Buried point accuracy verification method based on page automatic scanning identification technology
Through automated scanning and identification technology, the accuracy of buried points is verified, and the problem of inefficient buried point verification in the existing technology is solved, and efficient and accurate buried point management and data support are achieved.
Patent Information
- Application Number
- CN202510088035.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-20
- Publication Date
- 2025-05-13
AI Technical Summary
In the prior art, the buried point verification method relies on manual scripting, which is inefficient and difficult to ensure accuracy, especially in multi-page jump scenarios, which are difficult to achieve automation and accuracy verification.
Through address library maintenance, automated test engine request jump connections, page analysis and element recognition, click operations and logging, obtain click information and comparison analysis, combine with the database to verify the accuracy of buried points and generate reports.
Improve the efficiency and accuracy of buried point verification, reduce manual intervention, ensure data quality, support data analysis and optimize user experience.
Smart Images
Figure CN119988171A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of automatic identification technology, and specifically is a method for verifying the accuracy of embedded points based on page automatic scanning and identification technology. Background Art
[0002] In the field of Internet and mobile applications, tracking is a key data collection and analysis tool used to monitor user behavior and interactions on websites or applications. The quality of tracking data is critical to optimizing user experience, improving product features, and supporting decision making. However, as the complexity and functionality of applications continue to increase, manually configuring and verifying the accuracy of tracking becomes increasingly cumbersome and error-prone.
[0003] Traditional tracking verification methods usually involve manual testing and inspection, which is not only time-consuming and labor-intensive, but also susceptible to human factors. In addition, when the page structure or function of the application changes, the accuracy verification of tracking data needs to be continuously updated and maintained, which increases the complexity of management.
[0004] The existing solution has obvious shortcomings. It only supports automated execution according to the written test scripts. When facing multiple page jump scenarios, it relies heavily on manually written scripts. In terms of tracking accuracy verification, it is impossible to track the tracking results, resulting in low efficiency and difficulty in ensuring accuracy. Summary of the invention
[0005] The purpose of the present invention is to provide a method for verifying the accuracy of embedded points based on page automatic scanning and recognition technology to solve the problems raised in the above-mentioned background technology.
[0006] In order to achieve the above-mentioned purpose, the present invention provides the following technical solution: A method for verifying the accuracy of embedded points based on page automatic scanning and recognition technology has the following specific steps:
[0007] S1: Address library maintenance: The tracking point management server is responsible for maintaining the library containing all page jump link addresses, providing basic data for subsequent operations;
[0008] S2: Request jump connection: The APP client sends a test execution instruction, and the automated test engine requests the jump connection address from the service and executes the automatic jump. This process involves the AopCrawler tool and the App i um self-test framework loading the automated script schema path;
[0009] S3: Page parsing and element identification: Automatically jump according to the obtained jump link address. After jumping to the target page, use the tool to parse the XML structure of the page, so as to automatically identify the location of clickable elements and generate a list of clickable elements;
[0010] S4: Click operation and log recording: The automation tool traverses and polls the generated list of clickable elements, executes the click operation of each element in turn, records the detailed log of each click execution, and sends these logs to the platform server;
[0011] S5: Obtain click information: The platform server obtains the specific location where the automation tool executes the click operation and the corresponding timestamp information in real time;
[0012] S6: Comparative analysis: Compare and analyze the click position and timestamp obtained by the platform server with the trigger timestamp recorded in the page embedding record to determine the relationship between the two;
[0013] S7: Verification and report generation: Verify the accuracy of the buried points through database comparison, identify the locations where no points are buried, and finally generate relevant reports.
[0014] Preferably, the address library maintenance in S1 refers to that the tracking point management server maintains a library containing all page jump link addresses. This address library lays a solid foundation for a series of subsequent operations. It ensures that the automated testing engine can accurately obtain the required jump connection address, thereby smoothly carrying out subsequent processes such as automatic jump.
[0015] Preferably, the specific steps of requesting a jump connection in S2 are as follows:
[0016] Step 1: Instruction issuance: The APP customer issues a test execution instruction to start the entire test process. At this point, the test task is clearly communicated, providing direction for subsequent operations;
[0017] Step 2: Address request: After receiving the test execution instruction, the automated test engine requests the service to jump to the connection address. During this process, the AopCrawler tool is used to assist in obtaining more accurate address information. At the same time, the App ium self-test framework starts to load the automated script schema path to prepare for the upcoming jump.
[0018] Step 3: Automatic jump: After obtaining the jump link address, the automated testing engine performs an automatic jump operation to advance the test process to the target page. This jump process is a key step, which enables subsequent page parsing and element recognition operations to be carried out.
[0019] Preferably, the specific steps of page parsing and element identification in S3 are as follows:
[0020] Step 1: Automatic jump: Based on the jump link address obtained earlier, the system automatically jumps. This step is the key to entering the target page and lays the foundation for subsequent page parsing and element recognition;
[0021] Step 2: Page parsing: After jumping to the target page, use a special tool to parse the XML structure of the page. This process is like disassembling a complex puzzle. By analyzing the XML structure, you can gain a deep understanding of the composition and layout of the page.
[0022] Step 3: Element identification and list generation: Based on parsing the page XML structure, the system automatically identifies the location of clickable elements, including buttons and links. After identification, these clickable elements are organized into a list for subsequent automated tools to traverse and operate.
[0023] Preferably, the click operation and log recording in S4 refers to the automated tool efficiently traversing and polling the generated list of clickable elements, strictly executing the click operation of each element in sequence, ensuring that no possible interaction point is missed, and while executing the click, recording the situation of each operation in detail, including the time of the click, element location information, forming a detailed log, and sending these logs to the platform server.
[0024] Preferably, obtaining click information in S5 refers to the platform server obtaining the specific location where the automated tool executes the click operation in real time, and at the same time, accurately recording the corresponding timestamp information to provide key data basis for subsequent comparative analysis.
[0025] Preferably, the comparative analysis in S6 refers to the platform server carefully comparing and analyzing the acquired click position and timestamp with the trigger timestamp of the page embedding record, aiming to determine the corresponding relationship between the two through precise comparison, in preparation for verifying the accuracy of the embedding.
[0026] Preferably, the verification and report generation in S7 refers to using the database for comprehensive comparison, strictly verifying the accuracy of the buried points, carefully screening during the comparison process, accurately identifying the locations of the unburied points, and finally, generating a detailed report based on the comparison results and identification.
[0027] The beneficial effects of the present invention are as follows:
[0028] 1. The present invention proposes a method for verifying the accuracy of tracking points based on the automatic identification technology of page elements through this scheme. It combines the automatic jump mechanism of APP pages with the page element parsing and identification mechanism, greatly improves the efficiency of tracking point verification, reduces the time and workload of manual testing, and at the same time, relies on the automatic verification mechanism to make tracking point verification more accurate, reduce the possibility of errors, and ensure data accuracy. In the context of increasingly complex business tracking point data, this scheme can improve the workflow in the field of tracking point management and data verification, provide better data support for decision-making, reduce the risks of application development and maintenance, and has important practical application value.
[0029] 2. The present invention provides a method for automatically identifying page elements to verify the accuracy of buried data. It automatically identifies page elements, analyzes page structure, attributes and user interactions, accurately identifies buried events and compares them with expectations to evaluate accuracy. This method greatly improves the efficiency and accuracy of buried data management, ensures that the collected data meets expectations, and lays a solid foundation for data analysis. At the same time, it helps to improve the workflow in the field of network analysis and user experience optimization, and provide more accurate data to support decision-making. Reducing manual intervention in an automated manner has significant advantages and broad application prospects in improving data quality, optimizing workflows and assisting scientific decision-making.
[0030] 3. The present invention utilizes the page automatic jump connection library through this method to realize automatic page traversal, without the need to repeatedly write jump scripts. It has the characteristic of high page element traversal coverage, and can repeat the scan by maintaining the jump connection library once, and achieves full coverage by identifying clickable attributes. At the same time, the point-of-entry verification efficiency is high, and operations and point-of-entry logs are automatically recorded to realize automatic identification and verification, efficiently identify element point-of-entry events and generate verification reports. This method improves the efficiency and accuracy of point-of-entry management, and provides reliable support for data analysis. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] Figure 1 This is a flow chart of the method for verifying the accuracy of embedding points based on the page automatic scanning and recognition technology of the present invention;
[0032] Figure 2 It is a schematic diagram of the complete technical solution of the present invention. DETAILED DESCRIPTION
[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0034] like Figure 1-Figure 2 As shown, the embodiment of the present invention provides a method for verifying the accuracy of tracking points based on page automatic scanning and recognition technology, and the specific steps are as follows:
[0035] S1: Address library maintenance: The tracking point management server is responsible for maintaining the library containing all page jump link addresses, providing basic data for subsequent operations;
[0036] S2: Request jump connection: The APP client sends a test execution instruction, and the automated test engine requests the jump connection address from the service and executes the automatic jump. This process involves the AopCrawler tool and the App i um self-test framework loading the automated script schema path;
[0037] S3: Page parsing and element identification: Automatically jump according to the obtained jump link address. After jumping to the target page, use the tool to parse the XML structure of the page, so as to automatically identify the location of clickable elements and generate a list of clickable elements;
[0038] S4: Click operation and log recording: The automation tool traverses and polls the generated list of clickable elements, executes the click operation of each element in turn, records the detailed log of each click execution, and sends these logs to the platform server;
[0039] S5: Obtain click information: The platform server obtains the specific location where the automation tool executes the click operation and the corresponding timestamp information in real time;
[0040] S6: Comparative analysis: Compare and analyze the click position and timestamp obtained by the platform server with the trigger timestamp recorded in the page embedding record to determine the relationship between the two;
[0041] S7: Verification and report generation: Verify the accuracy of the buried points through database comparison, identify the locations where no points are buried, and finally generate relevant reports.
[0042] Tracking points are tracking codes inserted into mobile applications or websites. They can capture user behavior and interaction data. Situations such as page browsing, button clicking, and form submission are all within their monitoring range. The data collected by tracking points can be used to analyze user behavior. Events are specific behavioral operations performed by users on applications or websites, such as clicking buttons, viewing pages, and purchasing products. Each such event is captured and recorded by tracking points. In short, tracking points are a means of obtaining data, and events are specific behaviors of users. The two are closely related. The former serves the data collection of the latter and together assists in the analysis of user behavior.
[0043] Among them, the address library maintenance in S1 refers to the fact that the tracking point management server maintains a library containing all page jump link addresses. This address library lays a solid foundation for a series of subsequent operations. It ensures that the automated testing engine can accurately obtain the required jump connection address, thereby smoothly carrying out subsequent processes such as automatic jump.
[0044] In short, the tracking points mentioned above are tracking codes inserted into mobile applications or websites to capture user behavior and interaction data, such as page views, button clicks, and form submissions. Tracking points can help analyze user behavior and generate data for analysis.
[0045] The specific steps of requesting a jump connection in S2 are as follows:
[0046] Step 1: Instruction issuance: The APP customer issues a test execution instruction to start the entire test process. At this point, the test task is clearly communicated, providing direction for subsequent operations;
[0047] Step 2: Address request: After receiving the test execution instruction, the automated test engine requests the service to jump to the connection address. During this process, the AopCrawler tool is used to assist in obtaining more accurate address information. At the same time, the App ium self-test framework starts to load the automated script schema path to prepare for the upcoming jump.
[0048] Step 3: Automatic jump: After obtaining the jump link address, the automated testing engine performs an automatic jump operation to advance the test process to the target page. This jump process is a key step, which enables subsequent page parsing, element recognition and other operations to be carried out.
[0049] In summary, the APP automation testing technology in S5 is a technology used to automate the testing of mobile applications (usually iOS and Android applications). These technologies allow developers and testers to write automated test scripts to simulate user operations in applications to verify the functionality and performance of applications. The following are currently common testing technologies and tools: Appi um: Appi um is an open source automated testing framework that supports iOS, Android, and Windows applications. It uses standard mobile application testing protocols and can write test scripts in a variety of programming languages. UIAutomator (Android) and XCUITest (iOS): These are automated testing frameworks for Android and iOS provided by Google and Apple, respectively. They allow developers to write automated test scripts for native applications for specific platforms.
[0050] The specific steps of page parsing and element identification in S3 are as follows:
[0051] Step 1: Automatic jump: Based on the jump link address obtained earlier, the system automatically jumps. This step is the key to entering the target page and lays the foundation for subsequent page parsing and element recognition;
[0052] Step 2: Page parsing: After jumping to the target page, use a special tool to parse the XML structure of the page. This process is like disassembling a complex puzzle. By analyzing the XML structure, you can gain a deep understanding of the composition and layout of the page.
[0053] Step 3: Element identification and list generation: Based on parsing the page XML structure, the system automatically identifies the location of clickable elements, including buttons and links. After identification, these clickable elements are organized into a list for subsequent automated tools to traverse and operate.
[0054] Among these steps, automatic jumps ensure the continuity of the process and allow the system to reach its goal smoothly. Page parsing is a crucial link. Just like peeling off silk from an onion, accurate analysis of the XML structure can grasp the details of the page. Element recognition and list generation are the prerequisites for subsequent automated operations. By accurately identifying clickable elements such as buttons and links and forming an ordered list, clear guidance is provided for the traversal of the automated tool, making the entire operation process more efficient and orderly.
[0055] Among them, the click operation and log recording in S4 refers to the automated tool efficiently traversing and polling the generated list of clickable elements, strictly executing the click operation of each element in turn, ensuring that no interaction point is missed, and while executing the click, recording each operation in detail, including the time of the click, element location information, forming a detailed log, and sending these logs to the platform server.
[0056] During this process, the automated tool traverses the list of clickable elements with extremely high precision. Each click is executed strictly in sequence to ensure that all interaction points are processed. The log information recorded at the time of the click is very comprehensive, such as time and location. These logs will be sent to the platform server accurately, providing a strong basis for subsequent analysis.
[0057] The acquisition of click information in S5 refers to the platform server acquiring the specific location where the automated tool performs the click operation in real time, and at the same time, accurately recording the corresponding timestamp information to provide key data basis for subsequent comparative analysis.
[0058] In short, it is of great significance for the platform server to obtain click information. It can capture the specific location of the click of the automation tool in real time and accurately record the timestamp. These detailed information are the key basis for subsequent comparative analysis, which helps to gain a deeper understanding of the operation and optimize the process.
[0059] Among them, the comparative analysis in S6 refers to the platform server carefully comparing and analyzing the obtained click position and timestamp with the trigger timestamp of the page embedding record, and through precise comparison, it aims to determine the correspondence between the two, in preparation for verifying the accuracy of the embedding.
[0060] In short, the platform server will take the obtained click position and timestamp information seriously, and compare it in detail with the trigger timestamp of the page embedding record. In this process, the correspondence between the two is rigorously explored with a high-precision comparison method, thereby laying a solid foundation for the subsequent accurate verification of whether the embedding is accurate and ensuring the effectiveness of data monitoring.
[0061] The verification and report generation in S7 refers to using the database for comprehensive comparison, strictly verifying the accuracy of the buried points, carefully screening during the comparison process, and accurately identifying the locations of unburied points. Finally, a detailed related report is generated based on the comparison results and identification conditions.
[0062] The accuracy of the buried points is strictly verified through comprehensive comparison with the database. During this process, careful screening is carried out to accurately identify the locations where no points have been buried. Based on the results of comparison and identification, a detailed report is generated to provide a basis for subsequent improvements and ensure the integrity and reliability of data collection.
[0063] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.
[0064] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.
Claims
1. A method for verifying the accuracy of embedding points based on page automatic scanning and recognition technology, characterized in that: The specific steps of the method for verifying the accuracy of the buried points based on the page automatic scanning and recognition technology are as follows: S1: Address library maintenance: The tracking point management server is responsible for maintaining the library containing all page jump link addresses, providing basic data for subsequent operations; S2: Request jump connection: The APP client sends a test execution instruction, and the automated test engine requests the jump connection address from the service and performs automatic jump. This process involves the AopCrawler tool and the Appium self-test framework loading the automated script schema path; S3: Page parsing and element identification: Automatically jump according to the obtained jump link address. After jumping to the target page, use the tool to parse the XML structure of the page, so as to automatically identify the location of clickable elements and generate a list of clickable elements; S4: Click operation and log recording: The automation tool traverses and polls the generated list of clickable elements, executes the click operation of each element in turn, records the detailed log of each click execution, and sends these logs to the platform server; S5: Obtain click information: The platform server obtains the specific location where the automation tool executes the click operation and the corresponding timestamp information in real time; S6: Comparative analysis: Compare and analyze the click position and timestamp obtained by the platform server with the trigger timestamp recorded in the page embedding record to determine the relationship between the two; S7: Verification and report generation: Verify the accuracy of the buried points through database comparison, identify the locations where no points are buried, and finally generate relevant reports.
2. According to claim 1, a method for verifying the accuracy of embedding points based on page automatic scanning and recognition technology is characterized in that: The address library maintenance in S1 refers to the fact that the tracking point management server maintains a library containing all page jump link addresses. This address library lays a solid foundation for a series of subsequent operations. It ensures that the automated testing engine can accurately obtain the required jump connection address, thereby smoothly carrying out automatic jumps and subsequent processes.
3. According to claim 1, a method for verifying the accuracy of embedding points based on page automatic scanning and recognition technology is characterized in that: The specific steps of requesting a jump connection in S2 are as follows: Step 1: Instruction issuance: The APP customer issues a test execution instruction to start the entire test process. At this point, the test task is clearly communicated, providing direction for subsequent operations; Step 2: Address request: After receiving the test execution instruction, the automated test engine requests the service to jump to the connection address. During this process, the AopCrawler tool is used to assist in obtaining more accurate address information. At the same time, the Appium self-test framework starts loading the automated script schema path to prepare for the upcoming jump. Step 3: Automatic jump: After obtaining the jump link address, the automated testing engine performs an automatic jump operation to advance the test process to the target page. This jump process is a key step, which enables subsequent page parsing and element recognition operations to be carried out.
4. According to claim 1, a method for verifying the accuracy of embedding points based on page automatic scanning and recognition technology is characterized in that: The specific steps of page parsing and element identification in S3 are as follows: Step 1: Automatic jump: Based on the jump link address obtained earlier, the system automatically jumps. This step is the key to entering the target page and lays the foundation for subsequent page parsing and element recognition; Step 2: Page parsing: After jumping to the target page, use a special tool to parse the XML structure of the page. This process is like disassembling a complex puzzle. By analyzing the XML structure, you can gain a deep understanding of the composition and layout of the page. Step 3: Element identification and list generation: Based on parsing the page XML structure, the system automatically identifies the location of clickable elements, including buttons and links. After identification, these clickable elements are organized into a list for subsequent automated tools to traverse and operate.
5. According to claim 1, a method for verifying the accuracy of embedding points based on page automatic scanning and recognition technology is characterized in that: The click operation and log recording in S4 refers to the automated tool efficiently traversing and polling the generated list of clickable elements, strictly executing the click operation of each element in turn, ensuring that no possible interaction point is missed, and while executing the click, recording each operation in detail, including the time of the click, element location information, forming a detailed log, and sending these logs to the platform server.
6. According to claim 1, a method for verifying the accuracy of embedding points based on page automatic scanning and recognition technology is characterized in that: Acquiring click information in S5 refers to the platform server acquiring the specific location where the automated tool executes the click operation in real time, and at the same time, accurately recording the corresponding timestamp information to provide key data basis for subsequent comparative analysis.
7. According to claim 1, a method for verifying the accuracy of embedding points based on page automatic scanning and recognition technology is characterized in that: The comparative analysis in S6 refers to the platform server carefully comparing the acquired click position and timestamp with the trigger timestamp of the page embedding record, and through precise comparison, it aims to determine the correspondence between the two, in preparation for verifying the accuracy of the embedding.
8. According to claim 1, a method for verifying the accuracy of embedding points based on page automatic scanning and recognition technology is characterized in that: The verification and report generation in S7 refers to using the database for comprehensive comparison, strictly verifying the accuracy of the buried points, carefully screening during the comparison process, and accurately identifying the locations of unburied points. Finally, based on the comparison results and identification conditions, a detailed related report is generated.