Automatic buried point verification method and device, readable medium and electronic equipment

Abstract

The invention relates to the technical field of computers, and discloses a burying point automatic verification method and device, a readable medium and electronic equipment. According to the method, an execution log of the UI automatic use case can be obtained, the UI automatic use case comprises a point burying step, and a mapping relation exists between the point burying step and a point burying demand rule; and determining a burying point interval log corresponding to each burying point step in the execution log, and performing burying point verification on the burying point interval log based on the burying point demand rule associated with the mapping relationship. On the basis, different burying point steps in the UI automatic use case are mapped with the corresponding burying point demand rules, so that the burying point interval log corresponding to each burying point step can be extracted to perform corresponding automatic burying point verification, manual operation is not needed to generate the burying point log, conditions do not need to be set to screen the needed log, and the user experience is improved. And the automation degree and the accuracy and efficiency of burying point verification are improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present disclosure relate to the field of computer technology, and more particularly, embodiments of the present disclosure relate to a method and device for automatic verification of a buried point, a computer readable storage medium and an electronic device. BACKGROUND

[0002] This section is intended to provide background information to facilitate an understanding of embodiments of the disclosure set forth in the claims. The description herein does not constitute admission of prior art.

[0003] A buried point is a data collection technique that can record specific user behavior or events in an application. Therefore, the quality of the buried point directly affects the quality of the collected data.

[0004] Currently, preconfigured buried point requirement rules can be selected, and logs are extracted based on manual operation, and parameters such as verification environment, user identifier, device identifier, buried point identifier, matching condition, and time range are selected for log screening, so that corresponding buried point verification is performed based on the screened logs and the selected buried point requirement rules. It can be seen that, on the one hand, this method relies on a large amount of manual operation; on the other hand, as user needs change and version functions iterate, historical buried points may change accordingly, and a large number of updates of historical buried points and their verification requirements need to be handled manually, which is costly and time-consuming. SUMMARY

[0005] In this context, embodiments of the present disclosure aim to provide a method and device for automatic verification of a buried point, a computer readable storage medium and an electronic device.

[0006] According to a first aspect of embodiments of the present disclosure, a method for automatic verification of a buried point is provided, which can include: obtaining an execution log of a user interface (UI) automation use case, the UI automation use case containing at least one buried point step, each buried point step having a mapping relationship with a corresponding buried point requirement rule; determining, in the execution log, a buried point interval log corresponding to each buried point step, respectively, and performing buried point verification on the buried point interval log based on the buried point requirement rule associated by the mapping relationship.

[0007] Optionally, performing buried point verification on the buried point interval log based on the buried point requirement rule associated by the mapping relationship includes: determining a buried point requirement quantity according to the buried point requirement rule associated by the mapping relationship; and performing buried point quantity verification based on a total number of buried point data in the buried point interval log and the buried point requirement quantity.

[0008] Optionally, the tracking point verification is performed on the tracking point interval logs based on the tracking point requirement rules associated with the mapping relationship, including: determining the tracking point requirement repetition ratio according to the tracking point requirement rules associated with the mapping relationship; obtaining the tracking point action identifier of each tracking point data in the tracking point interval logs, as well as the corresponding key and value; determining the real-time repetition ratio of tracking points with the same key and value in at least two tracking point data with the same tracking point action identifier; and performing tracking point repetition verification based on the real-time repetition ratio and the tracking point requirement repetition ratio.

[0009] Optionally, each event tracking requirement rule has a unique index identifier, and a mapping relationship is constructed between the event tracking step and the index identifier. Event tracking verification is performed on the event tracking interval logs based on the event tracking requirement rules associated with the mapping relationship, including: determining the index identifier corresponding to the event tracking step based on the mapping relationship; pulling the event tracking requirement rule from the event tracking database based on the index identifier; storing the index identifier and the corresponding event tracking requirement rule in the event tracking database; and performing event tracking verification on the event tracking interval logs based on the event tracking requirement rule.

[0010] Optionally, after retrieving the event tracking requirement rules from the event tracking database based on the index identifier, the method further includes: upon receiving a rule update notification from the event tracking database, retrieving the updated event tracking requirement rules from the event tracking database based on the index identifier; the rule update notification is sent by the event tracking database when the event tracking requirement rules are updated; and performing event tracking verification on the event tracking interval logs based on the event tracking requirement rules, including: performing event tracking verification on the event tracking interval logs based on the updated event tracking requirement rules.

[0011] Optionally, obtaining the execution log of the UI automation test case includes: during the execution of the steps of the UI automation test case, pulling the log generated by the execution of each tracking point step to obtain the execution log; or, after the execution of the steps of the UI automation test case is completed, pulling the log generated by the execution of at least one step to obtain the execution log.

[0012] Optionally, the method further includes: if the logs generated by any step fail to be pulled, polling the logs generated by the step until the pull is successful, and obtaining the execution logs.

[0013] Optionally, the execution logs of UI automation test cases are obtained, including: receiving a data tracking verification request sent when continuous integration is triggered; continuous integration is triggered when a predetermined event occurs, the predetermined event including any one of test events, release events, and timed events; and in response to the data tracking verification request, obtaining the execution logs of UI automation test cases.

[0014] According to a second aspect of the present disclosure, an automated event tracking verification device is provided. The device may include: a log retrieval module, configured to retrieve execution logs of UI automation test cases, wherein the UI automation test cases contain at least one event tracking step, and each event tracking step has a mapping relationship with a corresponding event tracking requirement rule; and an event tracking verification module, configured to determine the event tracking interval logs corresponding to each event tracking step in the execution logs, and to perform event tracking verification on the event tracking interval logs based on the event tracking requirement rule associated with the mapping relationship.

[0015] Optionally, the event tracking verification module is specifically used to determine the number of event tracking requirements based on the event tracking requirement rules associated with the mapping relationship; and to verify the number of event tracking based on the total number of event tracking data in the event tracking interval log and the number of event tracking requirements.

[0016] Optionally, the event tracking verification module is specifically used to determine the event tracking requirement repetition ratio based on the event tracking requirement rules associated with the mapping relationship; obtain the event tracking action identifier of each event tracking data in the event tracking interval log, as well as the corresponding key and value; determine the real-time repetition ratio of event tracking with the same key and value among at least two event tracking data with the same event tracking action identifier; and perform event tracking repetition verification based on the real-time repetition ratio and the event tracking requirement repetition ratio.

[0017] Optionally, each tracking point requirement rule has a unique index identifier, and a mapping relationship is constructed between the tracking point step and the index identifier. The tracking point verification module is specifically used to determine the index identifier corresponding to the tracking point step based on the mapping relationship; pull the tracking point requirement rule from the tracking point database based on the index identifier; store the index identifier and the corresponding tracking point requirement rule in the tracking point database; and perform tracking point verification on the tracking point interval logs based on the tracking point requirement rule.

[0018] Optionally, the event tracking verification module is also used to retrieve the updated event tracking requirement rules from the event tracking database based on the index identifier when a rule update notification is received from the event tracking database; the rule update notification is sent by the event tracking database when the event tracking requirement rules are updated; and to perform event tracking verification on the event tracking interval logs based on the updated event tracking requirement rules.

[0019] Optionally, the log retrieval module is specifically used to retrieve the logs generated by each step of the UI automation test case during the execution of the steps, and obtain the execution log; or, the log retrieval module is specifically used to retrieve the logs generated by at least one step after the execution of the UI automation test case is completed, and obtain the execution log.

[0020] Optionally, the log retrieval module is also used to poll and retrieve the logs generated by any step in the execution until the retrieval is successful, in the event that the retrieval of the logs generated by any step fails.

[0021] Optionally, the log retrieval module is specifically used to receive the event tracking verification request sent when continuous integration is triggered; continuous integration is triggered when a predetermined event occurs, and the predetermined event includes any one of test events, release events, and timed events; in response to the event tracking verification request, the execution log of the UI automation test case is obtained.

[0022] According to a third aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements any of the above-described automated verification methods for data embedding.

[0023] According to a fourth aspect of the present disclosure, an electronic device is provided, including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any of the above-described automated verification methods for data embedding via executing the executable instructions.

[0024] This disclosure provides an automated tracking verification method, an automated tracking verification device, a computer-readable storage medium, and an electronic device. The method can acquire the execution log of a UI automation test case, which includes tracking steps pointing to corresponding steps within the UI automation test case, and the tracking steps are mapped to tracking requirement rules. The method identifies the tracking interval log corresponding to each tracking step in the execution log and performs tracking verification on the tracking interval log based on the tracking requirement rules associated with the mapping relationship. Based on this, by mapping different tracking steps in the UI automation test case to corresponding tracking requirement rules, the tracking interval log corresponding to each tracking step can be extracted for corresponding automated tracking verification. This eliminates the need for manual operation to generate tracking logs or manual setting of conditions to filter required logs, improving the level of automation and the accuracy and efficiency of tracking verification. Attached Figure Description

[0025] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation, in which:

[0026] FIG. 1 One of the step flowcharts of the automated verification method for data embedding according to an embodiment of this disclosure is shown.

[0027] FIG. 2 A schematic diagram illustrating the principle of determining the embedded point interval log in an implementation of this disclosure is shown.

[0028] FIG. 3 The second flowchart of the automated verification method for data embedding according to the present disclosure is shown.

[0029] FIG. 4The third step of the automated verification method for data embedding according to the present disclosure is shown in the flowchart.

[0030] FIG. 5 The flowchart illustrating the implementation architecture of the automated verification method for data tracking combined with continuous integration according to embodiments of this disclosure is shown.

[0031] FIG. 6 A schematic diagram of the automated verification device for embedded points according to an embodiment of the present disclosure is shown.

[0032] FIG. 7 A schematic diagram of a computer-readable storage medium according to an embodiment of the present disclosure is shown.

[0033] FIG. 8 A schematic diagram of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0034] The principles and spirit of this disclosure will now be described with reference to several exemplary embodiments. It should be understood that these embodiments are given merely to enable those skilled in the art to better understand and implement this disclosure, and are not intended to limit the scope of this disclosure in any way. Rather, these embodiments are provided to make this disclosure more thorough and complete, and to fully convey the scope of this disclosure to those skilled in the art.

[0035] Those skilled in the art will recognize that embodiments of this disclosure can be implemented as a system, apparatus, device, method, or computer program product. Therefore, this disclosure can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0036] According to embodiments of this disclosure, an automated verification method for data tracking points, an automated verification device for data tracking points, a computer-readable storage medium, and an electronic device are provided.

[0037] In this document, any number of elements in the accompanying figures is for illustrative purposes and not for limitation, and any naming is for distinction only and has no limiting meaning.

[0038] The principles and spirit of this disclosure are explained in detail below with reference to several representative embodiments.

[0039] Existing automated event tracking verification typically requires manual selection of the event tracking rules to be verified, followed by selection of the verification environment, user ID or device ID, and the action to be tracked, matching conditions, and time range as filtering criteria for the event tracking logs. Upon manual selection to begin verification, a new page is displayed. This new page then allows manual operation within the client application to generate event tracking logs based on the selected functional scenario corresponding to the event tracking rule. The system then automatically retrieves these logs and verifies the corresponding event tracking rules according to the matching conditions to obtain the event tracking verification results.

[0040] The above solution automates verification based on manual selection of event tracking rules and generation of event tracking logs, achieving a deeply human-involved automated verification process. However, in the development process, all new event tracking requirements for new features need to be verified before deployment. Existing historical event tracking may also be affected by the addition of new features or updates to historical features as versions are released. Moreover, event tracking may not only include business event tracking but also various complex event tracking types such as technical event tracking and debugging event tracking. In other words, the large number of event tracking points, their diverse types, and different versions may require multiple tests in different verification environments. The verification selection criteria may need to be repeated, multiple times, and in multiple combinations. In this case, deep manual intervention will lead to time-consuming and costly event tracking verification, resulting in low efficiency and insufficient accuracy of the entire verification process.

[0041] In the embodiments disclosed herein, UI (User Interface) automation in the client is used to achieve automatic and accurate regression verification of event tracking. UI automation test cases can consist of multiple automatically executed steps on a page of the client application. Each UI automation test case can contain one or more event tracking steps. These steps can refer to steps triggered by the page entered within the UI automation test case that collect event tracking data, or steps triggered by the performed operation that collect event tracking data. Each event tracking step can trigger the collection of event tracking data for one or more event tracking points, and each event tracking step also has a mapping relationship with a corresponding event tracking requirement rule. Based on this, the collected execution logs contain event tracking interval logs corresponding to the event tracking steps. Therefore, event tracking verification of the event tracking interval logs can be automatically performed based on the mapping relationship and the event tracking requirement rules associated with the event tracking steps, realizing batch automated verification of the event tracking points corresponding to the functions while executing UI automation test cases.

[0042] After introducing the basic principles of the present invention, various non-limiting embodiments of the present invention will be described in detail below.

[0043] Example Application Scenarios

[0044] It should be noted that the following application scenarios are shown only to facilitate understanding of the spirit and principles of the present invention, and the embodiments of this disclosure are not limited in any way. On the contrary, the embodiments of this disclosure can be applied to any applicable scenario.

[0045] The automated verification method for tracking points disclosed herein can be applied to various application scenarios involving client version development testing, online monitoring, etc.

[0046] In one application scenario, after the client version is developed and before it goes online for testing, when performing functional testing through UI automated test cases, the generated execution logs can be automatically matched and verified with the associated tracking rules by mapping the tracking steps to the tracking requirement rules, thereby achieving automated UI tracking verification.

[0047] In another application scenario, online monitoring may be involved. After the client version is released, the data of the tracking points are collected online, and the quality of the tracking points is verified based on the execution logs to adapt to the dynamic changes in the tracking point requirements. This disclosure does not impose specific limitations on this.

[0048] Example Method

[0049] The following section, in conjunction with the above application scenarios, provides reference... FIG. 1 This describes an automated verification method for data entry points according to exemplary embodiments of the present disclosure.

[0050] like FIG. 1 One of the steps of the automated verification method for data tracking shown in the exemplary embodiments of this disclosure may include the following steps 101 to 102:

[0051] Step 101: Obtain the execution log of the UI automation test case. The UI automation test case contains at least one tracking step, and each tracking step has a mapping relationship with the corresponding tracking requirement rule.

[0052] In this embodiment, UI automation test cases can be automated test cases applied when performing automated functional testing on the object under test based on the UI. In practical applications, the object under test can be a web (web page) or an app. UI automation test cases can be written based on the required test scenarios and functions, and perform functional testing by automatically reproducing the operation of entering the page under test and the operation of functions on the page under test. Each UI automation test case can include one or more steps, which can be an operation to enter the page under test or an operation to trigger a function on the page under test. The triggering of the function can be clicking a function button, inputting information in an input box, etc. This embodiment does not impose specific restrictions on the form and content of the steps in the UI automation test cases.

[0053] Based on this, event tracking is a technology for collecting, processing, and sending operational data of the object under test. Essentially, it involves monitoring events occurring during the operation of the webpage or application under test, and making judgments and collecting data when events of interest to the testing requirements occur. Therefore, in the UI automation use cases provided in this disclosure, the steps that trigger event tracking data collection during execution are designated as event tracking steps. For example, if entering the page under test can trigger event tracking data collection, the step of entering the page under test is designated as an event tracking step; or, if selecting a function on the page under test triggers event tracking data collection, the step of selecting the function is designated as an event tracking step. The above description of event tracking steps is merely illustrative; those skilled in the art can determine the event tracking steps in the UI automation use cases according to actual needs.

[0054] Furthermore, the event tracking requirement rules specify that the operational data collected by the event tracking points must conform to the defined rules of the test analysis requirements, such as the page or operation corresponding to the event tracking point, the data type collected by the event tracking point, the number of event tracking points, etc. Based on this, the event tracking steps in UI automation test cases can be associated with the corresponding event tracking requirement rules, so that each event tracking step has a mapping relationship with the corresponding event tracking requirement rule. This mapping relationship can be stored in the form of a mapping table for easy querying and retrieval.

[0055] Execution logs are the logs generated by the object under test during the execution of UI automation test cases, including logs generated when each tracking step is executed.

[0056] Step 102: Determine the corresponding tracking interval log for each tracking step in the execution log, and perform tracking verification on the tracking interval log based on the tracking requirement rules associated with the mapping relationship.

[0057] In this embodiment, the execution log includes logs generated during the execution of each tracking step of the UI automation use case, and their order corresponds to the execution order of the tracking steps. The tracking interval log is the log generated during the execution of a tracking step, and can be determined according to the execution order of the tracking steps and the order of log generation times corresponding to the start and end times. For example, the start time of the tracking step execution can be used as the start time of the corresponding tracking interval log, and the end time of the tracking step execution can be used as the end time of the corresponding tracking interval log; or, the start time of the tracking step execution can be used as the start time of the corresponding tracking interval log, and the start time of the next adjacent tracking step can be used as the end time of the corresponding tracking interval log. This embodiment does not impose specific limitations on this.

[0058] Based on this, the tracking requirement rules associated with each tracking step can be determined according to the mapping relationship. Then, tracking verification can be performed on the tracking interval logs corresponding to the tracking steps according to the tracking requirement rules. Specifically, the operation data collected in the tracking interval logs can be verified based on the tracking requirement rules to see if it meets the tracking requirements, thereby verifying the quality of the tracking.

[0059] like FIG. 2 The diagram shown illustrates the principle of determining the embedded point interval log in an exemplary embodiment of this disclosure, as follows: FIG. 2 As shown, UI automation test cases include tracking step 1, tracking step 2, etc. The execution logs generated when UI automation test cases are executed include tracking interval log 1 generated when tracking step 1 is executed, tracking interval log 2 generated when tracking step 2 is executed, and so on.

[0060] In this example, the start time of logging interval 1 is the start time of logging step 1, and the end time of logging interval 1 is the start time of logging step 2; and so on, the start time of logging interval 2 can be the start time of logging step 2, the end time of logging interval 2 can be the start time of logging step 3, and so on. If the logging step is the last step of a UI automation use case, then the start time of the logging interval corresponding to that logging step can also be the start time of that last step, and the end time can be the end time of that last step.

[0061] Based on this, the logs generated during the execution of the tracking steps can be accurately matched.

[0062] In an optional embodiment of this disclosure, step 102, which verifies the logging of the logging interval based on the logging requirement rules associated with the mapping relationship, may include the following steps A1 to A2:

[0063] Step A1: Determine the number of tracking points required based on the tracking point requirement rules associated with the mapping relationship.

[0064] Step A2: Verify the number of tracking points based on the total number of tracking point data in the tracking point interval log and the number of tracking point requirements.

[0065] In this embodiment, the number of tracking points can be verified during tracking point verification. In some scenarios, a tracking step can only trigger the collection of one type of tracking data, with one type of tracking data corresponding to one tracking point. For example, when a video automatically starts playing after clicking to enter the playback page, it is necessary to determine whether the playback page has been entered. In the tracking point requirement rules, the tracking action identifier action=playstart can be defined. Since the determination that the playback page will automatically start playing should only occur once, the number of tracking points required for playback is one. Alternatively, in some scenarios, a step can include the collection of multiple tracking data. For example, when a browsing page has multiple displayed contents, the first three displayed contents are exposed during the page scrolling loading process, and operation data is collected when subsequent displayed contents are not exposed. In this case, it is necessary to determine the exposure quantity of the displayed contents. In the tracking point requirement rules, action=impress can be used. Since the exposure of each displayed content needs to be determined separately, the number of tracking points required for exposure is three. The above requirements for the number of tracking points can be adjusted according to the needs of the actual application scenario, and the required number of tracking points can be defined in the tracking point requirement rules.

[0066] Based on this, according to the tracking requirement rules associated with the mapping relationship, the number of tracking points required when collecting tracking data can be determined. The tracking data in the tracking interval log is the operation data collected when the tracking steps of UI automation use cases are automatically executed on the tested object, triggering the tracking. Examples include playback data collected by `action=playstart` upon entering the playback page, or exposure data of content displayed on the browsing page collected by `action=playstart`, reflecting the total number of actual tracking points. Assuming the tracking requirement rule for `action=playstart` defines the number of tracking points required as 1, and `action=playstart` appears once in the tracking interval log, then the tracking point quantity verification is considered successful; otherwise, it fails, indicating a possible over-tracking issue, leading to abnormal collected operation data. If the event tracking rule for action=impress defines the number of tracking points as 3, and action=impress appears three times in the tracking interval log, then the tracking point quantity verification is considered successful; otherwise, it fails. If the number of occurrences of action=impress is less than 3, it can be considered that there is a problem of missing tracking points; conversely, if the number of occurrences of action=impress is greater than 3, it can be considered that there is a problem of excessive tracking points.

[0067] In an optional embodiment of this disclosure, step 102, which verifies the logging of the logging interval based on the logging requirement rules associated with the mapping relationship, may include the following steps B1 to B4:

[0068] Step B1: Determine the repetition ratio of tracking points based on the tracking point requirement rules associated with the mapping relationship.

[0069] Step B2: Obtain the event identifier of each event data point in the event tracking interval log, as well as the corresponding key and value.

[0070] Step B3: Determine the real-time repetition ratio of data points with the same key and value among at least two data points with the same data point action identifier.

[0071] Step B4: Verify the repetition of data points based on the real-time repetition ratio and the required repetition ratio.

[0072] In this embodiment, duplicate tracking verification is supported during tracking verification. In some scenarios, duplicate tracking points may exist. For example, when the collected tracking data has the same action, further differentiation by key-value pairs may reveal identical keys, some identical values, and others different values. Alternatively, debugging key-value pairs can be added during development, where the values ​​may change over time and depending on the scenario. Duplicate tracking verification can be achieved by analyzing the overlap ratio between two tracking data points. This overlap ratio can be set according to the actual tracking requirements of the scenario to exclude the influence of debugging logs. The overlap ratio for tracking requirements can be defined in the tracking requirement rules, such as 90%, 95%, or any value between 0% and 100%.

[0073] In this embodiment, the repetition rate of tracking requirements during tracking data collection can be determined based on the tracking requirement rules associated with the mapping relationship. The real-time repetition rate of tracking can be determined based on the matching and comparison analysis of tracking data in the tracking interval log. Specifically, tracking action identifiers and corresponding key-value pairs are identified in the tracking data. Based on this, the tracking action identifiers in the tracking interval log are first matched. If the tracking action identifiers are the same, the key-value pairs are then matched to determine whether tracking duplication has occurred. The real-time repetition rate of tracking is then calculated in the tracking data, and tracking duplication verification is performed based on the real-time repetition rate and the tracking requirement repetition rate. For example, if there are m keys in tracking data 1 in the tracking interval log, and n keys in tracking data 2 with the same action as tracking data 1, and after matching, it is determined that tracking data 1 and tracking data 2 have x key-value pairs that are the same, then the real-time duplication ratio of tracking data 1 is x / m, and the real-time duplication ratio of tracking data 2 is x / n. If both x / m and x / n exceed the required duplication ratio for tracking, it can be judged that tracking data 1 and tracking data 2 are suspected of duplication, and the tracking duplication verification fails; otherwise, the tracking duplication verification is considered to have passed.

[0074] In this embodiment of the disclosure, the following is an example scenario of repeated data embedding:

[0075] In a video playback scenario, within the same data collection step, from the end of normal video playback to the automatic playback of the next video, the following data collection points a and b are collected.

[0076] Tracking data a:

[0077] XXXX-XX-XX 15:06:07.815

[0078] playend{"id":"XXX","is_autoplay":"0","position":"7","video_classify":"1010","time":"5","is_nextplay":"0","source":"recomvideo","type":"video","vi deo_classifyid":"123","download":"0","netstatus":"wifi","end":"playend","pla yer_name":"NewPlayer","is_newversion":"1","page":"revideo"}

[0079] Data point b:

[0080] XXX-XX-XX 15:06:07.914

[0081] playend{"id":"XXX","is_autoplay":"0","position":"7","video_classify":"1010","time":"5","is_nextplay":"0","source":"recomvideo","type":"video","vi deo_classifyid":"123","download":"0","netstatus":"wifi","end":"playend","is_newversion":"1","page":"revideo"}

[0082] As we can see, both event tracking data a and b have the action "playend" and their timings are close. Event tracking data a has an additional "player_name" field in its key field compared to event tracking data b, but the values ​​corresponding to the same key are identical. Based on this, calculations show that the real-time duplication rate of event tracking data a and b both exceed the required rate. Therefore, the duplication verification for event tracking data a and b fails.

[0083] In a video playback scenario, within the same data collection step, from the end of video playback due to screen swiping to the automatic playback of the next video, the following data collection points are collected: c and d.

[0084] Tracking data c:

[0085] XXXX-XX-XX 20:53:14.361:

[0086] playend{"id":"XXX","is_autoplay":"0","position":"1","video_classify":"1212","time":"3","is_nextplay":"0","source":"recomvideo","type":"video","vi deo_classifyid":"2100","download":"0","netstatus":"wifi","end":"interrupt","player_name":"NewPlayer","is_newversion":"1"}

[0087] Tracking data d:

[0088] XXXX-XX-XX 20:53:14.384:

[0089] playend{"id":"XXX","is_autoplay":"0","position":"1","video_classify":"1212","time":"3","is_nextplay":"0","source":"recomvideo","type":"video","vi deo_classifyid":"2100","download":"0","netstatus":"wifi","end":"playend","pl ayer_name":"NewPlayer","is_newversion":"1"}

[0090] As can be seen, the action for both event tracking data c and d is "playend", and their time points are close, with the same key field. Specifically, the value of the end field in event tracking data c is "interrupt", indicating playback interruption, while the value of the end field in event tracking data d is "playend". Based on this, by calculating that the real-time duplication rate of event tracking data c and d is greater than the required rate, the duplication verification for event tracking data c and d fails.

[0091] In an optional embodiment of this disclosure, the aforementioned verification of the number of tracking points and verification of duplicate tracking points can be performed individually or in combination. For example, only the number of tracking points can be verified, only the duplicate tracking points can be verified, or the number of tracking points can be verified based on the duplicate tracking points verification, thus avoiding duplicate tracking points from being treated as multiple tracking points and improving the accuracy of the verification results. Those skilled in the art can select and combine tracking point verification schemes according to actual needs, and this embodiment does not impose specific limitations in this regard.

[0092] The above-described verification of the number of tracking points and verification of tracking point duplication are merely examples. Those skilled in the art can further expand other tracking point verification schemes according to actual needs, and the embodiments disclosed herein do not impose specific limitations on them. Tracking point verification can systematically and automatically evaluate the quality of tracking points, and provide feedback, error reports, and warnings for tracking point data that fails verification, so as to guide the improvement of tracking points and further improve the quality of the collected operational data on the basis of improving the quality of tracking points.

[0093] For example, if tracking data 'a' and tracking data 'b' return to the front end with an error message indicating suspected duplicate tracking, analysis determines that only one tracking data point with at least action=playend, key=end, and value=playend should be collected when the video playback ends normally. Therefore, tracking data 'b' constitutes a duplicate tracking point relative to 'a'. Similarly, if tracking data 'c' and tracking data 'd' return to the front end with an error message indicating suspected duplicate tracking, analysis determines that only one tracking data point with at least action=playend, key=end, and value=interrupt should be collected when the video playback ends interrupted. Therefore, tracking data 'd' constitutes a duplicate tracking point relative to 'c'. Based on the analysis results, abnormal tracking points can be handled.

[0094] like FIG. 3 The second flowchart of the automated verification method for data embedding shown in this embodiment of the present disclosure may include the following steps 301 to 304:

[0095] Step 301: Obtain the execution log of the UI automation test case. The UI automation test case contains at least one tracking step, and each tracking step has a mapping relationship with the corresponding tracking requirement rule.

[0096] In this embodiment of the disclosure, step 301 can be referred to the relevant description of step 201 above. To avoid repetition, it will not be repeated here.

[0097] In this embodiment, execution logs can be automatically retrieved based on user identifier, environment, time, platform, version number, etc., during the execution of UI automation test cases. When retrieving execution logs, it can also determine whether there is any event tracking data and verify the correspondence between the generation time of the event tracking data and the execution time of the UI automation test case steps, ensuring that the retrieved execution logs are generated by the event tracking steps of the UI automation test case.

[0098] In one embodiment of this disclosure, step 301 may be step C1 as follows:

[0099] During the execution of UI automation test cases, the logs generated by each step of the event tracking are retrieved to obtain the execution logs.

[0100] In this embodiment, logs generated by each tracking step can be synchronously retrieved during the execution of UI automation test cases, so that execution logs containing the sequentially generated logs of each tracking step can be synchronously obtained after the UI automation test cases are completed. Because of this synchronous retrieval, the retrieval time, tracking time, and tracking step execution time can correspond.

[0101] In one embodiment of this disclosure, step 301 may be step C2 as follows:

[0102] After the steps of the UI automation use case are completed, pull the logs generated by at least one of the instrumented steps to obtain the execution logs.

[0103] In this embodiment of the disclosure, after the UI automation use case process is completed, the logs generated by at least one of the tracking steps can be retrieved separately to obtain the execution logs. During retrieval, the execution time of the tracking step and the log generation time can be used to determine whether the retrieved logs are generated by the tracking step corresponding to the UI automation use case.

[0104] In one embodiment of this disclosure, the method may further include the following step C3:

[0105] If the logs generated by any of the event tracking steps fail to be retrieved, the system will poll and retrieve the logs generated by the event tracking steps until the retrieval is successful, thus obtaining the execution logs.

[0106] In this embodiment of the disclosure, the logs generated by the execution of any event tracking step may fail to be retrieved, such as due to data corruption or loss during transmission caused by network environment fluctuations. In this case, the logs generated by the execution of the event tracking step can be retrieved in a polling manner until the retrieval is successful.

[0107] In one embodiment of this disclosure, each embedding point requirement rule has a unique index identifier.

[0108] In this embodiment of the disclosure, in order to set a unique index identifier for each tracking point requirement rule so as to manage and maintain the tracking point requirement rule, the smn field can be used as the index of the tracking point requirement rule, and different tracking point requirement rules can be uniquely distinguished by the value of the smn field.

[0109] Step 302: Determine the log interval corresponding to each tracking step in the execution log, and determine the index identifier corresponding to the tracking step based on the mapping relationship.

[0110] In this embodiment of the disclosure, the log of the embedded point interval can be referred to the relevant description of step 202 above. To avoid repetition, it will not be repeated here.

[0111] Furthermore, based on the index identifiers corresponding to the event tracking requirement rules, the event tracking steps in UI automation use cases can be mapped to the corresponding event tracking requirement rules through the index identifiers. Therefore, based on the mapping relationship, the index identifiers corresponding to the event tracking steps can be determined on the automation execution side. In this way, there is no need to store and maintain the event tracking requirement rules locally on the automation execution side, allowing for more flexible deployment of the storage location for the event tracking requirement rules.

[0112] Step 303: Retrieve the tracking requirement rules from the tracking database based on the index identifier; the tracking database stores the index identifier and the corresponding tracking requirement rules.

[0113] In this embodiment, the event tracking database can store index identifiers and corresponding event tracking requirement rules. The event tracking database can be an independent database deployed locally on the automation execution side or deployed on a remote event tracking platform. The event tracking platform can create, modify, and delete event tracking requirement rules and provide the automation execution side with an index identifier corresponding to each event tracking requirement rule. This allows the automation execution side to establish a mapping relationship between event tracking steps and event tracking requirement rules in UI automation use cases based on the index identifiers. Based on this, the event tracking requirement rules corresponding to the event tracking steps can be retrieved from the event tracking database based on the index identifiers. These event tracking requirement rules can correspond to the collection requirements of each event tracking data point in the event tracking interval log.

[0114] Step 304: Perform tracking verification on the tracking interval logs based on the tracking requirement rules.

[0115] In this embodiment of the disclosure, the verification of the embedded points can be referred to the relevant description of step 202 above. To avoid repetition, it will not be repeated here.

[0116] In one embodiment of this disclosure, step D1 may be included after step 303:

[0117] Step D1: Upon receiving a rule update notification from the event tracking database, retrieve the updated event tracking requirement rules from the event tracking database based on the index identifier; the rule update notification is sent by the event tracking database when the event tracking requirement rules are updated.

[0118] In this embodiment, when a tracking requirement rule in the tracking database is updated (e.g., created, modified, or deleted), a rule update notification can be sent to the automation execution side. This rule update notification can provide the index identifier corresponding to the updated tracking requirement rule. The tracking database can send rule update notifications when all tracking requirement rules are updated, or it can compare the update time of a tracking requirement rule with the time of its most recent fetch and determine whether to send a rule update notification based on the comparison result. Based on the timing of the tracking requirement rule update, it can be analyzed whether the update occurred after the most recent fetch, so that the UI automation execution side can obtain the updated tracking requirement rule.

[0119] Alternatively, the UI automation execution side can receive rule update notifications triggered by the most recently fetched event tracking rule and directly re-fetch the updated event tracking rule; it can also receive rule update notifications sent when all event tracking rules are updated, determine the fetching status of the event tracking rule based on the index identifier, and re-fetch the most recently fetched event tracking rule; furthermore, it can also maintain the mapping relationship based on the updated event tracking rule corresponding to the index identifier, and this disclosure does not impose specific limitations on this.

[0120] In an optional implementation of this disclosure, the UI automation execution side can also perform periodic synchronization of event tracking rules, and maintain the mapping relationship between event tracking steps and event tracking rules based on the index identifiers and corresponding event tracking rules in the event tracking database.

[0121] Based on step D1, step 304 may include the following step D2:

[0122] Step D2: Perform event tracking verification on the event tracking interval logs based on the updated event tracking requirement rules.

[0123] Based on this, the updated event tracking requirement rules can be used to verify the event tracking interval logs, so as to ensure the timeliness and accuracy of event tracking verification.

[0124] like FIG. 4 The third step of the automated verification method for data collection points shown in this embodiment of the present disclosure may include the following steps 401 to 403:

[0125] Step 401: Receive the data entry verification request sent when continuous integration is triggered; continuous integration is triggered when a predetermined event occurs, which may include any one of the following: test event, release event, or timed event.

[0126] Continuous integration is a process of automatically detecting, pulling, building, and unit testing after code changes. In this embodiment, it is also possible to perform instrumentation verification when UI automation test cases are automatically triggered during continuous integration. Specifically, the steps in the UI automation test cases can be aggregated according to the core instrumentation scope of the actual business to form an automatic verification instrumentation execution set. Furthermore, the automatic verification instrumentation execution set can be divided according to different functions of the business to perform localized and targeted automatic instrumentation verification.

[0127] Building upon this foundation, continuous integration is triggered upon the occurrence of a predetermined event to send a verification request for the corresponding automated verification event set. The predetermined time can be a test event, a release event, or a scheduled event. Test events can occur after feature development and testing, allowing for the early detection of issues with core event tracking rather than during regression testing. Release events can occur when code is merged into a release branch for version release. Before release, automated event tracking verification can be performed concurrently with UI automated testing. Release can be requested after both functional testing and event tracking verification pass, reducing the chance of missing event tracking issues introduced by continuous integration. Scheduled events can be set to periodically execute customized automated verification event sets for web or app-based environments. An alarm mechanism can be configured for failed event tracking verification, triggering notifications via instant messaging, email, phone, SMS, or other messaging channels to promptly recall event tracking issues online. This fully automated event tracking verification process maintains event tracking quality.

[0128] Step 402: In response to the event tracking verification request, obtain the execution log of the UI automation test case.

[0129] In this embodiment of the disclosure, step 402 can be referred to in the relevant description of step 201 or step 301 above. To avoid repetition, it will not be described again here.

[0130] Step 403: Determine the corresponding tracking interval log for each tracking step in the execution log, and perform tracking verification on the tracking interval log based on the tracking requirement rules associated with the mapping relationship.

[0131] In this embodiment of the disclosure, step 403 can be referred to in the aforementioned description of step 202, or steps 302 to 304. To avoid repetition, it will not be described again here.

[0132] like FIG. 5 The illustrated embodiment of this disclosure presents a flowchart of the implementation architecture for an automated data tracking verification method combined with continuous integration. This method is applied to an app.

[0133] Continuous integration is triggered when test events, release events, or timed events occur, and the mobile application is packaged and sent as an APP package along with a data tracking verification request.

[0134] The UI automation execution side responds to the event tracking verification request by triggering the corresponding automatic verification event tracking execution set, which can include UI automation use cases for function and event tracking verification. Based on this, it obtains the execution log and pulls the associated event tracking requirement rules to perform automated event tracking verification.

[0135] If the event tracking verification passes, the corresponding pre-defined event verification result will be executed. For example, if the test event confirms that the corresponding function can be submitted for testing, if the release event confirms that the regression phase has passed, the version can be released, and if the timed event does not trigger the alarm mechanism.

[0136] This disclosure provides an automated event tracking verification method. It can obtain the execution logs of UI automation test cases, which contain event tracking steps pointing to corresponding steps within the test case. These event tracking steps are mapped to event tracking requirement rules. The method identifies the event tracking interval logs corresponding to each event tracking step in the execution logs and performs event tracking verification on the event tracking interval logs based on the associated event tracking requirement rules. By mapping different event tracking steps in UI automation test cases to corresponding event tracking requirement rules, it is possible to extract the event tracking interval logs corresponding to each event tracking step for automated event tracking verification. This eliminates the need for manual operation to generate event tracking logs or manually setting conditions to filter required logs, thus improving the level of automation and the accuracy and efficiency of event tracking verification.

[0137] Example Device

[0138] After introducing the automated verification method for data tracking according to exemplary embodiments of this disclosure, the following will refer to... FIG. 6 An automated verification device for data embedding according to an exemplary embodiment of this disclosure will be described.

[0139] It should be noted that other specific details of the various functional modules of the automated verification device for data tracking in this disclosure have been described in detail in the above-described embodiments of the automated verification method for data tracking, and will not be repeated here.

[0140] FIG. 6 An exemplary embodiment of the present disclosure illustrates an automated event tracking verification device 600, which may include: a log retrieval module 601, configured to retrieve execution logs of UI automation test cases, wherein each UI automation test case contains at least one event tracking step, and each event tracking step is mapped to a corresponding event tracking requirement rule; and an event tracking verification module 602, configured to determine the event tracking interval logs corresponding to each event tracking step in the execution logs, and to perform event tracking verification on the event tracking interval logs based on the event tracking requirement rules associated with the mapping relationship.

[0141] In an optional embodiment of this disclosure, the event tracking verification module 602 is specifically used to determine the number of event tracking requirements based on the event tracking requirement rules associated with the mapping relationship; and to verify the number of event tracking based on the total number of event tracking data in the event tracking interval log and the number of event tracking requirements.

[0142] In an optional embodiment of this disclosure, the event tracking verification module 602 is specifically used to determine the event tracking requirement repetition ratio according to the event tracking requirement rules associated with the mapping relationship; obtain the event tracking action identifier of each event tracking data in the event tracking interval log, as well as the corresponding key and value; determine the real-time repetition ratio of event tracking with the same key and value among at least two event tracking data with the same event tracking action identifier; and perform event tracking repetition verification based on the real-time repetition ratio of event tracking and the event tracking requirement repetition ratio.

[0143] In an optional implementation of this disclosure, each tracking point requirement rule has a unique index identifier, and a mapping relationship is constructed between the tracking point step and the index identifier. The tracking point verification module 602 is specifically used to determine the index identifier corresponding to the tracking point step based on the mapping relationship; pull the tracking point requirement rule from the tracking point database based on the index identifier; store the index identifier and the corresponding tracking point requirement rule in the tracking point database; and perform tracking point verification on the tracking point interval log based on the tracking point requirement rule.

[0144] In an optional embodiment of this disclosure, the event tracking verification module 602 is further configured to, upon receiving a rule update notification from the event tracking database, retrieve the updated event tracking requirement rules from the event tracking database based on the index identifier; the rule update notification is sent by the event tracking database when the event tracking requirement rules are updated; and to perform event tracking verification on the event tracking interval logs based on the updated event tracking requirement rules.

[0145] In an optional embodiment of this disclosure, the log retrieval module 601 is specifically used to retrieve the logs generated by each tracking step during the execution of the UI automation test case, and obtain the execution log; or, the log retrieval module 601 is specifically used to retrieve the logs generated by at least one tracking step after the execution of the UI automation test case is completed, and obtain the execution log.

[0146] In an optional embodiment of this disclosure, the log retrieval module 601 is further configured to poll and retrieve the logs generated by the execution of any tracking step until retrieval is successful, in the event that the retrieval of the logs generated by the execution of any tracking step fails, thereby obtaining the execution logs.

[0147] In an optional embodiment of this disclosure, the log retrieval module 601 is specifically used to receive the event tracking verification request sent when continuous integration is triggered; continuous integration is triggered when a predetermined event occurs, the predetermined event including any one of a test event, a release event, and a timed event; in response to the event tracking verification request, the execution log of the UI automation test case is obtained.

[0148] According to the automated event tracking verification device of this disclosure, the device can acquire the execution log of a UI automation test case, which contains event tracking steps pointing to corresponding steps within the UI automation test case, and the event tracking steps are mapped to event tracking requirement rules. The device determines the event tracking interval log corresponding to each event tracking step in the execution log, and performs event tracking verification on the event tracking interval log based on the event tracking requirement rules associated with the mapping relationship. Based on this, by mapping different event tracking steps in the UI automation test case to corresponding event tracking requirement rules, the event tracking interval log corresponding to each event tracking step can be extracted for corresponding automated event tracking verification. This eliminates the need for manual operation to generate event tracking logs and manual setting of conditions to filter required logs, thus improving the level of automation and the accuracy and efficiency of event tracking verification.

[0149] It should be noted that although several modules or units of the automated verification device for data embedding have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0150] Example Computer-Readable Storage Medium

[0151] The computer-readable storage medium of exemplary embodiments of the present disclosure will now be described.

[0152] In this exemplary embodiment, reference is made to FIG. 7 As shown, a program product 700 for implementing the above-described method according to an exemplary embodiment of the present disclosure is described. This product may be a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a device such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, a computer-readable storage medium may be any tangible medium that contains or stores a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0153] The program product 700 can employ any combination of one or more readable media. The readable media can be a readable signal medium or a computer-readable storage medium. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0154] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a computer-readable storage medium, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0155] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RE, etc., or any suitable combination thereof.

[0156] Program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (FAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0157] Example Electronic Device

[0158] refer to FIG. 8 An electronic device according to an exemplary embodiment of the present disclosure will be described.

[0159] FIG. 8 The electronic device 800 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0160] like FIG. 8 As shown, the electronic device 800 is presented in the form of a general-purpose computing device. The components of the electronic device 800 may include, but are not limited to: at least one processing unit 810, at least one storage unit 820, a bus 830 connecting different system components (including storage unit 820 and processing unit 810), and a display unit 840.

[0161] The storage unit stores program code, which can be executed by the processing unit 810 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure. For example, the processing unit 810 can perform actions such as... FIG. 1 The methods and steps shown are as follows.

[0162] Storage unit 820 may include volatile storage units, such as random access memory (RAM) 821 and / or cache memory 822, and may further include read-only memory (ROM) 823.

[0163] The storage unit 820 may also include a program / utility 824 having a set (at least one) of program modules 825, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0164] Bus 830 may include a data bus, an address bus, and a control bus.

[0165] Electronic device 800 can also communicate with one or more external devices 900 (e.g., keyboard, pointing device, Bluetooth device, etc.) via input / output (I / O) interface 850. Electronic device 800 also includes a display unit 840 connected to input / output (I / O) interface 850 for display purposes. Furthermore, electronic device 800 can communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 860. As shown, network adapter 860 communicates with other modules of electronic device 800 via bus 830. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0166] It should be noted that although several modules or sub-modules of the apparatus have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0167] Furthermore, although the operations of the methods disclosed herein are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0168] While the spirit and principles of this disclosure have been described with reference to several specific embodiments, it should be understood that this disclosure is not limited to the disclosed specific embodiments, and the division of aspects does not imply that features in these aspects cannot be combined for benefit; such division is merely for convenience of expression. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A method for automatic verification of a buried point, characterized in that, The method includes: Obtain the execution log of the UI automation test case, wherein the UI automation test case contains at least one tracking step, and each tracking step has a mapping relationship with the corresponding tracking requirement rule; The execution log determines the corresponding tracking interval log for each tracking step, and the tracking interval log is verified based on the tracking requirement rule associated with the mapping relationship.

2. The method of claim 1, wherein, The step of performing data tracking verification on the logs of the data tracking interval based on the data tracking requirement rules associated with the mapping relationship includes: The number of data points required is determined based on the data point requirement rules associated with the mapping relationship. The number of tracking points is verified based on the total number of tracking point data in the tracking point interval log and the number of tracking point requirements.

3. The method of claim 1, wherein, The step of performing data tracking verification on the logs of the data tracking interval based on the data tracking requirement rules associated with the mapping relationship includes: The repetition ratio of data collection points is determined based on the data collection point requirement rules associated with the mapping relationship. Obtain the event identifier of each event data point in the event tracking interval log, as well as the corresponding key and value; Determine the real-time repetition ratio of embedding points with the same key and value among at least two embedding point data with the same embedding point action identifier; The repetition of the data points is verified based on the real-time repetition ratio of the data points and the required repetition ratio of the data points.

4. The method of claim 1, wherein, Each of the aforementioned event tracking requirement rules has a unique index identifier. The mapping relationship is constructed between the event tracking step and the index identifier. The event tracking verification of the event tracking interval logs based on the event tracking requirement rules associated with the mapping relationship includes: The index identifier corresponding to the embedding step is determined based on the mapping relationship; The tracking requirement rules are retrieved from the tracking database based on the index identifier; the tracking database stores the index identifier and the corresponding tracking requirement rules. The event tracking is verified based on the event tracking requirement rules.

5. The method of claim 4, wherein, After retrieving the event tracking requirement rules from the event tracking database based on the index identifier, the process also includes: Upon receiving a rule update notification from the event tracking database, the updated event tracking requirement rules are retrieved from the event tracking database based on the index identifier; the rule update notification is sent by the event tracking database when the event tracking requirement rules are updated. The step of verifying the data entry points in the logs of the data entry point interval based on the data entry point requirement rules includes: The event tracking is verified based on the updated event tracking requirement rules for the event tracking interval logs.

6. The method of claim 1, wherein, The step of obtaining the execution logs of the UI automation test cases includes: During the execution of the steps in the UI automation use case, the logs generated by each of the aforementioned tracking steps are retrieved to obtain the execution logs; or, After the execution of the steps in the UI automation use case is completed, the logs generated by at least one of the instrumentation steps are retrieved to obtain the execution logs.

7. The method of claim 1, wherein, The step of obtaining the execution logs of the UI automation test cases includes: Receive the data entry verification request sent when continuous integration is triggered; the continuous integration is triggered when a predetermined event occurs, the predetermined event including any one of a test event, a release event, and a timed event; In response to the event tracking verification request, obtain the execution log of the UI automation test case.

8. A device for automatic verification of a buried point, characterized in that, The device includes: The log retrieval module is used to obtain the execution logs of UI automation test cases. The UI automation test cases contain at least one tracking step, and each tracking step has a mapping relationship with the corresponding tracking requirement rule. The event tracking verification module is used to determine the event tracking interval log corresponding to each event tracking step in the execution log, and to perform event tracking verification on the event tracking interval log based on the event tracking requirement rules associated with the mapping relationship.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that When the computer program is executed by the processor, it implements the automated verification method for data embedding according to any one of claims 1 to 7.

10. An electronic device, comprising: include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to execute the automated verification method for data entry points according to any one of claims 1 to 7 by executing the executable instructions.

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