task parameter is the lower inflection point of the number of times of repeated execution of the test task, therefore, the automatic execution effect of the test task to be processed can be improved as much as possible on the premise of ensuring the effective execution of the test task to be processed.

S323: judging whether the resource allocation of the test task to be processed meets a preset heightening condition, if so, executing S324-S326; if not, generating and sending prompt information.

The preset heightening condition refers to a condition met by a test task which is allocated with higher resource configuration (namely, higher than the lowest resource configuration); in addition, the preset turn-up condition is not limited in the embodiment of the present application, and for example, it may specifically be: the amount of resources is greater than the "lower inflection point of the number of repeated executions of the test task" above.

It can be seen that, after the resource allocation of the test task to be processed is obtained, it may be determined whether the resource amount of the resource allocation is greater than the "low inflection point of the number of times of repeatedly executing the test task" above, and if so, it may be determined that the resource allocation satisfies the preset turn-up condition, so that the task parameter regulation and control manner (as shown in S324-S326 below) corresponding to the preset turn-up condition may be directly adopted for regulation and control subsequently; however, if the resource configuration is smaller than the preset minimum configuration condition, it may be determined that the resource configuration does not satisfy the preset minimum configuration condition nor the preset increase condition, so that it may be determined that the resource configuration has a defect (for example, insufficient resource, etc.), and it may be further inferred that the resource configuration is likely to cause a failure in executing the to-be-processed test task, so that a prompt message may be directly generated and sent, so that the prompt message may notify the user that there is a problem with the resource configuration allocated for the to-be-processed test task, so that the user may know the abnormal situation based on the prompt message, and further enable the user to adopt a corresponding handling measure for the abnormal situation (for example, manually ending the execution flow of the to-be-processed test task in time; or recording the to-be-processed test task, etc.).

S324: and comparing the resource allocation of the test task to be processed with the low inflection point of the demand of the tested service resource to obtain a resource abundance degree representation value.

The resource richness degree characterization value is used for representing the relative relation between the actually allocated resource quantity for the to-be-processed test task and the low inflection point of the demand of the tested service resource.

In addition, the embodiment of the present application does not limit the determination process of the "characteristic value of the resource abundance degree," and for example, the determination process may specifically be: and determining the ratio of the resource quantity of the resource allocation of the test task to be processed to the low inflection point of the demand of the tested service resource as a resource richness degree representation value.

S325: and querying second heightening information corresponding to the resource richness degree representation value under the QPS maximum value corresponding to the lower inflection point of the repeated execution times of the test task and the lower inflection point of the demand of the tested service resource from a second mapping relation which is constructed in advance.

The second mapping relation is used for recording corresponding to-be-used heightening information of a large number of resource rich degree values under various (alternative task repeated execution times lower inflection points, candidate QPS values); moreover, the second mapping relationship is not limited in the embodiments of the present application, for example, the second mapping relationship is similar to the above "first mapping relationship". That is, the second mapping relationship may include the correspondence relationship shown in table 2.

TABLE 2 second mapping relationship

In table 2, D represents the number of resource richness values; e represents the number of low inflection points of the repeated execution times of the alternative tasks; f represents the number of candidate QPS values.

Based on the related content of the second mapping relationship, after the resource abundance degree representation value is obtained, the triple to be used (the resource abundance degree representation value, the lower inflection point of the repeated execution times of the test task, and the maximum QPS value corresponding to the lower inflection point of the demand of the service resource to be tested) may be matched with each candidate triple (the resource abundance degree value, the lower inflection point of the repeated execution times of the candidate task, and the candidate QPS value) in the second mapping relationship, so that it is determined that the resource abundance degree representation value is equal to the w-th resource abundance degree value d_wThe above-mentioned "lower inflection point of the number of repeated executions of the test task" is equal to the lower inflection point e of the number of repeated executions of the qth alternative task_qAnd the maximum QPS value corresponding to the lower inflection point of the measured service resource requirement is equal to the p-th candidate QPS value f₁Then, the corresponding relation R can be directly expressed_w,q,pThe candidate key-up information G recorded in_w,q,pAnd determining as second heightening information. Wherein w is a positive integer, and w belongs to {1, 2, 3, … …, D }; q is a positive integer belonging to {1, 2, 3, … …, E }; p is a positive integer, and p is e {1, 2, 3, … …, F }.

In addition, the embodiment of the present application does not limit the manner of obtaining the second mapping relationship, and may be preset, for example. As another example, it may also be: and carrying out big data analysis processing on the execution description data of the test tasks executed in the historical time period to obtain the second mapping relation.

The second heightening information is used for expressing a relative relation between the task parameters actually regulated and controlled aiming at the resource configuration of the test task to be processed and the binary (the lower inflection point of the repeated execution times of the test task and the maximum QPS value corresponding to the lower inflection point of the demand of the tested service resource); the present embodiment does not limit the manner of indicating the second height adjustment information, and may indicate it by a scale or by a numerical increment, for example.

S326: and determining a task parameter of resource configuration by using the second heightening information, the lower inflection point of the repeated execution times of the test task and the maximum QPS value corresponding to the lower inflection point of the demand of the tested service resource.

As an example, when the second upward adjustment information includes the execution times upward adjustment information and the QPS upward adjustment information, S326 may specifically include S3261-S3263:

s3261: and determining the cycle times of the task to be referred according to the execution time increasing information and the low inflection point of the repeated execution times of the test task.

The execution time increase information is used for representing the relative relationship between the actually regulated and controlled maximum acceptable task repeated execution times of the resource configuration of the test task to be processed and the lower inflection point of the test task repeated execution times; the embodiment of the present application does not limit the execution number increase information, and for example, the execution number increase information may be a proportional value or a number increase amount.

The number of task cycles to be referred to is used to represent the maximum acceptable number of task repeated executions actually regulated and controlled according to the resource configuration of the test task to be processed.

In addition, the determination process of the "number of cycles of task to be referred to" described above is similar to the determination process of the amount of resources to be used shown in step 125 above.

S3262: and determining a QPS value to be referred according to the QPS heightening information and the QPS maximum value corresponding to the low inflection point of the demand of the detected service resource.

The QPS elevation information is used to represent a relative relationship between the actually regulated maximum acceptable QPS for the "resource configuration of the test task to be processed" and the "QPS maximum value corresponding to the measured service resource demand low inflection point" above; the embodiments of the present application do not limit the QPS increase information, and may be a proportional value or a count increase amount, for example.

The QPS value to be referred to is used to represent its maximum acceptable QPS for the "resource configuration of test task to be processed" actual regulation described above.

In addition, the determination process of the "QPS value to be referred to" described above is similar to the determination process of the amount of resources to be used shown in step 125 described above.

S3263: and according to the cycle times of the tasks to be referred and the QPS value to be referred, performing task parameter regulation and control processing on the resource configuration of the test tasks to be processed to obtain the task parameters of the resource configuration.

In the embodiment of the present application, after the cycle count of the task to be referred to and the QPS value to be referred to are obtained, the maximum acceptable task repeat execution count under the "resource configuration of the test task to be processed" and the QPS thereof may be regulated according to the two, so as to obtain the task parameter of the resource configuration, so that the maximum acceptable QPS recorded in the task parameter is the "QPS value to be referred to", and the maximum acceptable task repeat execution count recorded in the task parameter is the "cycle count of the task to be referred to", which can achieve the purpose of improving the automatic execution effect of the test task to be processed as much as possible on the premise of ensuring that the test task to be processed is effectively executed.

Based on the related contents of S3261 to S3263, after the second raising information is obtained, the second raising information, the lower inflection point of the number of times of repeatedly executing the test task, and the maximum QPS value corresponding to the lower inflection point of the demand of the service resource under test may be integrated to determine the task parameter of the resource configuration, so that the task parameter meets the raising requirement expressed by the second raising information.

Based on the related content of S32, after obtaining the low inflection point of the number of times of repeatedly executing the test task and the maximum QPS value corresponding to the low inflection point of the demand for the service resource to be tested, the task parameter of the "resource configuration of the test task to be processed" may be determined with reference to these two pieces of information, so that the task parameter may be adapted to the resource configuration of the test task to be processed as much as possible, which is beneficial to ensuring that the test task to be processed is executed better.

Based on the related content of S3, after the test scheduling reference information is obtained, the resource configuration and the task parameter adjustment and control processing may be performed on the test task to be processed with reference to the test scheduling reference information and the current state of the resource pool to obtain the resource configuration of the test task to be processed and the task parameter of the resource configuration.

S4: and executing the test task to be processed according to the resource configuration of the test task to be processed and the task parameters of the resource configuration.

In the embodiment of the application, after the resource configuration of the test task to be processed and the task parameters of the resource configuration are obtained, the test environment of the test task to be processed can be deployed according to the resource configuration; and then, in the test environment, executing the test task to be processed according to the task parameters configured by the resources, so that the aim of automatically executing the test task to be processed can be fulfilled.

Based on the relevant contents of S1 to S4, it can be known that, in the testing method provided in the embodiment of the present application, after receiving an automatic testing request triggered by a user for a to-be-processed testing task, first, using an information index identifier of a testing object of the to-be-processed testing task, which is carried by the automatic testing request, to query, from a pre-constructed analysis information index database, test scheduling reference information corresponding to the information index identifier, so that the test scheduling reference information can indicate a minimum condition that needs to be achieved when resource scheduling is performed for the to-be-processed testing task; determining the resource allocation of the test task to be processed and task parameters of the resource allocation according to the test scheduling reference information and the current state of the resource pool; and finally, executing the test task to be processed according to the resource configuration and the task parameters of the resource configuration, so that the aim of automatically executing the test task to be processed can be fulfilled, adverse effects (for example, a large amount of resources are consumed) caused by artificially driving the test task can be effectively avoided, and the resource consumption in the test process can be effectively reduced.

Method embodiment two

In order to better implement automatic execution of a test task, an embodiment of the present application further provides an analysis information index database, where a large amount of raw information (for example, execution description data of a completed test task) and analysis results obtained by analyzing the raw information (for example, the "test scheduling candidate information corresponding to a large amount of candidate identifiers", the "first mapping relationship", the "second mapping relationship", the "preset density", and the like) are recorded in the analysis information index database, so that when an automatic execution process is performed on a certain test task, corresponding information can be obtained from the analysis information index database.

In addition, all the analysis results recorded in the above "analysis information index database" are obtained by performing data analysis (for example, big data mining analysis, artificial intelligence analysis based on machine learning model, and the like) on a large amount of raw information related to completed test tasks.

In addition, the embodiment of the present application is not limited to the above-mentioned construction method of the "analysis information index database", and for example, the construction method may be performed in an offline manner.

Method embodiment three

In addition, in order to further improve the automatic test effect, the "analysis information index database" may be updated in real time. Based on this, the present application provides another possible implementation manner of the testing method, and in this implementation manner, the testing method may further include, in addition to the foregoing S1 to S4, S5:

s5: and after the test task to be processed is determined to be completed, updating the analysis information index database by using the execution description data of the test task to be processed.

In the embodiment of the application, after determining that the automatic execution process for the test task to be processed is completed, the analysis information index database may be updated with the execution description data of the test task to be processed (e.g., information about whether the test task is completed, what the resource configuration is, the QPS regulated for the resource configuration, the execution time period, the execution duration, the number of times of task repeated execution, etc.), in particular, all the original information and analysis results (for example, the "test scheduling reference information corresponding to the information index identifier", the "first mapping relationship", the "second mapping relationship", the "preset density", and the like) related to the test task to be processed in the analysis information index database are updated once.

Based on the above-mentioned relevant content of S5, after determining that the automatic execution process for the to-be-processed test task has been completed, the analysis information index database may be updated by using the execution description data of the to-be-processed test task, so that the analysis information index database can record the test task analysis information contributed by the to-be-processed test task, and thus the real-time performance of the analysis information index database can be improved as much as possible.

In fact, when analyzing the relevant information of each service under test (e.g., the lower inflection point of the number of times of repeatedly executing the test task, the lower inflection point of the demand for the service resource under test, and the maximum value of the query rate per second QPS corresponding to the lower inflection point of the demand for the service resource under test), it is usually necessary to complete a large number of test tasks for the service under test in advance.

However, in some cases, the following phenomena may occur: only a small number of test tasks for a certain service under test are completed, so that only a small number of sample data (for example, execution description data of a small number of test tasks, etc.) under the service under test exists in the analysis information index database, so in order to improve an analysis effect for the service under test, the embodiment of the present application further provides another possible implementation manner, and in this implementation manner, the test method further includes, in addition to the foregoing S1-S5, S6:

s6: and when determining that the number of the execution description data corresponding to the test object of the test task to be processed in the analysis information index database is lower than a second threshold value and that the resource pool meets the preset low-pressure condition, continuing to execute step S1 and the subsequent steps.

The execution description data corresponding to the "test object of the test task to be processed" refers to the execution description data related to the "test object of the test task to be processed" (that is, the execution description data obtained by performing the service test on the test object).

The preset low pressure condition may be preset, for example, when the resource shortage degree representation data is larger, the probability that the current free resource of the resource pool meets the resource scheduling requirement of the test task is smaller under the estimated task density, and thus the resource is more congested, the preset low pressure condition may be: the resource tension level characterizing data is below a third threshold.

Based on the related content of S6, if it is determined that the number of the execution description data corresponding to the "test object of the test task to be processed" in the analysis information index database is lower than the second threshold value, it can be determined that the service test procedure for the test object is less, so in order to improve the analysis effect for the test object, the steps S1-S5 may be automatically executed in the case that the resource pool pressure is smaller, until the loop execution process for S1-S5 is ended when it is determined that the number of the execution description data corresponding to the test object in the analysis information index database is not lower than the second threshold, and analyzes the execution description data corresponding to the test object to obtain the analysis result (for example, the test scheduling reference information) of the test object, therefore, the accuracy of the analysis result can be improved as much as possible on the premise of not influencing the normal work of the resource pool.

Method example four

For a better understanding of the testing method provided by the embodiments of the present application, the following description is made with reference to the system shown in fig. 2. Fig. 2 is a schematic diagram of an engineering architecture of a test system according to an embodiment of the present disclosure.

For the test system shown in fig. 2, the test system is suitable for executing any one of the possible embodiments of the test method provided by the embodiment of the present application, so that the test system can automatically execute a certain test task.

As shown in fig. 2, the test system provided in the embodiment of the present application may be divided into an online system and an offline system, and for convenience of understanding, the online system and the offline system are respectively described below.

Online system

For the online system shown in fig. 2, the online system refers to a system that functions when there is a task request (e.g., the above "automatic test request"), and the online system can be divided into the following 7 modules:

the online task management module: the method is an entrance of automatic testing and is responsible for managing user tasks and preprocessing.

Task engine services: managing task execution flow, initiating sub-module request, result feedback, node series connection and the like.

A data acquisition module: and the task engine service is responsible for collecting task data from the task engine service, including execution results, execution time consumption and the like.

A resource scheduling module: and the system is responsible for generating an optimal allocation strategy according to the real-time resource pool state and the resource optimization service and allocating resources for the test tasks.

A resource optimization module: and the system is responsible for online estimation according to the index data generated by offline analysis, wherein the online estimation comprises resource inflection values, estimation available resource states, task density and the like.

A container scheduling module: a test environment is created based on the allocated resources.

The test execution module: and the system is responsible for sending test flow and counting test results to the established test environment.

In addition, for further understanding of the online system shown in fig. 2, the working principle of the online system will be described below by taking the automatic execution process for the test task to be processed as an example.

As an example, the working principle of the online system is as follows: after the on-line task management module receives an automatic test request triggered by a user aiming at a test task to be processed, a task engine service module initiates a request to a resource scheduling module so that the resource scheduling module can perform resource allocation by referring to two information, namely a resource pool real-time state acquired by a resource pool management module and test scheduling reference information acquired by a resource optimization module to obtain resource allocation of the test task to be processed, and regulates and controls the maximum acceptable QPS and the repeated execution times of the task under the resource allocation to obtain task parameters of the resource allocation; then, the task engine service module deploys a test environment according to the resource configuration, and initiates a request to the test execution module, so that the test execution module can execute the test task to be processed according to the task parameters of the resource configuration, so that after the task engine service module determines that the execution of the test task to be processed is finished, the task engine service module initiates a request to the data collection module, so that the data collection module can collect task sample data (for example, execution description data of the test task to be processed) from the engine service module.

Based on the related content of the online system, at the peak of the test tasks, the resource state is relatively tense, and a large number of test tasks may be queued for a long time or even failed to be deployed due to insufficient resources, so the resource scheduling module should ensure that as many test tasks as possible are correctly executed, and therefore, within the security threshold of the tested service resources, the resource scheduling module can reduce the resource configuration and the corresponding QPS to ensure that as many environment quantities as possible are provided, thereby ensuring the task concurrency. However, during the low peak period of the test task, the resource pool has a large amount of idle resources, so that the resource scheduling module can utilize the idle resources as much as possible, and therefore, the resource scheduling module can promote the configuration of the tested service resources and the corresponding QPS, so as to optimize the time consumption of the test task and the user experience. Therefore, the function of intelligently selecting the resource strategy for the tested service according to the current available resource quantity can be realized.

Off-line system

For the offline system shown in fig. 2, the offline system refers to a module that can perform independent analysis on output independent of task request, and the offline system can be divided into the following 3 modules:

an offline task scheduling module: the system is an entrance for off-line system testing and is responsible for supplementing a new task sample according to a data acquisition sample range.

An offline data analysis module: and the data acquisition system is responsible for carrying out data analysis including sample classification, data fitting and the like according to data acquisition samples.

An offline index storage module: an analysis index for storing offline data.

In addition, the working principle of the off-line system is as follows: the offline task scheduling module can perform sample coverage statistical analysis on a large amount of data stored by the data acquisition module, so that when a certain sample number (for example, the number of test tasks for testing XXX software) is determined to be low, a sample supplementary execution flow (for example, an execution process for testing the XXX software is automatically initiated) can be initiated by the offline task scheduling module in a task testing low peak period so as to ensure the balance of different types of samples; the offline data analysis module is responsible for performing information analysis processing (for example, classification statistics, data analysis, characteristic fitting and the like) on the collected samples to obtain analysis results, and the analysis results are placed in the storage module for the next online request.

Based on the related content of the offline system, the offline data analysis module in the offline system can analyze the minimum resource configuration and the optimal resource configuration of the tested service (or analyze the resource configurations used by the tested service under different resource tension degrees, etc.) and the QPS that can be maximally withstood under different resource configurations based on some existing data related to the test tasks, so that the analysis results can be subsequently used to perform an automatic test process for the tested service.

Based on the related content of the test system, the test system can intelligently select the appropriate resource configuration and task parameters thereof for each test task. For example, when the test task amount is large, the test system can automatically select the configuration of the lowest resource for the tested service, and the resource occupation amount of each test is reduced, so that the system can support more test tasks. In addition, when the testing task amount is small, the testing system can automatically select the optimal performance resource allocation for the tested service, and meanwhile qps of the testing request is improved, and the testing time is shortened.

Based on the testing method provided by the above method embodiment, the embodiment of the present application further provides a testing apparatus, which is explained and explained with reference to the drawings.

Device embodiment

Please refer to the above method embodiment for technical details of the testing apparatus provided in the apparatus embodiment.

Referring to fig. 3, the figure is a schematic structural diagram of a testing apparatus according to an embodiment of the present application.

The test apparatus 300 provided in the embodiment of the present application includes:

a receiving unit 301, configured to receive an automatic test request triggered by a user for a to-be-processed test task; the automatic test request carries an information index identification of a test object of the test task to be processed;

a query unit 302, configured to query test scheduling reference information corresponding to the information index identifier from a pre-constructed analysis information index database; the test scheduling reference information is used for representing the minimum condition required to be achieved when the resource scheduling is carried out on the test task to be processed;

a determining unit 303, configured to determine, according to a current state of a resource pool and the test scheduling reference information, a resource configuration of the to-be-processed test task and a task parameter of the resource configuration;

the testing unit 304 is configured to execute the to-be-processed testing task according to the resource configuration and the task parameter of the resource configuration.

In a possible implementation manner, the test scheduling reference information includes at least one of a lower inflection point of the number of times that a test task is repeatedly executed, a lower inflection point of the demand of the service resource to be tested, and a maximum value of a query rate per second QPS corresponding to the lower inflection point of the demand of the service resource to be tested.

the determining unit 303 includes:

the allocation subunit is configured to perform resource allocation processing on the to-be-processed test task according to the current state of the resource pool and the low inflection point of the demand of the to-be-tested service resource, so as to obtain resource allocation of the to-be-processed test task;

and the regulating subunit is used for determining the task parameters of the resource configuration according to the lower inflection point of the repeated execution times of the test task and the maximum QPS value corresponding to the lower inflection point of the demand of the tested service resource.

In one possible embodiment, the allocation subunit includes:

the first determining subunit is configured to determine, according to the current state of the resource pool, a current idle resource of the resource pool;

and the second determining subunit is configured to perform resource allocation processing on the to-be-processed test task according to the current idle resource and the low inflection point of the demand of the to-be-tested service resource, so as to obtain resource allocation of the to-be-processed test task.

In a possible embodiment, the testing device 300 further comprises:

the acquisition unit is used for acquiring the estimated task density; the pre-estimated task density is used for representing the number of test tasks which are predicted to be executed simultaneously during the execution period of the test tasks to be processed;

the second determining subunit is specifically configured to: and according to the pre-estimated task density, the current idle resource and the low inflection point of the demand of the tested service resource, performing resource allocation processing on the test task to be processed to obtain the resource allocation of the test task to be processed.

In a possible implementation manner, the second determining subunit is specifically configured to: determining resource tension degree characterization data according to the estimated task density and the resource amount of the current idle resource; and if the resource tension degree characterization data meet a preset resource tension condition, performing resource allocation processing on the test task to be processed from the current idle resource according to the low inflection point of the demand of the tested service resource to obtain the resource allocation of the test task to be processed.

In a possible implementation, the second determining subunit is further configured to: if the resource tension degree representation data does not meet the preset resource tension condition, inquiring first heightening information corresponding to the resource tension degree representation data under the low inflection point of the measured service resource requirement from a pre-constructed first mapping relation; determining the amount of resources to be used by utilizing the first heightening information and the low inflection point of the demand of the service resources to be tested; and according to the amount of the resources to be used, performing resource allocation processing on the test task to be processed from the current idle resources to obtain the resource allocation of the test task to be processed.

In one possible embodiment, the predicted task density is predicted using execution description data of test tasks executed over a historical period of time.

In one possible embodiment, the regulatory subunit is specifically configured to: and if the resource configuration of the test task to be processed meets a preset minimum configuration condition, determining a lower inflection point of the repeated execution times of the test task and a maximum QPS value corresponding to the lower inflection point of the demand of the service resource to be tested as a task parameter of the resource configuration.

In one possible embodiment, the regulatory subunit is further configured to: if the resource allocation of the test task to be processed meets a preset heightening condition, comparing the resource allocation of the test task to be processed with the low inflection point of the demand of the service resource to be tested to obtain a resource richness degree representation value; querying second increase information corresponding to the resource richness degree representation value under the QPS maximum value corresponding to the low inflection point of the repeated execution times of the test task and the low inflection point of the demand of the tested service resource from a second mapping relation which is constructed in advance; and determining the task parameters of the resource configuration by using the second heightening information, the lower inflection point of the repeated execution times of the test task and the maximum QPS value corresponding to the lower inflection point of the demand of the tested service resource.

In a possible embodiment, the testing device 300 further comprises:

and the updating unit is used for updating the analysis information index database by using the execution description data of the test task to be processed after the test task to be processed is determined to be executed and completed.

Based on the related content of the testing apparatus 300, it can be known that, for the testing apparatus 300 provided in this embodiment of the present application, after receiving an automatic test request triggered by a user for a to-be-processed test task, first, by using an information index identifier of a test object of the to-be-processed test task carried by the automatic test request, a test scheduling reference information corresponding to the information index identifier is queried from a pre-constructed analysis information index database, so that the test scheduling reference information can indicate a minimum condition that needs to be reached when performing resource scheduling for the to-be-processed test task; determining the resource allocation of the test task to be processed and task parameters of the resource allocation according to the test scheduling reference information and the current state of the resource pool; finally, the test task to be processed is executed according to the resource allocation and the task parameters of the resource allocation, so that the purpose of automatically executing the test task to be processed can be achieved, adverse effects (for example, a large amount of resources need to be consumed) caused by artificially driving the test task can be effectively avoided, and the resource consumption in the test process can be effectively reduced.

In addition, because the resource allocation of the test task to be processed and the task parameters of the resource allocation are performed based on the current state of the resource pool, the resource allocation of the test task to be processed and the task parameters of the resource allocation better conform to the current state of the resource pool, so that the purposes of scheduling more resources to the test task to be processed when the resources are rich and scheduling less resources to the test task to be processed when the resources are deficient can be achieved, and the use effect (for example, the utilization rate and the like) of the resource pool is favorably improved.

Further, an embodiment of the present application further provides an apparatus, where the apparatus includes a processor and a memory:

the memory is used for storing a computer program;

the processor is used for executing any implementation mode of the testing method provided by the embodiment of the application according to the computer program.

Further, the present application also provides a computer-readable storage medium for storing a computer program for executing any implementation of the testing method provided by the present application.

Further, an embodiment of the present application also provides a computer program product, which when running on a terminal device, causes the terminal device to execute any implementation of the test method provided in the embodiment of the present application.

It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of the singular or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.

The foregoing is merely a preferred embodiment of the invention and is not intended to limit the invention in any manner. Although the present invention has been described with reference to the preferred embodiments, it is not intended to be limited thereto. Those skilled in the art can make many possible variations and modifications to the disclosed solution, or to modify equivalent embodiments, without departing from the scope of the solution, using the methods and techniques disclosed above. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.

Claims

1. A method of testing, the method comprising:

and executing the test task to be processed according to the resource configuration and the task parameters of the resource configuration.

2. The method according to claim 1, wherein the test scheduling reference information includes at least one of a lower inflection point of the number of times that the test task is repeatedly executed, a lower inflection point of the demand of the service resource under test, and a maximum value of a query rate per second QPS corresponding to the lower inflection point of the demand of the service resource under test.

3. The method according to claim 2, wherein the test scheduling reference information includes a low inflection point of the number of times of repeated execution of the test task, a low inflection point of the demand of the service resource under test, and a QPS maximum value corresponding to the low inflection point of the demand of the service resource under test;

the determining the resource allocation of the test task to be processed and the task parameters of the resource allocation according to the current state of the resource pool and the test scheduling reference information includes:

and determining the task parameters of the resource configuration according to the lower inflection point of the repeated execution times of the test task and the maximum QPS value corresponding to the lower inflection point of the demand of the tested service resource.

4. The method according to claim 3, wherein the performing resource allocation processing on the to-be-processed test task according to the current state of the resource pool and the low inflection point of the demand of the tested service resource to obtain the resource configuration of the to-be-processed test task comprises:

5. The method of claim 4, further comprising:

6. The method according to claim 5, wherein the performing resource allocation processing on the to-be-processed test task according to the pre-estimated task density, the current idle resource, and the low inflection point of the demand of the to-be-tested service resource to obtain the resource allocation of the to-be-processed test task comprises:

7. The method of claim 6, further comprising:

8. The method of claim 5, wherein the predicted task density is predicted using performance description data for test tasks performed over a historical period of time.

9. The method according to claim 3, wherein the determining the task parameter of the resource configuration according to the lower inflection point of the number of times of repeatedly executing the test task and the maximum QPS value corresponding to the lower inflection point of the demand of the service resource under test comprises:

10. The method of claim 9, further comprising:

11. The method of claim 1, further comprising:

and after the test task to be processed is determined to be completed, updating the analysis information index database by using the execution description data of the test task to be processed.

12. A test apparatus, comprising:

the receiving unit is used for receiving an automatic test request triggered by a user aiming at a test task to be processed; the automatic test request carries an information index identification of a test object of the test task to be processed;

the query unit is used for querying test scheduling reference information corresponding to the information index identification from a pre-constructed analysis information index database; the test scheduling reference information is used for representing the minimum condition required to be achieved when the resource scheduling is carried out on the test task to be processed;

13. An apparatus, comprising a processor and a memory:

the memory is used for storing a computer program;

the processor is configured to perform the method of any of claims 1-11 in accordance with the computer program.

14. A computer-readable storage medium, characterized in that the computer-readable storage medium is used to store a computer program for performing the method of any of claims 1-11.

15. A computer program product, characterized in that the computer program product, when run on a terminal device, causes the terminal device to perform the method of any of claims 1-11.