Intelligent network data comparison method and system

Abstract

The invention provides an intelligent network data comparison method and system, and belongs to the technical field of data processing, and the method specifically comprises the following steps: writing a script to remotely control a mobile phone, automatically opening a page of a target application, simulating a user to click and browse page data in a rolling manner, and obtaining a page screenshot with to-be-verified information; the script automatically opens pages of other terminals of the target application, obtains page screenshots with to-be-verified information in the other terminals, transmits the page screenshots with the to-be-verified information of different terminals of the target application to the big data interface, and performs structured processing on the page screenshots to obtain structured data; the structured data of different terminals are compared to obtain the comparison result, and whether the structured data are consistent or not is determined by using the comparison result, so that the test processing efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to an intelligent network data comparison method and system. Background Art

[0002] Users can usually access the same data through multiple terminals, and development teams usually use a unified data source (such as API or database) in multiple application environments (mobile and computer). For example, in a typical development process, multiple teams may develop multiple terminals of an application at the same time, and these functions need to display the same data. In the past, it was only possible to manually compare data from multiple terminals to confirm that the data displayed on different pages was consistent, which made it difficult to meet the development efficiency requirements.

[0003] In response to the above technical problems, the present application specifically provides a method and system for intelligently comparing network data. Summary of the invention

[0004] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: An intelligent network data comparison method, specifically comprising: S1 writes a script to remotely control the mobile phone, automatically opens the target application page, simulates user clicks and scrolls through page data, and obtains screenshots of the page with information to be verified; The S2 script automatically opens the pages of other terminals of the target application and obtains screenshots of the pages with the information to be verified in other terminals; The S3 script transmits page screenshots with information to be verified from different terminals of the target application to the big data interface, and performs structured processing on the page screenshots to obtain structured data; S4 compares the structured data of different terminals to obtain a comparison result, and uses the comparison result to determine whether they are consistent.

[0005] A further technical solution is that the script is constructed using the AIrTest automation tool.

[0006] A further technical solution is that after obtaining the page screenshot with the information to be verified, the page screenshot is placed in a corresponding folder, and when performing a comparison process on the structured data, the structured data in different folders are compared and processed respectively.

[0007] The beneficial effects of the present invention are: By utilizing the technical solution of the present invention, it is possible to automatically extract and obtain page screenshots with information to be verified, and to obtain structured data of different page screenshots, thereby achieving unmanned supervision, and then achieving data comparison of pages of different terminals, significantly improving the test verification efficiency, while also ensuring the accuracy and reliability of the verification process.

[0008] On the other hand, the present application provides an intelligent network data comparison system, which applies the above-mentioned intelligent network data comparison method, specifically including: Preprocessing module, pre-verification module, page adjustment module, verification processing module; The pre-processing module is responsible for obtaining the information to be verified corresponding to different page screenshots, and determining whether pre-verification processing is required based on the number of terminals that perform verification processing on different page screenshots; The pre-verification module is responsible for analyzing the image similarity of the compared page screenshots of different terminals to obtain analysis results, and using the analysis results of different page screenshots to determine the verification strategy adjustment method of the page screenshots; The page adjustment module is responsible for performing screenshot adjustment processing of the page screenshot using the verification strategy adjustment method, and when it does not belong to the preset verification strategy adjustment method, the page screenshot that needs to be intercepted and adjusted is determined based on the information to be verified corresponding to different page screenshots and the analysis results of image similarity, and is used as the secondary intercepted page screenshot; The verification processing module is responsible for extracting structured data from the secondary page screenshots and page screenshots of different terminals, and comparing the structured data to obtain comparison results.

[0009] A further technical solution is that the number of terminals for verifying the page screenshot is determined based on a one-to-one correspondence between the page screenshot and the terminal.

[0010] A further technical solution is to determine whether a pre-verification process is required, specifically including: Based on the information to be verified corresponding to the page screenshot, determining the quantity of information to be verified of different page screenshots and the data volume of different information to be verified; Based on the amount of information to be verified in different page screenshots and the amount of data of the information to be verified in different page screenshots, the total amount of data of the information to be verified in different page screenshots is determined, and the total amount of verification data is determined in combination with the number of terminals for verification processing of different page screenshots; Whether a pre-verification process is required is determined based on the total amount of verification data.

[0011] A further technical solution is that the method for determining the total amount of verification data is: The total amount of data of the information to be verified in different page screenshots and the number of terminals for verification processing of the page screenshots are used to determine the sum of the total amount of data of different terminals in different page screenshots, and the sum is used as the total amount of data; The total amount of verification data is determined based on the total amount of data in different page screenshots.

[0012] A further technical solution is that, when no pre-verification process is required, the verification process module is directly used to extract the structured data of the page screenshot, and the structured data is compared to obtain a comparison result.

[0013] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0014] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings; Figure 1 is a flow chart of a method for intelligently comparing network data; Figure 2 It is a framework diagram of an intelligent comparison network data system; Figure 3 is a flow chart for determining whether a pre-authentication process is required; Figure 4 It is a flow chart of a method for determining a verification strategy adjustment method for a page screenshot; Figure 5 It is a flow chart of a method for determining a secondary capture of a page screenshot. DETAILED DESCRIPTION

[0016] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0017] In modern software development, crawler technology for user interfaces (UI) is widely used in many fields such as data collection, information monitoring, and competitive analysis. In today's society, users can usually access the same data through multiple terminals, and development teams usually use a unified data source (such as API or database) in multiple application environments (mobile terminal, computer terminal). For example, in a typical development process, multiple teams may develop multiple terminals of an application at the same time, and these functions need to display the same data. In the past, it was only possible to manually compare multi-terminal data to confirm that the data finally displayed on different pages was consistent. The present invention realizes program automation comparison.

[0018] The purpose of the present invention is to use a computer program to intelligently compare the consistency of data finally displayed by multiple terminals.

[0019] To achieve the above purpose, the present invention adopts the following technical solutions: Use the AirTest tool to write scripts to remotely control the phone, automatically open the pages of related applications (such as opening the page of the mini-program specified by WeChat), and simulate users clicking and scrolling to browse page data.

[0020] During the browsing process, take screenshots of the pages with information to be verified and store them in folders according to the relevant page modules.

[0021] The script automatically opens the computer browser to access the relevant page after completing the mobile page browsing.

[0022] During the browsing process, take screenshots of the pages with information to be verified and store them in folders according to the relevant page modules.

[0023] After completing the screenshot on the computer, the script starts to traverse the folders where the pictures are stored and pass the pictures to the large model interface one by one, instructing the large model to structure the relevant information on the pictures to ensure that the returned data structure is exactly the same.

[0024] Finally, the script matches the information obtained from different ends one by one to see if they are consistent.

[0025] Embodiment 1 To solve the above-mentioned problem, according to one aspect of the present invention, Figure 1 As shown, the present invention proposes an intelligent network data comparison method, which specifically includes: S1 writes a script to remotely control the mobile phone, automatically opens the target application page, simulates user clicks and scrolls through page data, and obtains screenshots of the page with information to be verified; The S2 script automatically opens the pages of other terminals of the target application and obtains screenshots of the pages with the information to be verified in other terminals; The S3 script transmits page screenshots with information to be verified from different terminals of the target application to the big data interface, and performs structured processing on the page screenshots to obtain structured data; S4 compares the structured data of different terminals to obtain a comparison result, and uses the comparison result to determine whether they are consistent.

[0026] Furthermore, the script is constructed using the AIrTest automation tool.

[0027] Specifically, after obtaining the screenshot of the page with the information to be verified, the screenshot of the page is placed in a corresponding folder, and when performing the comparison processing of the structured data, the structured data in different folders are compared and processed respectively.

[0028] Embodiment 2 On the other hand, as Figure 2 As shown, the present application provides an intelligent network data comparison system, which is applied to the above-mentioned intelligent network data comparison method, specifically including: Preprocessing module, pre-verification module, page adjustment module, verification processing module; The pre-processing module is responsible for obtaining the information to be verified corresponding to different page screenshots, and determining whether pre-verification processing is required based on the number of terminals that perform verification processing on different page screenshots; Specifically, when the sum of the number of information to be verified in different page screenshots is greater than a preset information number threshold, it is determined that a pre-verification process is required.

[0029] When no pre-verification process is required, the verification process module is directly used to extract the structured data of the page screenshot, and the structured data is compared to obtain a comparison result.

[0030] The pre-verification module is responsible for analyzing the image similarity of the compared page screenshots of different terminals to obtain analysis results, and using the analysis results of different page screenshots to determine the verification strategy adjustment method of the page screenshots; In a possible embodiment, according to the image similarity of the page screenshots in different matching verification terminals, the matching verification terminals whose image similarity does not meet the requirements are determined, and the matching verification terminals whose image similarity does not meet the requirements are determined as image deviation page screenshots. When the number of image deviation page screenshots is greater than the preset number of page screenshots, the preset verification policy adjustment method is used to determine the verification policy adjustment method of the page screenshots. When the number of image deviation page screenshots is not greater than the preset number of page screenshots, there is no need to use the preset verification policy adjustment method to determine the verification policy adjustment method of the page screenshots.

[0031] The page adjustment module is responsible for performing screenshot adjustment processing of the page screenshot using the verification strategy adjustment method, and when it does not belong to the preset verification strategy adjustment method, the page screenshot that needs to be intercepted and adjusted is determined based on the information to be verified corresponding to different page screenshots and the analysis results of image similarity, and is used as the secondary intercepted page screenshot; When the preset verification strategy adjustment method is adopted, a corresponding single secondary intercepted page screenshot is generated based on different information to be verified, and the structured data of the secondary intercepted page screenshot is used for comparison to obtain the comparison result. When it does not belong to the preset verification strategy adjustment method, it is determined that a secondary intercepted page screenshot is required to generate a page screenshot, and the secondary intercepted page screenshot and the structured data of the page screenshot are used for comparison to obtain the comparison result.

[0032] The verification processing module is responsible for extracting structured data from the secondary page screenshots and page screenshots of different terminals, and comparing the structured data to obtain comparison results.

[0033] Furthermore, the number of terminals for verifying the page screenshot is determined based on a one-to-one correspondence between the page screenshot and the terminal.

[0034] Specifically, Figure 3 As shown, determine whether pre-verification processing is required, including: Based on the information to be verified corresponding to the page screenshot, determining the quantity of information to be verified of different page screenshots and the data volume of different information to be verified; Based on the amount of information to be verified in different page screenshots and the amount of data of the information to be verified in different page screenshots, the total amount of data of the information to be verified in different page screenshots is determined, and the total amount of verification data is determined in combination with the number of terminals for verification processing of different page screenshots; Whether a pre-verification process is required is determined based on the total amount of verification data.

[0035] Furthermore, the method for determining the total amount of verification data is: The total amount of data of the information to be verified in different page screenshots and the number of terminals for verification processing of the page screenshots are used to determine the sum of the total amount of data of different terminals in different page screenshots, and the sum is used as the total amount of data; The total amount of verification data is determined based on the total amount of data in different page screenshots.

[0036] It should be noted that when the total amount of verification data is greater than the preset data amount, it is determined that a pre-verification process is required.

[0037] Optionally, when no pre-verification processing is required, the verification processing module is directly used to extract the structured data of the page screenshot, and the structured data is compared to obtain a comparison result.

[0038] Optionally, determine whether pre-verification processing is required, including: Based on the information to be verified corresponding to the page screenshot, determining the quantity of information to be verified of different page screenshots and the data volume of different information to be verified; Based on the number of information to be verified in different page screenshots and the data volume of different information to be verified, the total data volume of the information to be verified in different page screenshots is determined, and in combination with the number of terminals for verification processing in different page screenshots, the sum of the total data volume of different terminals in different page screenshots is determined, and the sum is used as the total data volume; The determination of the complex page screenshots for verification processing in the page screenshots is based on the total amount of data and the number of complex page screenshots for verification processing, and whether pre-verification processing is required is determined by using the number of complex page screenshots for verification processing.

[0039] Further, when the number of the complex page screenshots for the verification process does not meet the requirement, it is determined that a preliminary verification process is required.

[0040] Optionally, determine whether pre-verification processing is required, including: S11 determines the amount of information to be verified of different page screenshots and the data volume of different information to be verified based on the information to be verified corresponding to the page screenshot; Optionally, the above step S11 includes the following contents: S111 determines the total amount of information to be verified corresponding to different page screenshots based on the information to be verified corresponding to the page screenshots. When the total amount of information to be verified is greater than a preset amount threshold, it is determined that a pre-verification process is required. When the total amount of information to be verified is not greater than the preset amount threshold, the process proceeds to step S112. S112: when it is determined that there is no page screenshot whose total number is greater than the preset information number threshold value based on the total number of information to be verified corresponding to different page screenshots, the process proceeds to step S113; when there is a page screenshot whose total number is greater than the preset information number threshold value, the process proceeds to step S114; S113: when the number of the page screenshots is within the preset screenshot number range, it is determined that no pre-verification process is required; when the number of the page screenshots is not within the preset screenshot number range, the process proceeds to step S12; S114: When the total number of page screenshots greater than the preset information quantity threshold is greater than the preset screenshot quantity threshold, it is determined that pre-verification processing is required; when the total number of page screenshots greater than the preset information quantity threshold is not greater than the preset screenshot quantity threshold, proceed to step S12.

[0041] S12 determines the verification processing complexity coefficient of different page screenshots based on the amount of information to be verified in different page screenshots and the amount of data of different information to be verified, and in combination with the number of terminals for verification processing of different page screenshots; Optionally, the above step S12 includes the following contents: S121 determines the verification processing complexity coefficients of different page screenshots based on the number of information to be verified of different page screenshots and the data volume of different information to be verified, and in combination with the number of terminals for verification processing of different page screenshots. When the verification processing complexity coefficients of different page screenshots all meet the requirements, the process proceeds to step S122. When there are page screenshots whose verification processing complexity coefficients do not meet the requirements, the process proceeds to step S123. S122: when the number of the page screenshots is within the preset screenshot number range, it is determined that no pre-verification process is required; when the number of the page screenshots is not within the preset screenshot number range, the process proceeds to step S124; S123: when the number of page screenshots that do not meet the verification processing complexity coefficient is greater than the preset screenshot number threshold, it is determined that a preliminary verification process is required; when the number of page screenshots that do not meet the verification processing complexity coefficient is not greater than the preset screenshot number threshold, the process proceeds to step S124; S124: When the sum of the verification processing complexity coefficients of different page screenshots does not meet the requirement, it is determined that preliminary verification processing is required. When the sum of the verification processing complexity coefficients of different page screenshots meets the requirement, the process proceeds to step S13.

[0042] S13 determines a comprehensive complexity coefficient according to the verification processing complexity coefficients of different page screenshots, and uses the comprehensive complexity coefficient to determine whether a preliminary verification process is required.

[0043] Specifically, the image similarity is determined using a preset image similarity evaluation model based on different page screenshots as input.

[0044] It should be noted that the image similarity evaluation model is constructed based on any one of the neural network models such as the CNN model and the LSTM model.

[0045] Specifically, Figure 4 As shown, the method for determining the verification strategy adjustment mode of the page screenshot is: The terminal for verifying the page screenshot is used as a matching verification terminal, and according to the image similarities of the page screenshots on different matching verification terminals, a matching verification terminal whose image similarity does not meet the requirement is determined; Screenshot of the image deviation page determined by the matching verification terminal according to the image similarity not meeting the requirements; A verification strategy adjustment method for the page screenshots is determined based on the number of the image deviation page screenshots.

[0046] Further, the matching verification terminal whose image similarity does not meet the requirement is a matching verification terminal whose image similarity with other matching verification terminals does not meet the requirement.

[0047] It can be understood that the method of adjusting the verification strategy of the page screenshots based on the number of the image deviation page screenshots specifically includes: When the number of the image deviation page screenshots is greater than the preset number of page screenshots, a preset verification strategy adjustment method is used to determine the verification strategy adjustment method of the page screenshots; When the number of the image deviation page screenshots is not greater than the preset number of page screenshots, there is no need to adopt the preset verification policy adjustment method to determine the verification policy adjustment method of the page screenshots.

[0048] It should be noted that the preset verification strategy adjustment method is to generate a corresponding single secondary intercepted page screenshot based on different information to be verified, and use the structured data of the secondary intercepted page screenshot to perform comparison to obtain the comparison result.

[0049] In another embodiment, the method for determining the adjustment mode of the verification strategy of the page screenshot is: The terminal for verifying the page screenshot is used as a matching verification terminal, and the image similarity of the page screenshot on different matching verification terminals is determined; Determine the average similarity of different page screenshots according to the average image similarities of different page screenshots on different matching verification terminals; The page screenshots whose similarity mean does not meet the requirements are taken as image deviation page screenshots, and the verification strategy adjustment method of the page screenshots is determined based on the number of the image deviation page screenshots.

[0050] In another embodiment, the method for determining the adjustment mode of the verification strategy of the page screenshot is: S21: using the terminal for verifying the page screenshot as a matching verification terminal, and determining the information deviation probability of the page screenshot according to the image similarity between different matching verification terminals and using the image similarity between different matching verification terminals; S22 determines information weight coefficients of different page screenshots based on the amount of information to be verified in different page screenshots, and determines deviation weight coefficients of different page screenshots based on the product of the information weight coefficients of different page screenshots and the probability of information deviation; S23 determines a comprehensive deviation coefficient based on the sum of the deviation weight coefficients of different page screenshots, and uses the comprehensive deviation coefficient to determine a verification strategy adjustment method for the page screenshots.

[0051] Optionally, the comprehensive deviation coefficient is used to determine the verification strategy adjustment method of the page screenshot, specifically including: When the comprehensive deviation coefficient does not meet the requirement, a preset verification strategy adjustment method is used to determine the verification strategy adjustment method of the page screenshot; When the comprehensive deviation coefficient meets the requirement, there is no need to adopt a preset verification strategy adjustment method to determine the verification strategy adjustment method of the page screenshot.

[0052] Optionally, the above step S21 includes the following contents: S211: taking the terminal for verification of the page screenshot as a matching verification terminal, and determining that there is no matching verification terminal whose image similarity does not meet the requirement according to the image similarity of the page screenshot between different matching verification terminals, then determining that there is no need to adopt a preset verification strategy adjustment method to determine the verification strategy adjustment method of the page screenshot, and when there is a matching verification terminal whose image similarity does not meet the requirement, then proceeding to step S212; S212 determines that there are page screenshots of matching verification terminals whose image similarity does not meet the requirements. When the number of page screenshots of matching verification terminals whose image similarity does not meet the requirements is greater than the preset number of page screenshots, it is determined that a preset verification strategy adjustment method needs to be adopted to determine the verification strategy adjustment method of the page screenshots. When the number of page screenshots of matching verification terminals whose image similarity does not meet the requirements is not greater than the preset number of page screenshots, the process proceeds to step S213; S213 utilizes the image similarity between different matching verification terminals to determine the information deviation probability of the page screenshot, and takes the page screenshot with an information deviation probability greater than the preset deviation probability as a deviation page screenshot; when the number of the deviation page screenshots is greater than the preset number of page screenshots, it is determined that a preset verification policy adjustment method needs to be adopted to determine the verification policy adjustment method of the page screenshot; when the number of the deviation page screenshots is not greater than the preset number of page screenshots, proceed to step S22.

[0053] Optionally, the above step S22 includes the following contents: S221 determines the information weight coefficients of different page screenshots according to the amount of information to be verified of different page screenshots. When the sum of the information weight coefficients of the deviation page screenshots is greater than the preset weight coefficient threshold, it is determined that the preset verification strategy adjustment method needs to be adopted to determine the verification strategy adjustment method of the page screenshots. When the sum of the information weight coefficients of the deviation page screenshots is not greater than the preset weight coefficient threshold, the process proceeds to step S222; S222 determines the deviation weight coefficients of different page screenshots based on the product of the information weight coefficients of different page screenshots and the information deviation probability, and when there is a page screenshot whose deviation weight coefficient is greater than the preset deviation coefficient threshold, when there is no page screenshot whose deviation weight coefficient is greater than the preset deviation coefficient threshold, then proceeds to step S23; S223: When the number of page screenshots whose deviation weight coefficient is greater than the preset deviation coefficient threshold does not meet the requirement, it is determined that a preset verification strategy adjustment method needs to be adopted to determine the verification strategy adjustment method of the page screenshots; when the number of page screenshots whose deviation weight coefficient is greater than the preset deviation coefficient threshold meets the requirement, the process proceeds to step S224; S224 determines the screening deviation weight coefficient based on the number of page screenshots whose deviation weight coefficient is greater than the preset deviation weight coefficient threshold and the corresponding deviation weight coefficient. When the screening deviation weight coefficient does not meet the requirements, it is determined that the preset verification policy adjustment method is required to determine the verification policy adjustment method of the page screenshot. When the screening deviation weight coefficient meets the requirements, it proceeds to step S23.

[0054] Specifically, the screenshot adjustment process of the page screenshot is performed by using the verification strategy adjustment method, which specifically includes: When the preset verification strategy adjustment method is adopted, a corresponding single secondary intercepted page screenshot is generated based on different information to be verified, and the structured data of the secondary intercepted page screenshot is used for comparison to obtain the comparison result; When it does not belong to the preset verification strategy adjustment method, it is determined that a secondary page screenshot needs to be generated by intercepting the page screenshot, and the secondary page screenshot is compared with the structured data of the page screenshot to obtain a comparison result.

[0055] It should be noted that if Figure 5 As shown, the method for determining the secondary interception page screenshot is: The terminal that performs verification processing on the page screenshot is used as a matching verification terminal, and the mean similarity value of the page screenshot is determined according to the average value of image similarities between different matching verification terminals; Determining the amount of information to be verified in the page screenshot based on the amount of information to be verified corresponding to the page screenshot, and determining a preset information weight coefficient corresponding to the page screenshot using the amount of information to be verified; A modified similarity coefficient of the page screenshot is determined according to the product of the preset information weight coefficient and the similarity average value, and the modified similarity coefficient is used to determine whether the page screenshot is a secondary intercepted page screenshot.

[0056] Further, when the corrected similarity coefficient of the page screenshot is less than a preset similarity coefficient threshold, it is determined that the page screenshot is a secondary captured page screenshot.

[0057] In another embodiment, the method for determining the secondary page screenshot is: The terminal for verifying the page screenshot is used as a matching verification terminal, and when there is a matching verification terminal whose image similarity is less than a set value of a similarity coefficient according to the image similarity between different matching verification terminals, it is determined that the page screenshot is a secondary capture page screenshot; When there is no matching verification terminal whose image similarity is less than the set value of the similarity coefficient: When the image similarities between different matching verification terminals all meet the requirements, it is determined that the page screenshot does not belong to a secondary intercepted page screenshot; When there is a matching verification terminal whose image similarity does not meet the requirements: When the number of matching verification terminals whose image similarity does not meet the requirement is greater than the preset number of verification terminals, it is determined that the page screenshot is a secondary captured page screenshot; When the number of matching verification terminals whose image similarity does not meet the requirement is not greater than the preset number of verification terminals: Determine the amount of information to be verified in the page screenshot based on the amount of information to be verified corresponding to the page screenshot, and when the amount of information to be verified in the page screenshot is greater than a preset verification information amount threshold, determine that the page screenshot is a secondary intercepted page screenshot; When the amount of information to be verified in the page screenshot is not greater than the preset verification information amount threshold: Determine the preset information weight coefficient corresponding to the page screenshot by using the amount of the information to be verified, and determine the mean similarity value of the page screenshot according to the average value of the image similarities between different matching verification terminals; A modified similarity coefficient of the page screenshot is determined according to the product of the preset information weight coefficient and the similarity average value, and the modified similarity coefficient is used to determine whether the page screenshot is a secondary intercepted page screenshot.

[0058] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0059] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0060] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A method for intelligently comparing network data, characterized in that: Specifically include: Write scripts to remotely control the phone, automatically open the target application page, simulate user clicks, scroll through page data, and obtain screenshots of pages with information to be verified; The script automatically opens the pages of other terminals of the target application and obtains screenshots of the pages with the information to be verified in other terminals; The script transmits page screenshots with information to be verified from different terminals of the target application to the big data interface, and performs structured processing on the page screenshots to obtain structured data; The structured data of different terminals are compared to obtain comparison results, and the comparison results are used to determine whether they are consistent.

2. The intelligent network data comparison method according to claim 1, characterized in that: The script is constructed using the AIrTest automation tool.

3. The intelligent network data comparison method according to claim 1, characterized in that: After obtaining the page screenshot with the information to be verified, the page screenshot is placed in a corresponding folder, and when performing a comparison process on the structured data, the structured data in different folders are compared and processed respectively.

4. An intelligent network data comparison system, applied to an intelligent network data comparison method according to any one of claims 1 to 3, characterized in that: Specifically include: Preprocessing module, pre-verification module, page adjustment module, verification processing module; The pre-processing module is responsible for obtaining the information to be verified corresponding to different page screenshots, and determining whether pre-verification processing is required based on the number of terminals that perform verification processing on different page screenshots; The pre-verification module is responsible for analyzing the image similarity of the compared page screenshots of different terminals to obtain analysis results, and using the analysis results of different page screenshots to determine the verification strategy adjustment method of the page screenshots; The page adjustment module is responsible for performing screenshot adjustment processing of the page screenshot using the verification strategy adjustment method, and when it does not belong to the preset verification strategy adjustment method, the page screenshot that needs to be intercepted and adjusted is determined based on the information to be verified corresponding to different page screenshots and the analysis results of image similarity, and is used as the secondary intercepted page screenshot; The verification processing module is responsible for extracting structured data from the secondary page screenshots and page screenshots of different terminals, and comparing the structured data to obtain comparison results.

5. The intelligent comparison network data system according to claim 4, characterized in that: The number of terminals for verifying the page screenshot is determined according to a one-to-one correspondence between the page screenshot and the terminal.

6. The intelligent comparison network data system according to claim 4, characterized in that: Determine whether pre-authentication processing is required, including: Based on the information to be verified corresponding to the page screenshot, determining the quantity of information to be verified of different page screenshots and the data volume of different information to be verified; Based on the amount of information to be verified in different page screenshots and the amount of data of the information to be verified in different page screenshots, the total amount of data of the information to be verified in different page screenshots is determined, and the total amount of verification data is determined in combination with the number of terminals for verification processing of different page screenshots; Whether a pre-verification process is required is determined based on the total amount of verification data.

7. The intelligent comparison network data system according to claim 6, characterized in that: The method for determining the total amount of verification data is: The total amount of data of the information to be verified in different page screenshots and the number of terminals for verification processing of the page screenshots are used to determine the sum of the total amount of data of different terminals in different page screenshots, and the sum is used as the total amount of data; The total amount of verification data is determined based on the total amount of data in different page screenshots.

8. The intelligent comparison network data system according to claim 4, characterized in that: When no pre-verification process is required, the verification process module is directly used to extract the structured data of the page screenshot, and the structured data is compared to obtain a comparison result.

9. The intelligent comparison network data system according to claim 4, characterized in that: The screenshot adjustment process of the page screenshot is performed by using the verification strategy adjustment method, specifically including: When the preset verification strategy adjustment method is adopted, a corresponding single secondary intercepted page screenshot is generated based on different information to be verified, and the structured data of the secondary intercepted page screenshot is used for comparison to obtain the comparison result; When it does not belong to the preset verification strategy adjustment method, it is determined that a secondary page screenshot needs to be generated by intercepting the page screenshot, and the secondary page screenshot is compared with the structured data of the page screenshot to obtain a comparison result.

10. The intelligent comparison network data system according to claim 4, characterized in that: The method for determining the secondary interception page screenshot is: The terminal that performs verification processing on the page screenshot is used as a matching verification terminal, and the mean similarity value of the page screenshot is determined according to the average value of image similarities between different matching verification terminals; Determining the amount of information to be verified in the page screenshot based on the amount of information to be verified corresponding to the page screenshot, and determining a preset information weight coefficient corresponding to the page screenshot using the amount of information to be verified; A modified similarity coefficient of the page screenshot is determined according to the product of the preset information weight coefficient and the similarity average value, and the modified similarity coefficient is used to determine whether the page screenshot is a secondary intercepted page screenshot.

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