Consistency determination method and device for cross-platform migration

Abstract

The invention provides a consistency determination method and device for cross-platform migration, and relates to the field of artificial intelligence, in particular to the fields of large models, natural language processing, deep learning and the like. According to the specific implementation scheme, in response to a migration evaluation request from a client side, first page information of a first migration platform and second page information of a second migration platform are obtained, a corresponding first test case is generated according to the first page information, a corresponding second test case is generated according to the second page information, and the first test case and the second test case are used for testing. And determining the consistency between the first migration platform and the second migration platform based on the test data used for testing the same interaction function in the first test case and the second test case, thereby effectively realizing the overview and tracking of the page information used for realizing the interaction function on the platform, and automatically generating the test case, and improving the test efficiency. And determining the influence of the interaction function on the consistency between the two migration platforms through the test case.

Description

Technical Field

[0001] The present disclosure relates to the field of AI (Artificial Intelligence), specifically to technical fields such as large models, natural language processing, and deep learning, and particularly relates to a method and apparatus for determining the consistency of cross-platform migration. Background Art

[0002] As the communication with users becomes more in-depth, in order to meet the diverse needs of users, rich interactive functions are added to the page structure. During the subsequent process of platform migration, multiple complex interactive functions are the main influencing factors for evaluating whether the functions between the old and new platforms are consistent and whether users can adapt to the new platform.

[0003] Therefore, how to determine the consistency of the interactive functions between the old and new platforms before and after platform migration is particularly important. Summary of the Invention

[0004] The present disclosure provides a method and apparatus for determining the consistency of cross-platform migration.

[0005] According to one aspect of the present disclosure, a method for determining the consistency of cross-platform migration is provided, including: in response to a migration evaluation request from a client, obtaining first page information of a first migration platform and second page information of a second migration platform; generating corresponding first test cases according to the first page information, and generating corresponding second test cases according to the second page information; determining the consistency between the first migration platform and the second migration platform based on the test data for testing the same interactive function among the first test cases and the second test cases.

[0006] According to another aspect of the present disclosure, an apparatus for determining the consistency of cross-platform migration is provided, including: a first obtaining module, which obtains first page information of a first migration platform and second page information of a second migration platform in response to a migration evaluation request from a client; a generating module, which is used to generate corresponding first test cases according to the first page information and generate corresponding second test cases according to the second page information; a first determining module, which is used to determine the consistency between the first migration platform and the second migration platform based on the test data for testing the same interactive function among the first test cases and the second test cases.

[0007] According to still another aspect of the present disclosure, an electronic device is provided, including:

[0008] At least one processor; and

[0009] A memory communicatively connected to the at least one processor; wherein,

[0010] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the cross-platform migration consistency determination method proposed in the above aspect of the present disclosure.

[0011] According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the cross-platform migration consistency determination method proposed in the above aspect of the present disclosure.

[0012] According to still another aspect of the present disclosure, there is provided a computer program product including a computer program which, when executed by a processor, implements the cross-platform migration consistency determination method proposed in the above aspect of the present disclosure.

[0013] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings are used to better understand the solution and do not constitute a limitation to the present disclosure. Among them:

[0015] Figure 1 is a flowchart of the cross-platform migration consistency determination method provided in Embodiment 1 of the present disclosure;

[0016] Figure 2 is a flowchart of the cross-platform migration consistency determination method provided in Embodiment 2 of the present disclosure;

[0017] Figure 3 is a flowchart of the cross-platform migration consistency determination method provided in Embodiment 3 of the present disclosure;

[0018] Figure 4 is a flowchart of the cross-platform migration consistency determination method provided in Embodiment 4 of the present disclosure;

[0019] Figure 5 is a flowchart of the cross-platform migration consistency determination method provided in Embodiment 5 of the present disclosure;

[0020] Figure 6 is a flowchart of the cross-platform migration consistency determination method provided in Embodiment 6 of the present disclosure;

[0021] Figure 7 is a structural diagram of the cross-platform migration consistency determination device provided in an embodiment of the present disclosure;

[0022] Figure 8 It is a block diagram of an electronic device for implementing the consistency determination method for cross - platform migration in embodiments of the present disclosure. Detailed implementation manners

[0023] The following describes exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, descriptions of well - known functions and structures are omitted below for clarity and conciseness.

[0024] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information and other processing are all carried out on the premise of obtaining the user's consent, and all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0025] The following describes the cross - platform migration consistency determination method and apparatus in embodiments of the present disclosure with reference to the drawings.

[0026] It should be noted that the execution subject of the cross - platform migration consistency determination method in this embodiment is a cross - platform migration consistency determination apparatus. The cross - platform migration consistency determination apparatus can be implemented in software and / or hardware and can be configured in an electronic device.

[0027] In common platforms, in order to meet the rich needs of users, multiple interactive functions are usually configured on the platform page. If a request to migrate the platform is triggered, in order to make the user feel natural even when using the new migrated platform, it is particularly important to determine the consistency of the interactive functions between the old platform and the new platform before migration.

[0028] In related technologies, in order to determine the consistency between different platforms, the following methods are usually adopted:

[0029] The first method uses manually designed test cases to cover all elements on the web pages of the platform without differentiating the elements.

[0030] It should be noted that when determining the consistency between different platforms by the above methods, at least the following problems exist:

[0031] Regarding the first method, multiple interactive functions are the main factors affecting the consistency between different platforms. If the same interactive function owned by two platforms is not analyzed in detail when determining the consistency between the two platforms, even if the platform migration is completed, the user experience effect will be seriously affected.

[0032] Figure 1 Schematic flowchart of the method for determining consistency in cross-platform migration provided by Embodiment 1 of the present disclosure.

[0033] As shown in Figure 1 the following steps may be included in the method for determining consistency in cross-platform migration:

[0034] Step 101: In response to a migration evaluation request from a client, obtain the first page information of the first migration platform and the second page information of the second migration platform.

[0035] It should be noted that among the first migration platform and the second migration platform, the following two situations may be included: The first situation is that the first migration platform is the platform for data to be migrated, and the second migration platform is the platform for receiving the migrated data from the first migration platform; the second situation is that the second migration platform is the platform for data to be migrated, and the first migration platform is the platform for receiving the migrated data from the second migration platform. The specific actual situation can be determined according to actual needs, and this embodiment does not specifically limit the first migration platform and the second migration platform.

[0036] It should be noted that the specific business scenarios applicable to the first migration platform and the second migration platform are determined according to the actual situation, and this embodiment does not make specific limitations. For example, both the first migration platform and the second migration platform can be e-commerce platforms.

[0037] It should be understood that in actual situations, with the gradual maturity of technology and the in-depth exploration of user needs, the pages on the platform are becoming increasingly rich. Correspondingly, the page information obtained is gradually increasing. However, this will greatly affect the subsequent progress of analyzing the page information and generating test cases.

[0038] Step 102: Generate a corresponding first test case according to the first page information, and generate a corresponding second test case according to the second page information.

[0039] It should be understood that in actual scenarios, the interaction function is the main factor affecting whether the two platforms are consistent and whether users can adapt to the new platform. Therefore, in the process of generating test cases according to the page information, the elements used to implement the interaction function in the page information can be focused on.

[0040] As an example, analyze all the elements included in the page information, select the elements used to implement the interaction function from all the elements, and generate test cases according to the elements used to implement the interaction function.

[0041] Step 103: Determine the consistency between the first migration platform and the second migration platform based on the test data for testing the same interaction function among the first test case and the second test case.

[0042] It should be understood that in actual situations, since there are multiple interactive functions that can be implemented on the platform, the interactive functions that can be tested by the data included in the generated test cases can also be diverse. Therefore, the data included in the test cases can also be distinguished according to the interactive functions for which the data is used for testing.

[0043] For example, in the first test case, there is test data A for testing the interactive function of search and test data B for testing the interactive function of login. In the second test case, there is test data C for testing the interactive function of search. Then, the test data for testing the same interactive function (search) in the first test case and the second test case are test data A and test data C.

[0044] In summary, the method for determining the consistency of cross-platform migration proposed in the present disclosure, in response to a migration evaluation request from a client, obtains the first page information of the first migration platform and the second page information of the second migration platform, generates a corresponding first test case according to the first page information, and generates a corresponding second test case according to the second page information. Based on the test data for testing the same interactive function in the first test case and the second test case, the consistency between the first migration platform and the second migration platform is determined. Thus, by analyzing the page information in the migration platform, test cases for the two migration platforms are respectively generated, and by comparing the generated test cases, the consistency between the two migration platforms is determined, effectively realizing the overview and tracking of the page information used to implement interactive functions on the platform. Moreover, it can automatically generate test cases, and the test cases contain the data for implementing interactive functions that are the key concerns. Through the test cases, there is no need to laboriously analyze and compare the information for implementing interactive functions on the two migration platforms one by one, increasing the analysis cost and affecting the analysis efficiency. Moreover, the impact of interactive functions on the consistency between the two migration platforms is taken into account, which helps to improve the user experience of the new migration platform.

[0045] It should be noted that in the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision, and disclosure of the user's personal information and other processing are all carried out on the premise of obtaining the user's consent, and all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0046] To illustrate how the corresponding first test case is generated according to the first page information and how the corresponding second test case is generated according to the second page information in the embodiments of the present disclosure, the present disclosure also proposes a method for determining the consistency of cross-platform migration.

[0047] Figure 2Schematic flowchart of the consistency determination method for cross-platform migration provided in the second embodiment of the present disclosure.

[0048] As Figure 2 shown, the consistency determination method for cross-platform migration may include the following steps:

[0049] Step 201, in response to a migration evaluation request from a client, obtain the first page information of the first migration platform and the second page information of the second migration platform.

[0050] It should be noted that the explanation of step 201 can be referred to the relevant description in any embodiment of the present disclosure, and will not be elaborated here.

[0051] Step 202, for the page information to be processed in the first page information and the second page information, parse to obtain at least one interactive element.

[0052] It should be understood that, usually, there are multiple elements in the page information to be processed, but not all elements are used to implement interactive functions. Moreover, since there can be multiple types of interactive functions that can be implemented by the platform, thus, focus on selecting the interactive elements in the page information to be processed that are used to implement interactive functions, and the interactive elements can also be distinguished according to the interactive functions implemented by the interactive elements.

[0053] In order to completely parse the page information to be processed to determine at least one interactive element, as a possible implementation manner, traverse and analyze the page structure composed of the page information to be processed to determine the interactive element.

[0054] As an example, obtain the page structure composed of the page information to be processed, traverse and analyze the page structure to determine at least one node in the page structure that is used to implement interactive functions, and based on the nodes used to implement interactive functions, determine at least one interactive element.

[0055] Step 203, according to the interactive functions implemented by the interactive elements on the corresponding first migration platform or second migration platform, determine the target test case template through a preset mapping relationship table between interactive functions and test case templates.

[0056] It should be understood that since different migration platforms are written by different technicians, with different writing styles, even for interactive elements that implement the same interactive function, the test cases generated by different migration platforms will be different. In order not to slow down the progress of subsequent analysis of the test cases generated by different migration platforms, the overall structure of the generated test cases is unified through test case templates.

[0057] To determine the target test case template, as a possible implementation, the target test case template is determined according to the target interaction function that the interaction element is used to implement.

[0058] As an example, analyze the interaction element to determine the target interaction function that the interaction element is used to implement; from the mapping relationship table between the interaction function and the test case template, determine the target test case template corresponding to the target interaction function.

[0059] It should be noted that the mapping relationship table between the interaction function and the test case template includes at least one interaction function and the corresponding test case template.

[0060] For example, the mapping relationship table between the interaction function and the test case template is shown in Table 1. In Table 1, there are search interaction functions, login interaction functions, and jump interaction functions. There is a mapping relationship between the search interaction function and test case template a, a mapping relationship between the login interaction function and test case template b, and a mapping relationship between the jump interaction function and test case template c. Assume that the target interaction function that the interaction element is used to implement is the login interaction function. Then, according to the mapping relationship table between the interaction function and the test case template, the test case template corresponding to the target interaction function (login interaction function) is determined to be test case template b, and test case template b is used as the target test case template.

[0061] Table 1 Mapping Relationship Table between Interaction Function and Test Case Template

[0062] Interaction function Test case template Search interaction function Test case template a Login interaction function Test case template b Jump interaction function Test case template c

[0063] Step 204, according to the interaction element, generate the first test case or the second test case corresponding to the page information to be processed through the target test case template.

[0064] It should be understood that since users have developed usage habits on the platform where the data to be migrated is located, in order to enable users to adapt to the new migration platform, during the process of determining the consistency between the first migration platform and the second migration platform, not only the consistency of the specific implementation effects of the interaction functions needs to be concerned, but also the page structure and the data flow information involved in the interaction functions on the platform need to be concerned.

[0065] For example, on the first migration platform, the search function is located above the page structure, and on the second migration platform, the search function is located below the page structure. Assume that the first migration platform is the platform where the data to be migrated is located, and users have adapted to the search interaction function being above on the first migration platform. The same search interaction function located in different page structures will affect users' adaptability to the new platform.

[0066] To completely generate the first test case or the second test case, as a possible implementation, according to the interaction elements, page structure information, and data flow information, generate the first test case or the second test case corresponding to the page information to be processed.

[0067] As an example, obtain the page structure information and data flow information associated with the interaction elements; fill the interaction elements, page structure information, and data flow information into the target test case template correspondingly to generate the first test case or the second test case corresponding to the page information to be processed.

[0068] Step 205: Based on the test data for testing the same interaction function among the first test case and the second test case, determine the consistency between the first migration platform and the second migration platform.

[0069] It should be noted that the explanation of step 205 can refer to the relevant descriptions in any embodiment of the present disclosure and will not be elaborated here.

[0070] In summary, for the page information to be processed in the first page information and the second page information, at least one interaction element is parsed; according to the interaction function implemented by the interaction element on the corresponding first migration platform or second migration platform, the target test case template is determined through the preset mapping relationship table between the interaction function and the test case template; according to the interaction element, through the target test case template, the first test case or the second test case corresponding to the page information to be processed is generated. Thus, according to the interaction function implemented by the interaction element, through the mapping relationship table between the interaction function and the test case template, the first test case or the second test case corresponding to the page information to be processed is generated. This can not only distinguish the interaction elements based on the interaction function, but also determine the target test case template according to the implemented interaction function, and can quickly generate the unified first test case or the second test case, avoiding the difficulty of subsequent analysis of the first test case and the second test case due to differences in writing styles, and greatly improving the efficiency of obtaining the test data for testing the same interaction function.

[0071] To illustrate how to determine the test data for testing the same interaction function among the first test case and the second test case in the embodiments of the present disclosure, the present disclosure also proposes a method for determining the consistency of cross-platform migration.

[0072] Figure 3 It is a schematic flowchart of the method for determining the consistency of cross-platform migration provided in Embodiment 3 of the present disclosure.

[0073] As Figure 3 shown, the method for determining the consistency of cross-platform migration may include the following steps:

[0074] Step 301: In response to a migration evaluation request from a client, obtain the first page information of the first migration platform and the second page information of the second migration platform.

[0075] Step 302: Generate corresponding first test cases according to the first page information, and generate corresponding second test cases according to the second page information.

[0076] It should be noted that the explanations of Step 301 and Step 302 can refer to the relevant descriptions in any embodiment of the present disclosure, and will not be elaborated here.

[0077] Step 303: Select a first interaction element from the interaction elements included in the first test case, and select a second interaction element from the interaction elements included in the second test case, where the first interaction element and the second interaction element are used to implement the same interaction function.

[0078] For example, the first test case includes interaction element a and interaction element b, where interaction element a is used to implement the search interaction function and interaction element b is used to implement the login interaction function; the second test case includes interaction element c and interaction element d, where interaction element c is used to implement the search interaction function and interaction element d is used to implement the jump interaction function; then the interaction function implemented by interaction element a (search interaction function) and the interaction function implemented by interaction element c (search interaction function) are the same interaction function. Therefore, among interaction element a and interaction element b, select interaction element a as the first interaction element, and among interaction element c and interaction element d, select interaction element c as the second interaction element.

[0079] Step 304: Determine test data for testing the same interaction function according to at least one of the first interaction element, the page structure information associated with the first interaction element, and the data flow information, and according to at least one of the second interaction element, the page structure information associated with the second interaction element, and the data flow information.

[0080] Among them, it should be noted that even for interaction elements that implement the same interaction function, the page structure information and data flow information associated with the interaction elements are different on different platforms.

[0081] For example, the image data format associated with the first interaction element on the first migration platform is the JPEG format, and the image data format associated with the second interaction element on the second migration platform is the PNG format. Then the image data format associated with the first interaction element is different from the image data format associated with the second interaction element.

[0082] Data flow is a sequence of bytes that is ordered and has a starting point and an ending point. It includes input stream and output stream.

[0083] Data format refers to the form in which data appears in file or message transmission.

[0084] It should be noted that the data stream information can also include data format information.

[0085] Step 305: Based on the test data for testing the same interaction function among the first test case and the second test case, determine the consistency between the first migration platform and the second migration platform.

[0086] It should be noted that the explanatory description of step 305 can be referred to the relevant descriptions in any embodiment of the present disclosure, and will not be elaborated here.

[0087] In summary, select the first interaction element from the interaction elements included in the first test case, and select the second interaction element from the interaction elements included in the second test case, where the first interaction element and the second interaction element are used to implement the same interaction function; according to at least one of the first interaction element, the page structure information associated with the first interaction element, and the data stream information, and according to at least one of the second interaction element, the page structure information associated with the second interaction element, and the data stream information, determine the test data for testing the same interaction function. Thus, according to the interaction functions implemented by the interaction elements included in the first test case and the interaction functions implemented by the interaction elements included in the second test case, select the interaction elements included in the first test case and the interaction elements included in the second test case to determine the test data for testing the same interaction function, which not only significantly takes into account the consistency in the specific implementation effects of the same interaction function between the two migration platforms, but also takes into account the consistency in the page structure aspect and the data stream aspect of the same interaction function between the two migration platforms, so as to facilitate a more detailed analysis of the consistency between the first migration platform and the second migration platform subsequently.

[0088] To illustrate how to determine the consistency between the first migration platform and the second migration platform based on the test data for testing the same interaction function among the first test case and the second test case in the embodiments of the present disclosure, the present disclosure also proposes a method for determining the consistency of cross-platform migration.

[0089] Figure 4 It is a schematic flowchart of the method for determining the consistency of cross-platform migration provided in Embodiment 4 of the present disclosure.

[0090] As Figure 4 shown, the method for determining the consistency of cross-platform migration may include the following steps:

[0091] Step 401: In response to a migration evaluation request from a client, obtain the first page information of the first migration platform and the second page information of the second migration platform.

[0092] Step 402: Generate a corresponding first test case based on the first page information, and generate a corresponding second test case based on the second page information.

[0093] It should be noted that the explanations of Step 401 and Step 402 can be found in the relevant descriptions in any embodiment of the present disclosure, and will not be elaborated here.

[0094] Step 403: Compare at least one of the interaction function, associated page structure information, and associated data flow based on the first interaction element tested by the test data in the first test case and the second interaction element tested by the test data in the second test case, to obtain difference data.

[0095] Among them, it should be noted that the difference data includes at least one set of data among the first difference data in terms of interaction function, the second difference data in terms of page structure, and the third difference data in terms of data flow.

[0096] In some embodiments, based on the first interaction element tested by the test data in the first test case and the second interaction element tested by the test data in the second test case, a large difference comparison model is used to determine the first difference data in terms of interaction function between the first test case and the second test case.

[0097] In the embodiments of the present disclosure, using the large difference comparison model to compare the first interaction element and the second interaction element may include performing comparative analysis on the specific data included in the first interaction element and the specific data included in the second interaction element, giving the data difference result, and combining the data difference result to generate the first difference data, etc.

[0098] In some embodiments, based on the page structure information associated with the first interaction element tested by the test data in the first test case and the page structure information associated with the second interaction element tested by the test data in the second test case, a large difference comparison model is used to determine the second difference data in terms of page structure between the first test case and the second test case.

[0099] In the embodiments of the present disclosure, using the large difference comparison model to compare the page structure information associated with the first interaction element and the page structure information associated with the second interaction element may include performing comparative analysis on the arrangement manner of the first interaction element in the page to be processed and the arrangement manner of the second interaction element in the page to be processed, performing comparative analysis on the organization manner of the first interaction element in the page to be processed and the organization manner of the second interaction element in the page to be processed, etc., giving the page structure difference analysis result, and combining the difference analysis result to generate the second difference data, etc.

[0100] In some embodiments, according to the data flow information associated with the first interaction element tested based on the test data in the first test case, and the data flow information associated with the second interaction element tested based on the test data in the second test case, a large difference comparison model is used to determine the third difference data in terms of data flow between the first test case and the second test case.

[0101] In the embodiments of the present disclosure, using a large difference comparison model to perform difference comparison on the data flow information associated with the first interaction element and the data flow information associated with the second interaction element may include comparing and analyzing the data formats involved in the first interaction element and the data formats involved in the second interaction element on the page, comparing and analyzing the data flows associated with the first interaction element and the data flows associated with the second interaction element, etc., giving the results of data flow difference analysis and generating the third difference data in combination with the difference analysis results.

[0102] Step 404, based on the difference data, determine the consistency between the first migration platform and the second migration platform.

[0103] It should be understood that the more first difference data, second difference data, and third difference data are obtained, or the greater the data deviation among the first difference data, second difference data, and third difference data, it indicates that the difference between the first migration platform and the second migration platform is greater, and correspondingly, it can be determined that the consistency between the first migration platform and the second migration platform is lower.

[0104] In summary, according to the first interaction element tested based on the test data in the first test case and the second interaction element tested based on the test data in the second test case, at least one of the interaction function, associated page structure information, and associated data flow is compared to obtain difference data; based on the difference data, the consistency between the first migration platform and the second migration platform is determined. Thus, not only can the difference data between the first migration platform and the second migration platform be analyzed through the first interaction element and the second interaction element, and then the consistency between the first migration platform and the second migration platform can be determined, but also for the first interaction element and the second interaction element under the same interaction function, more detailed analysis can be carried out from the aspects of page structure and data flow, improving the granularity of analyzing the consistency between the first migration platform and the second migration platform.

[0105] Under normal circumstances, after determining the consistency between the first migration platform and the second migration platform, the obtained consistency data is not easy to understand and does not intuitively reflect the specific data differences and consistencies between the first migration platform and the second migration platform. Furthermore, it affects the relevant personnel's subsequent judgment on whether to migrate the first migration platform and the second migration platform. Therefore, after determining the consistency between the first migration platform and the second migration platform, the obtained consistency data can be further processed.

[0106] The present disclosure also proposes a method for determining the consistency of cross-platform migration.

[0107] Figure 5 It is a schematic flowchart of the method for determining the consistency of cross-platform migration provided in the fifth embodiment of the present disclosure.

[0108] As Figure 5 shown, the method for determining the consistency of cross-platform migration may include the following steps:

[0109] Step 501, in response to a migration evaluation request from a client, obtain the first page information of the first migration platform and the second page information of the second migration platform.

[0110] Step 502, generate a corresponding first test case according to the first page information, and generate a corresponding second test case according to the second page information.

[0111] Step 503, determine the consistency between the first migration platform and the second migration platform based on the test data for testing the same interaction function among the first test case and the second test case.

[0112] It should be noted that the explanations of steps 501 - 503 can refer to the relevant descriptions in any embodiment of the present disclosure and will not be elaborated here.

[0113] Step 504, determine the consistency score between the first migration platform and the second migration platform based on the test data for testing the same interaction function among the first test case and the second test case.

[0114] Among them, it should be noted that the specific method for scoring the consistency between the first migration platform and the second migration platform can be determined according to existing professional technologies and will not be elaborated in this embodiment.

[0115] Step 505, determine the migration risk level between the first migration platform and the second migration platform according to the consistency score and a set risk threshold.

[0116] Among them, it should be noted that the specific value of the risk threshold is determined according to the actual situation, and no specific limitation is made in this embodiment.

[0117] In this embodiment, when the consistency score does not exceed the risk threshold, a low migration risk level between the first migration platform and the second migration platform is determined.

[0118] In this embodiment, when the consistency score exceeds the risk threshold, a high migration risk level between the first migration platform and the second migration platform is determined.

[0119] It should be understood that through the determined migration risk level, it is convenient to directly give the migration risk result to relevant personnel, so that a judgment can be quickly made to promote the process progress of the migration platform. However, simply giving the migration risk level is not enough to meet the needs of relevant personnel for further analysis of the consistency between the first migration platform and the second migration platform.

[0120] In some embodiments, according to the difference data between the test data for testing the same interaction function among the first test case and the second test case, the corresponding relationship between the optimization strategy and the type of the difference data is queried, and the optimization strategy for the first migration platform and / or the second migration platform is determined.

[0121] Among them, it should be noted that the type of the difference data is used to indicate at least one of the aspects in the interaction function, page structure, and data flow involved in the difference data.

[0122] In the embodiments of the present disclosure, after determining the consistency between the first migration platform and the second migration platform, for the convenience of users to further understand, reliable optimization strategies are provided for subsequent adjustment of the first migration platform and the second migration platform under different migration risk levels.

[0123] For example, the correspondence between the optimization strategy and the type of differential data can be as shown in Table 2. In Table 2, there is type A, which is used to indicate that the differential data is the differential data in terms of interactive functions; type B, which is used to indicate that the differential data is the differential data in terms of page structure; type C, which is used to indicate that the differential data is the differential data in terms of data flow. There is a correspondence between type A and optimization strategy a, a correspondence between type B and optimization strategy b, and a correspondence between type C and optimization strategy c. Suppose the differential data between the test data for testing the same interactive function in the first test case and the second test case involves the aspects of interactive functions and data flow. Then the types of the differential data are type A (interactive function aspect) and type C (data flow aspect) respectively. Query in Table 2 that there is a correspondence between optimization strategy a and type A to which the differential data belongs, and a correspondence between optimization strategy c and type C to which the differential data belongs. Then, take optimization strategy a and optimization strategy c as the optimization strategies for the first migration platform and / or the second migration platform.

[0124] Table 2 Correspondence Table of Optimization Strategy and Type of Differential Data

[0125] Type of differential data Optimization strategy Type A Optimization strategy a Type B Optimization strategy b Type C Optimization strategy c

[0126] In order to conveniently obtain various data obtained in the process of determining the consistency between the first migration platform and the second migration platform, as a possible implementation manner, the differential data and the corresponding optimization strategy are stored in an associated manner, and the consistency score and the corresponding migration risk level are stored in the migration assessment report in an associated manner.

[0127] In some embodiments, if the migration risk level between the first migration platform and the second migration platform is a high migration risk level, call the auxiliary large model to determine the handling opinions on the first migration platform and / or the second migration platform based on the differential data between the test data for testing the same interactive function in the first test case and the second test case, and push the warning information and the handling opinions to the client; upon receiving the signal that the first migration platform and / or the second migration platform has been processed by the client, regenerate the first test case and the second test case; re-analyze the test data for testing the same interactive function in the regenerated first test case and the second test case until the re-determined consistency score does not exceed the risk threshold.

[0128] In summary, based on the test data for testing the same interaction function in the first test case and the second test case, determine the consistency score between the first migration platform and the second migration platform; according to the consistency score and the set risk threshold, determine the migration risk level between the first migration platform and the second migration platform. Thus, score the consistency between the first migration platform and the second migration platform to obtain the consistency score, and provide intuitive and clear data for relevant personnel through the migration risk level determined by the consistency score. Moreover, under different migration risk levels, it provides reliable data support for subsequent adjustment of the first migration platform and the second migration platform.

[0129] The present disclosure also proposes a method for determining the consistency of cross-platform migration.

[0130] Figure 6 It is a schematic flowchart of the method for determining the consistency of cross-platform migration provided in Embodiment VI of the present disclosure.

[0131] As Figure 6 shown, the method for determining the consistency of cross-platform migration may include the following steps:

[0132] Step 601, in response to a migration evaluation request from a client, obtain the first page information of the first migration platform and the second page information of the second migration platform.

[0133] Step 602, generate a corresponding first test case according to the first page information, and generate a corresponding second test case according to the second page information.

[0134] Step 603, based on the test data for testing the same interaction function in the first test case and the second test case, determine the consistency between the first migration platform and the second migration platform.

[0135] It should be noted that the explanations of steps 601-step 603 can refer to the relevant descriptions in any embodiment of the present disclosure, and will not be elaborated here.

[0136] Step 604, call an optimization large model to optimize at least one of the first test case and the second test case.

[0137] It should be understood that in the actual scenario, as the application scenarios of the first migration platform and / or the second migration platform continue to expand, the user requirements become increasingly complex. Reflected on the platform, there will be new interaction functions added, or the existing interaction functions continue to be upgraded. If the first test case and the second test case are not optimized, it may not be able to accurately reflect the changes in the interaction functions on the first migration platform and / or the second migration platform. Thus, it is very easy to cause the distortion of the data of the determined consistency between the first migration platform and the second migration platform.

[0138] In some embodiments, the interaction elements included in the first test case and the interaction elements included in the second test case are input into an optimization large model to determine at least one target interaction element for which the interaction functions used for implementation change before and after migration; according to the target interaction element, the interaction elements in the corresponding test case are updated to determine the optimized test case.

[0139] In summary, the optimization large model is called to optimize at least one of the first test case and the second test case. Thus, by calling the optimization large model to optimize the first test case and the second test case, the possible changes in the interaction functions on the migration platform are taken into account. Furthermore, the first test case and the second test case are automatically optimized so that the optimized test cases can immediately reflect the changes in the interaction functions on the corresponding migration platform.

[0140] Figure 7 It is a schematic structural diagram of a consistency determination device for cross-platform migration according to an embodiment of the present disclosure.

[0141] As Figure 7 shown, the consistency determination device for cross-platform migration includes:

[0142] A first acquisition module 701, in response to a migration evaluation request from a client, acquires first page information of a first migration platform and second page information of a second migration platform;

[0143] A generation module 702, configured to generate a corresponding first test case according to the first page information and a corresponding second test case according to the second page information;

[0144] A first determination module 703, configured to determine the consistency between the first migration platform and the second migration platform based on test data for testing the same interaction function among the first test case and the second test case.

[0145] In a possible implementation manner of the embodiment of the present disclosure, the generation module 702 is specifically configured to:

[0146] For the to-be-processed page information in the first page information and the second page information, parse to obtain at least one interaction element;

[0147] According to the interaction function implemented by the interaction element on the corresponding first migration platform or second migration platform, determine a target test case template through a preset mapping relationship table between interaction functions and test case templates;

[0148] Generate a first test case or a second test case corresponding to the to-be-processed page information according to the interaction element and through the target test case template.

[0149] In a possible implementation of the embodiment of the present disclosure, the generation module 702 is specifically configured to:

[0150] Obtain the page structure information and data stream information associated with the interaction element;

[0151] Correspondingly fill the interaction element, the page structure information, and the data stream information into the target test case template to generate a first test case or a second test case corresponding to the page information to be processed.

[0152] In a possible implementation of the embodiment of the present disclosure, the device further includes a second determination module, which is specifically configured to:

[0153] Select a first interaction element from the interaction elements included in the first test case, and select a second interaction element from the interaction elements included in the second test case, where the first interaction element and the second interaction element are used to implement the same interaction function;

[0154] Determine test data for testing the same interaction function according to at least one of the first interaction element, the page structure information associated with the first interaction element, and the data stream information, and according to at least one of the second interaction element, the page structure information associated with the second interaction element, and the data stream information.

[0155] In a possible implementation of the embodiment of the present disclosure, the first determination module 703 is specifically configured to:

[0156] Compare at least one of the interaction function, the associated page structure information, and the associated data stream according to the first interaction element tested by the test data in the first test case and the second interaction element tested by the test data in the second test case to obtain difference data;

[0157] Based on the difference data, determine the consistency between the first migration platform and the second migration platform.

[0158] In a possible implementation of the embodiment of the present disclosure, the first determination module 703 is specifically configured to:

[0159] According to the first interaction element tested by the test data in the first test case and the second interaction element tested by the test data in the second test case, determine the first difference data in terms of the interaction function between the first test case and the second test case through a large difference comparison model.

[0160] In a possible implementation of the embodiment of the present disclosure, the first determination module 703 is specifically configured to:

[0161] Based on the page structure information associated with the first interaction element tested according to the test data in the first test case, and the page structure information associated with the second interaction element tested according to the test data in the second test case, through a large model for differential comparison, to determine the second differential data between the first test case and the second test case in terms of page structure.

[0162] In a possible implementation manner of the embodiment of the present disclosure, the first determination module 703 is specifically configured to:

[0163] Based on the data flow information associated with the first interaction element tested according to the test data in the first test case, and the data flow information associated with the second interaction element tested according to the test data in the second test case, through a large model for differential comparison, to determine the third differential data between the first test case and the second test case in terms of data flow.

[0164] In a possible implementation manner of the embodiment of the present disclosure, the device further includes a scoring module, which is specifically configured to:

[0165] Based on the test data for testing the same interaction function among the first test case and the second test case, determine the consistency score between the first migration platform and the second migration platform;

[0166] According to the consistency score and the set risk threshold, determine the migration risk level between the first migration platform and the second migration platform.

[0167] In a possible implementation manner of the embodiment of the present disclosure, the scoring module is specifically configured to:

[0168] In the case where the consistency score does not exceed the risk threshold, determine the low migration risk level between the first migration platform and the second migration platform;

[0169] In the case where the consistency score exceeds the risk threshold, determine the high migration risk level between the first migration platform and the second migration platform.

[0170] In a possible implementation manner of the embodiment of the present disclosure, the device further includes an optimization strategy module, which is specifically configured to:

[0171] According to the differential data between the test data for testing the same interaction function among the first test case and the second test case, query the corresponding relationship between the optimization strategy and the type of differential data, and determine the optimization strategy for the first migration platform and / or the second migration platform.

[0172] In a possible implementation manner of the embodiment of the present disclosure, the device further includes an optimization module, which is specifically configured to:

[0173] Invoke the optimization large model to optimize at least one of the first test case and the second test case.

[0174] In a possible implementation manner of the embodiments of the present disclosure, the optimization module is specifically configured to:

[0175] Input the interaction elements included in the first test case and the interaction elements included in the second test case into the optimization large model, and determine at least one target interaction element whose interaction function for implementation changes before and after migration;

[0176] Update the interaction elements in the corresponding test case according to the target interaction elements to determine the optimized test case.

[0177] It should be noted that the foregoing explanation of the method for determining the consistency of cross-platform migration also applies to the device for determining the consistency of cross-platform migration in this embodiment, and will not be repeated here.

[0178] In summary, the device for determining the consistency of cross-platform migration proposed in the present disclosure, in response to a migration evaluation request from a client, obtains the first page information of the first migration platform and the second page information of the second migration platform, generates a corresponding first test case according to the first page information, and generates a corresponding second test case according to the second page information. Based on the test data for testing the same interaction function among the first test case and the second test case, determine the consistency between the first migration platform and the second migration platform. Thus, by analyzing the page information in the migration platform, test cases for the two migration platforms are respectively generated. By comparing the generated test cases, the consistency between the two migration platforms is determined, effectively realizing the overview and tracking of the page information used to implement the interaction function on the platform. Moreover, it can automatically generate test cases, and the test cases contain the data for implementing the interaction function that is focused on. Through the test cases, there is no need to tediously analyze and compare the information used to implement the interaction function on the two migration platforms one by one, increasing the analysis cost and affecting the analysis efficiency. Moreover, the impact of the interaction function on the consistency between the two migration platforms is taken into account, which helps to improve the user experience of the new migration platform.

[0179] To implement the above embodiments, the present disclosure also provides an electronic device, which may include at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for determining the consistency of cross-platform migration proposed in any of the above embodiments of the present disclosure.

[0180] To implement the above embodiments, the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the cross-platform migration consistency determination method proposed in any of the above embodiments of the present disclosure.

[0181] To implement the above embodiments, the present disclosure also provides a computer program product, which includes a computer program that, when executed by a processor, implements the cross-platform migration consistency determination method proposed in any of the above embodiments of the present disclosure.

[0182] Figure 8 is a block diagram of an electronic device for implementing the cross-platform migration consistency determination method of the embodiments of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as, for example, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, for example, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0183] As Figure 8 shown, the device 800 includes a computing unit 801 that can execute various appropriate actions and processes according to the computer program stored in a ROM (Read-Only Memory) 802 or the computer program loaded from a storage unit 807 into a RAM (Random Access Memory) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An I / O (Input / Output) interface 805 is also connected to the bus 804.

[0184] A plurality of components in the device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a magnetic disk, an optical disc, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0185] The computing unit 801 can be various general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any suitable processor, controller, microcontroller, etc. The computing unit 801 executes the various methods and processes described above, such as method XXX. For example, in some embodiments, method XXX may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed onto the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the method XXX described above may be executed. Alternatively, in other embodiments, the computing unit 801 may be configured to execute method XXX in any other suitable manner (e.g., by means of firmware).

[0186] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chip), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0187] The program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The program codes may be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0188] In the context of the present disclosure, a machine-readable medium may be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory), or a flash memory, an optical fiber, a CD-ROM (Compact Disc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0189] In order to provide interaction with a user, the systems and techniques described herein may be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or an LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the computer. Other kinds of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and the input received from the user may be in any form (including acoustic input, voice input, or tactile input).

[0190] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0191] A computer system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services ("Virtual Private Server", or simply "VPS"). The server can also be a server of a distributed system, or a server combined with blockchain.

[0192] It should be noted that artificial intelligence is a discipline that studies enabling a computer to simulate certain thinking processes and intelligent behaviors of humans (such as learning, reasoning, thinking, planning, etc.), and it has both hardware-level technologies and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include several major directions such as computer vision technology, speech recognition technology, natural language processing technology, and machine learning / deep learning, big data processing technology, and knowledge graph technology.

[0193] It should be understood that various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and no limitation is imposed herein.

[0194] The above specific embodiments do not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present disclosure shall be included within the protection scope of the present disclosure.

Claims

1. A method for determining consistency in cross - platform migration, the method comprising: In response to a migration evaluation request from a client, obtaining first page information of a first migration platform and second page information of a second migration platform; Generating a corresponding first test case according to the first page information, and generating a corresponding second test case according to the second page information; Based on the test data for testing the same interaction function among the first test case and the second test case, determining the consistency between the first migration platform and the second migration platform.

2. The method according to claim 1, wherein, The generating a corresponding first test case according to the first page information, and generating a corresponding second test case according to the second page information, includes: For the page information to be processed in the first page information and the second page information, parsing to obtain at least one interaction element; According to the interaction function implemented by the interaction element on the corresponding first migration platform or second migration platform, determining a target test case template through a preset mapping relationship table between interaction functions and test case templates; According to the interaction element, generating the corresponding first test case or second test case for the page information to be processed through the target test case template.

3. The method according to claim 2, wherein The generating the corresponding first test case or second test case for the page information to be processed according to the interaction element through the target test case template includes: Obtaining page structure information and data flow information associated with the interaction element; Filling the interaction element, the page structure information, and the data flow information into the target test case template correspondingly to generate the corresponding first test case or second test case for the page information to be processed.

4. The method according to any one of claims 1-3, wherein The method further includes: Selecting a first interaction element from the interaction elements included in the first test case, and selecting a second interaction element from the interaction elements included in the second test case, where the first interaction element and the second interaction element are used to implement the same interaction function; Determining the test data for testing the same interaction function according to at least one of the first interaction element, the page structure information associated with the first interaction element, and the data flow information, and according to at least one of the second interaction element, the page structure information associated with the second interaction element, and the data flow information.

5. The method according to claim 4, wherein The determining the consistency between the first migration platform and the second migration platform based on the test data for testing the same interaction function among the first test case and the second test case includes: Comparing at least one of the interaction function, the associated page structure information, and the associated data flow according to the first interaction element tested by the test data in the first test case and the second interaction element tested by the test data in the second test case to obtain difference data; Based on the difference data, determining the consistency between the first migration platform and the second migration platform.

6. The method according to claim 5, wherein The differential data includes first differential data in terms of interactive functions; the first interactive element tested according to the test data in the first test case and the second interactive element tested according to the test data in the second test case are compared against at least one of the interactive function, associated page structure information, and associated data stream to obtain differential data, including: The first interactive element tested according to the test data in the first test case and the second interactive element tested according to the test data in the second test case are used to determine the first differential data in terms of interactive functions between the first test case and the second test case through a differential comparison large model.

7. The method according to claim 5, wherein, The differential data includes second differential data in terms of page structure; the first interactive element tested according to the test data in the first test case and the second interactive element tested according to the test data in the second test case are compared against at least one of the interactive function, associated page structure information, and associated data stream to obtain differential data, including: The page structure information associated with the first interactive element tested according to the test data in the first test case and the page structure information associated with the second interactive element tested according to the test data in the second test case are used to determine the second differential data in terms of page structure between the first test case and the second test case through a differential comparison large model.

8. The method according to claim 5, wherein The differential data includes third differential data in terms of data stream; the first interactive element tested according to the test data in the first test case and the second interactive element tested according to the test data in the second test case are compared against at least one of the interactive function, associated page structure information, and associated data stream to obtain differential data, including: The data stream information associated with the first interactive element tested according to the test data in the first test case and the data stream information associated with the second interactive element tested according to the test data in the second test case are used to determine the third differential data in terms of data stream between the first test case and the second test case through a differential comparison large model.

9. The method according to claim 1, wherein Determining the consistency between the first migration platform and the second migration platform based on the test data for testing the same interactive function in the first test case and the second test case includes: Determining a consistency score between the first migration platform and the second migration platform based on the test data for testing the same interactive function in the first test case and the second test case. Determining the migration risk level between the first migration platform and the second migration platform according to the consistency score and a set risk threshold.

10. The method according to claim 9, wherein, The method further includes: Determining a low migration risk level between the first migration platform and the second migration platform when the consistency score does not exceed the risk threshold. In the case that the consistency score exceeds the risk threshold, determine the migration high-risk level between the first migration platform and the second migration platform.

11. The method according to claim 1, wherein, The method further includes: Query the corresponding relationship between the optimization strategy and the type of the difference data according to the difference data between the test data for testing the same interaction function among the first test case and the second test case, and determine the optimization strategy for the first migration platform and / or the second migration platform.

12. The method according to claim 1, wherein The method further includes: Invoke an optimization large model to optimize at least one of the first test case and the second test case.

13. The method according to claim 12, wherein The invoking the optimization large model to optimize at least one of the first test case and the second test case includes: Input the interaction elements included in the first test case and the interaction elements included in the second test case into the optimization large model, and determine at least one target interaction element whose interaction function for implementation changes before and after migration; Update the interaction elements in the corresponding test case according to the target interaction element to determine the optimized test case.

14. A consistency determination device for cross-platform migration, wherein, The apparatus includes: A first acquisition module, in response to a migration evaluation request from a client, acquires the first page information of the first migration platform and the second page information of the second migration platform; A generation module, configured to generate a corresponding first test case according to the first page information and generate a corresponding second test case according to the second page information; A first determination module, configured to determine the consistency between the first migration platform and the second migration platform based on the test data for testing the same interaction function among the first test case and the second test case.

15. An electronic device, characterized in that, It includes a processor and a memory; Wherein, the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the method according to any one of claims 1-13.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method according to any one of claims 1-13.

17. A computer program product, including a computer program, where the computer program, when executed by a processor, implements the method according to any one of claims 1-13.

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