Method and device for generating test task in cloud platform, equipment and storage medium

Abstract

The invention provides a method, device and equipment for generating a test task in a cloud platform and a storage medium, and the method comprises the steps: obtaining operation log data of the cloud platform, and carrying out the grouping processing of the operation log data to obtain a plurality of user log groups, the operation log data in the same user log group having the same user identifier; performing user session division on the operation log data of each user log group in the plurality of user log groups to obtain operation combinations corresponding to the plurality of user log groups; analyzing and identifying the operation combinations corresponding to the plurality of user log groups to obtain a high-frequency operation combination corresponding to the cloud platform, and generating a test task of the cloud platform by using the high-frequency operation combination to test the use condition of the function module in the cloud platform. Visibly, according to the automatic test task generation mode based on the operation log data provided by the embodiment of the invention, the generation efficiency of the test task can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing, and in particular to a method, device, equipment and storage medium for generating test tasks in a cloud platform. Background Art

[0002] The cloud platform is a large-scale, distributed management system. Its essence is a service provision model. Through this model, resources in the shared resource pool can be accessed through the network anytime, anywhere and on demand. The resources in the shared resource pool include computing resources, network resources, and storage resources. These resources can be dynamically allocated and adjusted and flexibly divided among different users. By conducting usability testing on the cloud platform, we can understand how users use the cloud platform, so as to carry out targeted optimization and improvement and enhance the user experience.

[0003] At present, in the usability testing process of cloud platforms, testers are usually required to manually extract test tasks based on previous testing experience. Obviously, this method of manually extracting test tasks is inefficient and cannot accurately reflect the actual situation of the cloud platform in actual use. Summary of the invention

[0004] In order to solve the above technical problems, the embodiments of the present disclosure provide a method, apparatus, device and storage medium for generating a test task in a cloud platform.

[0005] In a first aspect, the present disclosure provides a method for generating a test task in a cloud platform, the method comprising:

[0006] Acquire the operation log data of the cloud platform, and group the operation log data to obtain a plurality of user log groups; wherein the operation log data is used to record the user operations corresponding to each functional module in the cloud platform, and the operation log data in the same user log group have the same user identifier;

[0007] Performing user session division on the operation log data of each user log group in the multiple user log groups to obtain operation combinations corresponding to the multiple user log groups; wherein the operation combinations include multiple user operations having an execution order relationship;

[0008] The operation combinations corresponding to the multiple user log groups are analyzed and identified to obtain high-frequency operation combinations corresponding to the cloud platform; wherein the high-frequency operation combinations are used to generate test tasks for the cloud platform, and the test tasks are used to test the usage of functional modules in the cloud platform.

[0009] In an optional implementation manner, the obtaining of the operation log data of the cloud platform includes:

[0010] Calling an agent module deployed on a target node in the cloud platform, collecting operation log data generated by a device connected to the target node, and storing the operation log data in a target database;

[0011] The operation log data of the cloud platform is obtained from the target database.

[0012] In an optional implementation manner, before storing the operation log data in the target database, the method further includes:

[0013] Performing data deduplication processing and missing value filling processing on the operation log data to obtain processed log data;

[0014] Accordingly, storing the operation log data in a target database includes:

[0015] The processed log data is sorted according to the event time, and the sorted log data is stored in the target database.

[0016] In an optional implementation, dividing the operation log data of each user log group in the multiple user log groups into user sessions to obtain operation combinations corresponding to the multiple user log groups includes:

[0017] For a first user log group among the multiple user log groups, calculating an event time interval between first operation log data and second operation log data; wherein the first operation log data and the second operation log data are two adjacent operation log data in the first user log group;

[0018] If it is determined that the event time interval is not less than the preset time interval, the first operation log data is divided into a first operation group, and the second operation log data is divided into a second operation group.

[0019] In an optional implementation manner, the method further includes:

[0020] If it is determined that the event time interval is less than the preset time interval, determining whether the request type of the first operation log data belongs to the target type;

[0021] If it is determined that the request type of the first operation log data belongs to the target type, the first operation log data is classified into the first operation group, and the second operation log data is classified into the second operation group.

[0022] In an optional implementation manner, each operation log data in the same user log group has an execution order relationship.

[0023] In a second aspect, the present disclosure provides a device for generating a test task in a cloud platform, the device comprising:

[0024] An acquisition module, used to acquire operation log data of the cloud platform, and group the operation log data to obtain multiple user log groups; wherein the operation log data is used to record user operations corresponding to each functional module in the cloud platform, and the operation log data in the same user log group have the same user identifier;

[0025] A first division module is used to divide the operation log data of each user log group in the multiple user log groups into user sessions to obtain operation combinations corresponding to the multiple user log groups; wherein the operation combinations include multiple user operations having an execution order relationship;

[0026] An identification module is used to analyze and identify the operation combinations corresponding to the multiple user log groups to obtain high-frequency operation combinations corresponding to the cloud platform; wherein the high-frequency operation combinations are used to generate test tasks for the cloud platform, and the test tasks are used to test the usage of the functional modules in the cloud platform.

[0027] In a third aspect, the present disclosure provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device implements the above method.

[0028] In a fourth aspect, the present disclosure provides a test task generation device in a cloud platform, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0029] In a fifth aspect, the present disclosure provides a computer program product, wherein the computer program product comprises a computer program / instructions, and the computer program / instructions implement the above method when executed by a processor.

[0030] Compared with the prior art, the technical solution provided by the embodiments of the present disclosure has at least the following advantages:

[0031] The disclosed embodiments provide a method, apparatus, device and storage medium for generating a test task in a cloud platform, the method comprising: obtaining operation log data of the cloud platform, and grouping the operation log data to obtain a plurality of user log groups, wherein the operation log data in the same user log group have the same user identifier; dividing the operation log data of each user log group in the plurality of user log groups by user session to obtain operation combinations corresponding to the plurality of user log groups; analyzing and identifying the operation combinations corresponding to the plurality of user log groups to obtain high-frequency operation combinations corresponding to the cloud platform, and then using the high-frequency operation combinations to generate test tasks for the cloud platform to test the usage of functional modules in the cloud platform.

[0032] It can be seen that the embodiments of the present disclosure can generate test tasks for the cloud platform by utilizing high-frequency operation combinations identified based on operation log data. Compared with the method of manually extracting tests based on test experience, the method of automatically generating test tasks based on operation log data provided by the embodiments of the present disclosure can reduce manual intervention and improve the efficiency of generating test tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0035] Figure 1 A flowchart of a method for generating a test task in a cloud platform provided by an embodiment of the present disclosure;

[0036] Figure 2 A flowchart of another method for generating a test task in a cloud platform provided by an embodiment of the present disclosure;

[0037] Figure 3 A schematic diagram of the structure of a test task generation device in a cloud platform provided by an embodiment of the present disclosure;

[0038] Figure 4 A schematic diagram of the structure of a test task generating device in a cloud platform provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0039] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0040] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0041] With the rapid development of cloud computing technology, cloud platforms have become an important part of enterprise IT architecture. As a user-oriented service platform, the availability of cloud platforms is not only related to the continuity and stability of enterprise business, but also directly affects the user experience and satisfaction. By conducting usability testing on cloud platforms, we can understand how users use cloud platforms, so as to carry out targeted optimization and improvement to enhance the user experience.

[0042] At present, in the usability testing process of cloud platforms, testers are usually required to manually extract test tasks based on previous testing experience. Obviously, this method of manually extracting test tasks is inefficient and cannot accurately reflect the actual situation of the cloud platform in actual use.

[0043] To this end, an embodiment of the present disclosure provides a method for generating a test task in a cloud platform. Specifically, operation log data of the cloud platform is obtained, and the operation log data is grouped and processed to obtain multiple user log groups, wherein the operation log data in the same user log group has the same user identifier; the operation log data of each user log group in the multiple user log groups is divided into user sessions to obtain operation combinations corresponding to the multiple user log groups; the operation combinations corresponding to the multiple user log groups are analyzed and identified to obtain high-frequency operation combinations corresponding to the cloud platform, and then the high-frequency operation combinations are used to generate test tasks for the cloud platform to test the usage of functional modules in the cloud platform.

[0044] It can be seen that the embodiments of the present disclosure can generate test tasks for the cloud platform by utilizing high-frequency operation combinations identified based on operation log data. Compared with the method of manually extracting tests based on test experience, the method of automatically generating test tasks based on operation log data provided by the embodiments of the present disclosure can reduce manual intervention and improve the efficiency of generating test tasks.

[0045] Based on this, the present disclosure provides a method for generating a test task in a cloud platform. Figure 1 , is a flow chart of a method for generating a test task in a cloud platform provided by an embodiment of the present disclosure, the method specifically comprising:

[0046] S101: Acquire operation log data of the cloud platform, and group the operation log data to obtain multiple user log groups.

[0047] The operation log data is used to record user operations corresponding to each functional module in the cloud platform, and the operation log data in the same user log group have the same user identifier.

[0048] The method for generating test tasks in the cloud platform provided by the embodiments of the present disclosure can be applied to a client, for example, the client may include a client deployed on a tablet computer, etc., and can also be applied to a server, which is used to generate test tasks for the cloud platform.

[0049] In the embodiment of the present disclosure, operation log data refers to data used to record the interaction behavior between users and various functional modules in the cloud platform. The operation log data may include user login operations, data addition, deletion, modification and query operations, and other operation records related to user interactions.

[0050] In an optional implementation, proxy modules may be deployed on the target nodes of the cloud platform respectively, and operation log data generated by devices connected to the target nodes may be collected by calling the proxy modules deployed on the target nodes, and the collected operation log data may be stored in the target database.

[0051] The target node may include cloud servers, databases, network devices, etc. provided on the cloud platform. The cloud server is a virtualized resource used to simulate the functions of a traditional physical server. Users can run operating systems and applications on the cloud server. In the process of running operating systems and applications, corresponding operation log data will be generated. The target database may include a database corresponding to the cloud platform log collection system, which is used to store the user's operation log data.

[0052] In an optional implementation, since most of the collected operation log data is data generated from different devices, and the operating systems used by different devices may be different, the structure of the generated data may not be the same as the data structure of the target database. In order to successfully store the operation log data in the target database, after collecting the original data generated by the device connected to the target node, the embodiment of the present disclosure first converts the original data into operation log data of the target data structure, and then stores the operation log data of the target data structure in the target database. In practical applications, the operation log data of the target data structure can be stored in the target database using a designated secure channel. For example, a hypertext transfer protocol channel can be used to transfer the operation log data to the target database for storage.

[0053] The target data format may include fields such as event identifier, event time, source address, user name, user identifier, service name, resource type name, operation event, operation object name, operation object identifier, request type, event level, operation result, etc.

[0054] In the disclosed embodiment, after obtaining the operation log data of the cloud platform, the operation log data is grouped and processed according to the user identifier in the operation log data to obtain multiple user log groups. Since the operation log data in the same user log group has the same user identifier, it can be ensured that the operation log data of the same user are in the same user log group.

[0055] S102: Divide the operation log data of each user log group in the multiple user log groups into user sessions to obtain operation combinations corresponding to the multiple user log groups.

[0056] The operation combination includes a plurality of user operations having an execution order relationship.

[0057] In the embodiment of the present disclosure, after obtaining multiple user log groups, the operation log data of each user log group in the multiple user log groups is divided into user sessions to obtain operation combinations corresponding to the multiple user log groups.

[0058] In an optional implementation, multiple user log groups include a first user log group, wherein the first user log group can be any one of the multiple log groups, and by dividing the operation log data of each user log group in the multiple user log groups by user session, the operation combinations corresponding to the multiple user log groups can be obtained.

[0059] In the embodiment of the present disclosure, firstly, for a first user log group among multiple user log groups, the event time interval between the first operation log data and the second operation log data is calculated; if it is determined that the event time interval between the first operation log data and the second operation log data is not less than the preset time interval, the first operation log data is divided into the first operation combination, and the second operation log data is divided into the second operation combination. Wherein, the first operation log data and the second operation log data are two adjacent operation log data in the first user log group.

[0060] Exemplarily, assuming that the preset time interval is 30 minutes, the first user log group includes data 1, data 2 and data 3, the event time corresponding to data 1 is 06:01:00 (expressed in hour, minute and second format), the event time corresponding to data 2 is 06:02:00, and the event time corresponding to data 3 is 06:34:01. Assuming that the first operation log data is data 2 and the second operation log data is data 3, it can be determined that the event time interval between the first operation log data and the second operation log data is 32 minutes, which is greater than the preset time interval of 30 minutes. At this time, the first operation log data is divided into the first operation combination (i.e., the previous operation combination), and the second operation log data is divided into the second operation combination (i.e., the next operation combination).

[0061] For another example, assuming that the first operation log data is data 1 and the second operation log is data 2, it can be determined that the event time interval between the first operation log data (data 1) and the second operation log data (data 2) is 1 minute, which is less than the preset time interval. At this time, the first operation log data (data 1) and the second operation log data (data 2) are classified into the same operation combination.

[0062] In an optional implementation, in order to further improve the recognition accuracy of the operation combination, when it is determined that the event time interval between the first operation log data and the second operation log data is less than the preset time interval, the request type of the first operation log data can be judged. Specifically, if it is determined that the event time interval is less than the preset time interval, it is determined whether the request type of the first operation log data belongs to the target type; if it is determined that the request type of the first operation log data belongs to the target type, the first operation log data is classified into the first operation combination, and the second operation log data is classified into the second operation combination. Among them, the target type can include the system logout type, the user's active session end operation type, etc.

[0063] S103: Analyze and identify the operation combinations corresponding to the multiple user log groups to obtain high-frequency operation combinations corresponding to the cloud platform.

[0064] The high-frequency operation combination is used to generate a test task for the cloud platform, and the test task is used to test the usage of the functional modules in the cloud platform.

[0065] In the disclosed embodiment, after the operation log data of each user log group in the multiple user log groups is divided into user sessions and the operation combinations corresponding to the multiple user log groups are obtained, the operation combinations corresponding to the multiple user log groups are analyzed and identified to obtain the high-frequency operation combinations corresponding to the cloud platform, so as to generate test tasks for the cloud platform using the high-frequency operation combinations. The test tasks are used to test the usage of the functional modules in the cloud platform.

[0066] The high-frequency operation combinations can also be further classified, for example, according to the number of high-frequency operation combinations, the identified high-frequency operation combinations can be divided into high-complexity operation combinations, medium-complexity operation combinations, or low-complexity operation combinations. Furthermore, based on the classified high-frequency operation combinations, the test tasks of the cloud platform are generated in combination with the actual business scenarios.

[0067] In an optional implementation, the test task may include information such as operation sequence, expected results, and test objectives. The arrangement of the operation sequence depends on the order of operations in the high-frequency operation combination, and the user needs to provide basic input data for each step. The expected result refers to the corresponding test result or system status after the operation sequence is completed under normal circumstances. The test objectives can be used to describe which functional modules are tested in which aspects, such as verifying the integrity of a certain function, evaluating the smoothness of operation, etc.

[0068] In the method for generating test tasks in the cloud platform provided by the embodiments of the present disclosure, operation log data of the cloud platform is obtained, and the operation log data is grouped and processed to obtain multiple user log groups, wherein the operation log data in the same user log group has the same user identifier; the operation log data of each user log group in the multiple user log groups is divided into user sessions to obtain operation combinations corresponding to the multiple user log groups; the operation combinations corresponding to the multiple user log groups are analyzed and identified to obtain high-frequency operation combinations corresponding to the cloud platform, and then the test tasks of the cloud platform are generated using the high-frequency operation combinations to test the usage of the functional modules in the cloud platform.

[0069] It can be seen that the embodiments of the present disclosure can generate test tasks for the cloud platform by utilizing high-frequency operation combinations identified based on operation log data. Compared with the method of manually extracting tests based on test experience, the method of automatically generating test tasks based on operation log data provided by the embodiments of the present disclosure can reduce manual intervention and improve the efficiency of generating test tasks.

[0070] In an optional implementation, after collecting the operation log data generated by the device connected to the target node and storing the operation log data in the target database, in order to improve the quality of the operation log data, the operation log data may be preprocessed, wherein the preprocessing may include data deduplication processing and missing value filling processing, etc. Specifically, the operation log data with the same event identifier is first determined as duplicate data, and the duplicate data is deleted; in addition, the operation log data in which the content of other fields is the same except for the event identifier and the operation result, and the time interval between the events of two adjacent data is less than 1 minute, may be determined as duplicate data, and the duplicate data is deleted.

[0071] In the disclosed embodiment, after deduplication processing is performed on the operation log data to obtain the deduplication data, missing value filling processing can also be performed on the deduplication data. Specifically, the proportion of data with missing information values ​​in the deduplication data is first detected. If it is determined that the data with missing information values ​​exceeds 75% of the deduplication data, the deletion method is used to directly delete the data with missing information values ​​from the target database; if it is determined that the data with missing information values ​​does not exceed 75% of the deduplication data, the filling method is used to fill the data with missing information values. For example, the median or mode of the data can be used to fill the data with missing information values ​​to obtain the filled operation log data.

[0072] In an optional implementation, after the collected operation log data is deduplicated and missing value filled to obtain processed log data, the processed log data can also be sorted according to event time and the sorted log data can be stored in the target database.

[0073] In the disclosed embodiment, after the operation log data is sorted in ascending order according to event time to obtain the sorted log data, the sorted operation log data is first grouped so that the operation log data of the same user are gathered in the same user log group; then the operation log data with an execution order relationship in each user log group is divided into user sessions to obtain operation combinations corresponding to multiple user log groups.

[0074] In an optional implementation, a sequence pattern mining algorithm GSP can be used to analyze and identify the operation combinations corresponding to multiple user log groups to obtain high-frequency operation combinations corresponding to the cloud platform. GSP (Generalized Sequential Pattern Mining) is a data mining technology used to mine sequence patterns from large databases.

[0075] Specifically, first, the minimum support is set, where the support refers to the frequency of a single operation or an ordered combination of operations appearing in all user log groups. In actual applications, it can be set according to specific circumstances such as user granularity. The embodiment of the present disclosure can set the minimum support to 0.1.

[0076] Then, create an initial sequence; specifically, all user log groups can be traversed to calculate the support of each operation combination in the user log group, and the operations with support greater than the set minimum support are selected to form a frequent 1-sequence with a length of 1. Secondly, construct candidate 2-sequences; specifically, for each sequence in the frequent 1-sequence, connect it with other sequences to generate an initial candidate 2-sequence; then, generate frequent 2-sequences; specifically, calculate the support of each sequence in the candidate 2-sequence, and select the sequences with support greater than the minimum support to form a frequent 2-sequence with a length of 2.

[0077] Further, a candidate 3-sequence is constructed; specifically, for any two sequences s1 and s2 in the frequent 2-sequence, the first item of s1 and the last item of s2 are removed. If the remaining sequences are the same, the last item of s2 is added to the end of s1 and connected to the end of s1 to generate an initial candidate 3-sequence. In the process of constructing a candidate 3-sequence, if a subsequence of a new sequence is not a frequent sequence, the sequence is deleted from the initial candidate 3-sequence to generate a final candidate 3-sequence. Then, a frequent 3-sequence is generated; specifically, the support of each sequence in the candidate 3-sequence is calculated, and the sequences with a support greater than the minimum support are selected to form a frequent 3-sequence of length 3.

[0078] Then, longer candidate sequences are continuously generated until no new frequent sequences are generated. Among them, all frequent sequences are the high-frequency operation combination sets corresponding to the cloud platform.

[0079] like Figure 2 As shown, it is a flow chart of another method for generating test tasks in a cloud platform provided by an embodiment of the present disclosure.

[0080] Collect the operation log data of the cloud platform, for example, call the proxy module deployed on the target node in the cloud platform to collect the operation log data generated by the device connected to the target node. Then pre-process the operation log data, for example, perform data deduplication and missing value filling on the operation log data, and sort the processed log data according to the event time to obtain the operation log data with the execution order relationship. Then, group the pre-processed operation log data to obtain multiple user log groups, and the operation log data in the same user log group have the same user ID. Then, divide the operation log data of each user log group in the multiple user log groups into user sessions to obtain the operation combinations corresponding to the multiple user log groups; further, analyze and identify the operation combinations corresponding to the multiple user log groups to obtain the high-frequency operation combinations corresponding to the cloud platform; finally, use the high-frequency operation combinations to generate the availability test tasks of the cloud platform.

[0081] Based on the above method embodiment, the present disclosure also provides a device for generating a test task in a cloud platform, referring to Figure 3 , is a schematic diagram of a structure of a test task generation device in a cloud platform provided by an embodiment of the present disclosure, the device comprising:

[0082] The acquisition module 301 is used to acquire the operation log data of the cloud platform, and group the operation log data to obtain multiple user log groups; wherein the operation log data is used to record the user operations corresponding to each functional module in the cloud platform, and the operation log data in the same user log group have the same user identifier;

[0083] A first division module 302 is used to divide the operation log data of each user log group in the multiple user log groups into user sessions to obtain operation combinations corresponding to the multiple user log groups;

[0084] The identification module 303 is used to analyze and identify the operation combinations corresponding to the multiple user log groups to obtain high-frequency operation combinations corresponding to the cloud platform; wherein the high-frequency operation combinations are used to generate test tasks for the cloud platform, and the test tasks are used to test the usage of the functional modules in the cloud platform.

[0085] In an optional implementation manner, the acquisition module includes:

[0086] A collection submodule, used to call the agent module deployed on the target node in the cloud platform, collect the operation log data generated by the device connected to the target node, and store the operation log data in the target database;

[0087] The acquisition submodule is used to obtain the operation log data of the cloud platform from the target database.

[0088] In an optional implementation, the device further includes:

[0089] A processing module, used to perform data deduplication processing and missing value filling processing on the operation log data to obtain processed log data;

[0090] Correspondingly, the collected submodule is specifically used for:

[0091] The processed log data is sorted according to the event time, and the sorted log data is stored in the target database.

[0092] In an optional implementation manner, the first division module includes:

[0093] A calculation submodule, configured to calculate, for a first user log group among the plurality of user log groups, an event time interval between first operation log data and second operation log data; wherein the first operation log data and the second operation log data are two adjacent operation log data in the first user log group;

[0094] The division submodule is used to divide the first operation log data into a first operation combination and divide the second operation log data into a second operation combination if it is determined that the event time interval is not less than a preset time interval.

[0095] In an optional implementation, the device further includes:

[0096] a determination module, configured to determine whether the request type of the first operation log data belongs to a target type if it is determined that the event time interval is less than a preset time interval;

[0097] The second division module is used to divide the first operation log data into the first operation combination and divide the second operation log data into the second operation combination if it is determined that the request type of the first operation log data belongs to the target type.

[0098] In an optional implementation manner, each operation log data in the same user log group has an execution order relationship.

[0099] In the method for generating test tasks in the cloud platform provided by the embodiment of the present disclosure, the operation log data of the cloud platform is obtained, and the operation log data is grouped and processed to obtain multiple user log groups, wherein the operation log data in the same user log group has the same user identifier; the operation log data of each user log group in the multiple user log groups is divided into user sessions to obtain operation combinations corresponding to the multiple user log groups; the operation combinations corresponding to the multiple user log groups are analyzed and identified to obtain high-frequency operation combinations corresponding to the cloud platform, and then the test tasks of the cloud platform are generated using the high-frequency operation combinations to test the usage of the functional modules in the cloud platform. It can be seen that the embodiment of the present disclosure can generate the test tasks of the cloud platform using the high-frequency operation combinations obtained based on the identification of the operation log data. Compared with the method of manually extracting tests based on test experience, the method of automatically generating test tasks based on the operation log data provided by the embodiment of the present disclosure can reduce manual intervention and improve the generation efficiency of test tasks.

[0100] In addition to the above-mentioned methods and apparatus, the embodiments of the present disclosure also provide a computer-readable storage medium, which stores instructions. When the instructions are executed on a terminal device, the terminal device implements the method for generating test tasks in the cloud platform described in the embodiments of the present disclosure.

[0101] The embodiment of the present disclosure also provides a computer program product, which includes a computer program / instructions. When the computer program / instructions are executed by a processor, the method for generating a test task in the cloud platform described in the embodiment of the present disclosure is implemented.

[0102] In addition, the present disclosure also provides a test task generation device in a cloud platform, see Figure 4 As shown, it may include:

[0103] Processor 401, memory 402, input device 403 and output device 404. The number of processors 401 in the test task generation device in the cloud platform can be one or more. Figure 4 In some embodiments of the present disclosure, the processor 401, the memory 402, the input device 403 and the output device 404 may be connected via a bus or other means, wherein: Figure 4 The example of connecting through bus is taken in the following.

[0104] The memory 402 can be used to store software programs and modules, and the processor 401 executes various functional applications and data processing of the test task generation device in the cloud platform by running the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application required for a function, and the like. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. The input device 403 may be used to receive input digital or character information, and to generate signal inputs related to user settings and function controls of the test task generation device in the cloud platform.

[0105] Specifically in this embodiment, the processor 401 will load the executable files corresponding to the processes of one or more applications into the memory 402 according to the following instructions, and the processor 401 will run the applications stored in the memory 402, thereby realizing various functions of the test task generation device in the above-mentioned cloud platform.

[0106] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0107] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for generating a test task in a cloud platform, characterized in that: The method comprises: Acquire the operation log data of the cloud platform, and group the operation log data to obtain a plurality of user log groups; wherein the operation log data is used to record the user operations corresponding to each functional module in the cloud platform, and the operation log data in the same user log group have the same user identifier; Performing user session division on the operation log data of each user log group in the multiple user log groups to obtain operation combinations corresponding to the multiple user log groups; The operation combinations corresponding to the multiple user log groups are analyzed and identified to obtain high-frequency operation combinations corresponding to the cloud platform; wherein the high-frequency operation combinations are used to generate test tasks for the cloud platform, and the test tasks are used to test the usage of functional modules in the cloud platform.

2. The method according to claim 1, characterized in that The obtaining of the operation log data of the cloud platform includes: Calling an agent module deployed on a target node in the cloud platform, collecting operation log data generated by a device connected to the target node, and storing the operation log data in a target database; The operation log data of the cloud platform is obtained from the target database.

3. The method according to claim 2, characterized in that Before storing the operation log data in the target database, the method further includes: Performing data deduplication processing and missing value filling processing on the operation log data to obtain processed log data; Accordingly, storing the operation log data in a target database includes: The processed log data is sorted according to the event time, and the sorted log data is stored in the target database.

4. The method according to claim 1, characterized in that: The performing user session division on the operation log data of each user log group in the multiple user log groups to obtain operation combinations corresponding to the multiple user log groups includes: For a first user log group among the multiple user log groups, calculating an event time interval between first operation log data and second operation log data; wherein the first operation log data and the second operation log data are two adjacent operation log data in the first user log group; If it is determined that the event time interval is not less than the preset time interval, the first operation log data is divided into a first operation group, and the second operation log data is divided into a second operation group.

5. The method according to claim 4, characterized in that The method further comprises: If it is determined that the event time interval is less than the preset time interval, determining whether the request type of the first operation log data belongs to the target type; If it is determined that the request type of the first operation log data belongs to the target type, the first operation log data is classified into the first operation group, and the second operation log data is classified into the second operation group.

6. The method according to claim 1, characterized in that The operation log data in the same user log group have an execution order relationship.

7. A device for generating test tasks in a cloud platform, characterized in that: The device comprises: An acquisition module, used to acquire operation log data of the cloud platform, and group the operation log data to obtain multiple user log groups; wherein the operation log data is used to record user operations corresponding to each functional module in the cloud platform, and the operation log data in the same user log group have the same user identifier; A first division module is used to divide the operation log data of each user log group in the multiple user log groups into user sessions to obtain operation combinations corresponding to the multiple user log groups; wherein the operation combinations include multiple user operations having an execution order relationship; An identification module is used to analyze and identify the operation combinations corresponding to the multiple user log groups to obtain high-frequency operation combinations corresponding to the cloud platform; wherein the high-frequency operation combinations are used to generate test tasks for the cloud platform, and the test tasks are used to test the usage of the functional modules in the cloud platform.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device implements the method according to any one of claims 1 to 6.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program / instruction, and when the computer program / instruction is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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