A positioning method and device for feedback problems

Abstract

Embodiments of the present specification provide a positioning method and device for feedback problems, the method comprising: obtaining a first problem type corresponding to a first problem occurring in a target application, wherein the first problem type is determined based on problem feedback content uploaded by the target application for the first problem; based on a user identifier of a target user of the target application, obtaining a running data set of the target application from a running data management platform corresponding to the target application, the running data set including events triggered by the target application during the running process due to the operation of the target user; based on the first problem type and a preset correspondence relationship between a plurality of problem types and a plurality of event names of a plurality of events, determining a plurality of key event names corresponding to the first problem type; and based on the plurality of key event names and the running data set, determining a problem source corresponding to the first problem.

Description

Technical Field

[0001] This specification relates to the field of data processing technology, and in particular to a method and apparatus for locating feedback problems. Background Technology

[0002] With the development of internet technology, application software has become increasingly indispensable in people's lives. However, when users report problems during the operation of application software, how to enable developers to quickly locate the cause of the problem (usually a code problem) through user feedback has become an increasingly important issue.

[0003] Therefore, when problems occur during the operation of application software, it is crucial to help developers quickly locate the root cause of the problem. Summary of the Invention

[0004] This specification provides one or more embodiments of a method and apparatus for locating feedback problems, so as to locate the source of feedback problems.

[0005] Based on the first aspect, a method for locating feedback problems is provided, including:

[0006] Obtain the first problem type corresponding to the first problem that occurs in the target application, wherein the first problem type is determined based on the problem feedback content uploaded by the target application in response to the first problem;

[0007] Based on the user identifier of the target user of the target application, the runtime dataset of the target application is obtained from the runtime data management platform corresponding to the target application. The runtime dataset includes events triggered by the target user's operation during the operation of the target application.

[0008] Based on the first question type and the pre-defined correspondence between multiple question types and event names, determine several key event names corresponding to the first question type;

[0009] Based on the aforementioned key event names and the running dataset, the source of the problem corresponding to the first problem is determined.

[0010] According to the second aspect, a location device for feedback problems is provided, comprising:

[0011] The first acquisition module is configured to acquire a first problem type corresponding to a first problem that occurs in the target application, wherein the first problem type is determined based on the problem feedback content uploaded by the target application in response to the first problem;

[0012] The second acquisition module is configured to acquire the runtime dataset of the target application from the runtime data management platform corresponding to the target application based on the user identifier of the target user of the target application. The runtime dataset includes events triggered by the target user's operation during the operation of the target application.

[0013] The first determining module is configured to determine several key event names corresponding to the first problem type based on the first problem type and a preset correspondence between multiple problem types and event names of multiple events.

[0014] The second determining module is configured to determine the source of the problem corresponding to the first problem based on the several key event names and the running dataset.

[0015] According to a third aspect, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the method described in the first aspect.

[0016] According to a fourth aspect, an electronic device is provided, including a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, it implements the method described in the first aspect.

[0017] According to the method and apparatus provided in the embodiments of this specification, after obtaining the first problem type determined based on the problem feedback content uploaded by the target application in response to the first problem, based on the user identifier of the target user of the target application, the running data set formed by the target application during operation is obtained from the running data management platform corresponding to the target application. Then, based on the pre-set correspondence between multiple problem types and event names of multiple events, and the first problem type, several key event names corresponding to the first problem type are determined. Then, based on the several key event names and the running data set (including events triggered by the target user during the operation of the target application), the problem source corresponding to the first problem is determined, thereby realizing the automatic location of the problem source of the feedback problem. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0019] Figure 1 This is a schematic diagram illustrating the implementation framework of one embodiment disclosed in this specification;

[0020] Figure 2A flowchart illustrating a method for locating feedback problems provided in an embodiment;

[0021] Figure 3 A schematic block diagram of a location device for feedback problems provided in an embodiment;

[0022] Figure 4 This is a schematic block diagram of an electronic device provided for an embodiment. Detailed Implementation

[0023] The technical solutions of the embodiments of this specification will now be described in detail with reference to the accompanying drawings.

[0024] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0025] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0026] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0027] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0028] Currently, when problems occur during application software operation, in response to user feedback regarding these issues, relevant personnel must log into various operational data management platforms (such as log management platforms and / or event tracking platforms) based on user feedback and authorization. They must then input the user's identifier into each platform to retrieve the corresponding operational data. This data is then reviewed sequentially to determine if any anomalies exist. Finally, based on the identified anomalies, the developers are notified to perform application software maintenance.

[0029] For example, in one scenario, when the application software is client software developed using hybrid development technology that embeds a web page container (also known as an embedded browser) (i.e., the client software uses web pages as its presentation method), the relevant personnel of the application software need to obtain the corresponding runtime data from the runtime data management platforms corresponding to the client software and the embedded web page container, and then repeatedly check the runtime data of the client software and each front-end to check for any anomalies, and then identify the abnormal runtime data. The above process requires tedious and repeated logins to the runtime data management platform and anomaly checks on the runtime data in the runtime data management platform, which consumes a lot of manpower and is not efficient in locating problems.

[0030] Therefore, embodiments of this specification disclose a method and apparatus for locating feedback problems, so as to realize the automated location of the source of feedback problems, reduce the consumption of human resources in the problem location process, and improve the efficiency of problem location. Figure 1 The diagram illustrates an implementation scenario according to an embodiment disclosed in this specification. In this implementation scenario, the feedback problem localization system can provide a problem localization service for an application, which is a service to determine the source of problems that occur during the operation of the application.

[0031] In one implementation, the feedback issue localization system may include a target application, an issue feedback server, and an issue analysis server. The issue feedback server and the issue analysis server may be the same server or different servers. The issue localization process can be specifically described as follows:

[0032] If a target user encounters a problem while using the target application (hereinafter referred to as the first problem), they can provide feedback on this problem through the application's feedback function. Specifically, the target user can enter a description of the first problem through the application's feedback input interface.

[0033] In one implementation, after the target application encounters a first problem during operation, it can output a prompt message for the first problem. The target user can take a screenshot of the first problem (e.g., the prompt message for the first problem and / or the problem interface corresponding to the first problem) to obtain a problem feedback screenshot, which is then included in the problem feedback content.

[0034] After entering the issue feedback input interface, the target user can enter a description of the first issue, i.e., the issue text content. After the target user completes the issue text content, they can trigger the upload control for the issue text content. Correspondingly, the target application obtains the runtime data (the runtime data generated by the client part of the target application) stored locally on the device and includes it in the issue feedback content. Then, it requests authorization from the target user to upload the issue feedback content. Furthermore, the target user can also authorize the issue analysis server through the target application, so that the issue analysis server has the permission to obtain the runtime dataset of the target application based on the target user's user identifier.

[0035] Next, in one scenario, after obtaining authorization from the target user to upload feedback content, the target application, based on the target user's user identifier, uploads its feedback content regarding the first issue (including the target application's runtime data, the aforementioned feedback screenshots (if any), and the aforementioned issue text content) to the issue feedback server. Subsequently, the issue feedback server receives the feedback content corresponding to the target user's user identifier. On one hand, it can upload the target application's runtime data to the corresponding runtime data management platform; on the other hand, it uses the feedback screenshots and issue text content to execute the subsequent issue localization process.

[0036] In another scenario, the target application can upload the application's runtime data from the issue feedback, along with the target user's user ID, to the corresponding runtime data management platform. This allows the runtime data management platform to store the runtime data based on the target user's user ID. Subsequently, the issue feedback screenshot, issue text content, and the corresponding target user's user ID from the issue feedback content are uploaded to the issue feedback server.

[0037] After obtaining a screenshot of the problem feedback (if available) and the problem text content, the problem feedback server can determine the first problem type based on the problem text content. Specifically, the problem feedback server can perform word segmentation on the problem text content to obtain individual words. Then, based on the obtained word segments and the pre-defined correspondence between multiple problem types and multiple keywords, the problem type corresponding to the first problem is determined and designated as the first problem type.

[0038] The issue feedback server then sends the first issue type, the user identifier of the target user of the target application, and a screenshot of the issue feedback (if any) to the issue analysis server.

[0039] The problem analysis server obtains the first problem type corresponding to the first problem encountered by the target application, the user identifier of the target user of the target application, and a screenshot of the problem feedback (if any). Since the target user has been authorized, the problem analysis server can obtain the runtime dataset of the target application from the runtime data management platform corresponding to the target application based on the user identifier of the target user. This runtime dataset includes events triggered by the target user's operations on the target application during its operation.

[0040] The operational data management platform can store operational data generated by the target application during its operation within a preset time period, corresponding to the user's identifier. This preset time period can be set according to actual needs, such as the past week or the past N days. The operational dataset can include log datasets and / or event tracking datasets generated by the target application during its operation.

[0041] Understandably, the approach to troubleshooting issues in a target application (i.e., locating the root cause of the problem) is generally quite universal. For each type of problem, the cause can be determined and preliminarily located by examining specific events related to the target application. Correspondingly, the pre-defined data storage space of the problem analysis server can pre-store the mapping between multiple problem types and event names. These events can include log events and / or event tracking points related to the target application.

[0042] Accordingly, after the problem analysis server obtains the first problem type, it can read the correspondence between the preset problem types and the event names of multiple events from its corresponding preset data storage space. Based on the first problem type and the preset correspondence between the multiple problem types and the event names of multiple events, it determines several key event names corresponding to the first problem type. Then, based on the several key event names and the running dataset, it determines the problem source corresponding to the first problem.

[0043] In the above process, after obtaining the first problem type determined by the feedback content uploaded by the target application in response to the first problem, the runtime dataset generated by the target application during its operation is obtained from the runtime data management platform corresponding to the target application based on the user identifier of the target user of the target application. Then, based on the pre-defined correspondence between multiple problem types and event names, as well as the first problem type, several key event names corresponding to the first problem type are determined. Then, based on the several key event names and the runtime dataset (including events triggered by the target user during the operation of the target application), the source of the first problem is determined, thereby achieving automated location of the source of the feedback problem, reducing the manpower cost in the problem location process, and improving the efficiency of problem location.

[0044] The method and apparatus for locating feedback problems provided in this specification will be described in detail below with reference to specific embodiments.

[0045] Figure 2 A flowchart illustrating a feedback problem localization method in one embodiment of this specification is shown. This method can be implemented using a target program, which can be a problem analysis server in the aforementioned feedback problem localization system. This target program can be installed in an electronic device, which can be implemented using any device, equipment, platform, device cluster, etc., with computing and processing capabilities. Figure 2 As shown, the method includes the following steps:

[0046] In step S210, the first problem type corresponding to the first problem that occurred in the target application is obtained, wherein the first problem type is determined based on the problem feedback content uploaded by the target application in response to the first problem.

[0047] In one case, the target application can be any type of application. In one implementation, the arbitrary type of application can include client applications, web applications (such as browsers), and client applications that are embedded web containers (also known as embedded browsers) developed through hybrid development techniques.

[0048] Hybrid development can be understood as a development model that combines native (client-side) and HTML5 development technologies, leveraging their strengths to compensate for their weaknesses. The client-side code utilizes a WebView plugin or other frameworks to provide a container for HTML5 (the aforementioned webpage container). The main business logic and interface display on the client side are implemented using HTML5-related web technologies. In other words, this type of application uses web pages as its presentation method. This webpage container allows the application to display webpages using web technologies.

[0049] In one implementation, when a target user encounters a problem during the operation of the target application (hereinafter referred to as the first problem), the target user can provide feedback on the first problem through the problem feedback function provided by the target application. Specifically, the target user can trigger the "Problem Feedback" control provided on a designated interface of the target application. Correspondingly, the target application detects that the "Problem Feedback" control has been triggered and redirects to the problem feedback page.

[0050] In one implementation, the issue feedback page may display at least a "Feedback" control. Triggering the "Feedback" control will take you to the issue feedback input interface, where the target user can enter a description of the first issue, which will then be included in the issue feedback content.

[0051] In another implementation, the feedback page can also display several common types of reference questions and the question types to which each reference question belongs. Clicking on a reference question leads to a page displaying the answers to its corresponding FAQ (Frequently Asked Questions). When a target user clicks on a reference question, if the FAQ answer fails to resolve their initial problem, the user can continue to trigger the "Feedback" control to enter the feedback input interface. Here, the target application uses the question type of the reference question clicked by the target user as the reference question type and includes it in the feedback content.

[0052] Considering that the questions clicked by the target users are generally those that match the first question, the question type can help to initially classify the type of the first question, which can better help to determine the more accurate question type of the first question.

[0053] After the target user enters their description of the first problem (i.e., the problem text content) on the problem feedback input interface, they can trigger the upload control to upload the problem text content. Correspondingly, the target application obtains the runtime data (the runtime data generated by the client part of the target application) stored locally on the device and includes it in the problem feedback content. Then, it requests authorization from the target user to upload the problem feedback content. Furthermore, the target user can also authorize the problem analysis server through the target application, so that the problem analysis server has the permission to obtain the runtime dataset of the target application based on the target user's user identifier.

[0054] In one implementation, after the target application encounters a first problem during operation, it can output a prompt message for the first problem. The target user can take a screenshot of the first problem (e.g., the prompt message for the first problem and / or the corresponding problem interface) to obtain a problem feedback screenshot, which is then included in the problem feedback content. The prompt message for the first problem may include a descriptive description of the anticipated problem (e.g., connection failure, page missing, etc.).

[0055] Subsequently, in one scenario, the target application, corresponding to the target user's user identifier, uploads the feedback content obtained by the target application regarding the first issue (including the target application's runtime data, a reference issue type (if any), the aforementioned feedback screenshots (if any), and the aforementioned issue text content) to the issue feedback server. Afterward, the issue feedback server receives the feedback content corresponding to the target user's user identifier. On one hand, it can upload the target application's runtime data to the corresponding runtime data management platform, allowing the platform to store the target application's runtime data corresponding to the target user's user identifier. On the other hand, the issue feedback server uses the reference issue type, the aforementioned feedback screenshots, and the aforementioned issue text content to execute the subsequent issue localization process.

[0056] In another scenario, the target application can upload its runtime data from the issue feedback to the corresponding runtime data management platform, so that the runtime data management platform stores the runtime data corresponding to the target user's user identifier; then, the reference issue type, the aforementioned issue feedback screenshot, the aforementioned issue text content, and the corresponding target user's user identifier from the issue feedback content are uploaded to the issue feedback server.

[0057] After obtaining the reference question type (if any), question feedback screenshot (if any), and question text content, the question feedback server can, in one implementation, determine the first question type corresponding to the first question based on the question text content and the pre-defined correspondence between multiple question types and multiple keywords. Specifically, the question feedback server can perform word segmentation on the question text content to obtain each word, and then determine the first question type corresponding to the first question based on the obtained word segments and the pre-defined correspondence between multiple question types and multiple keywords.

[0058] For example, the pre-defined correspondence between multiple question types and multiple keywords includes the correspondence between keywords such as "cannot open" and "white screen" and question type 1. Accordingly, when the target application is a client application with an embedded web page container, the obtained word segments include words such as "cannot open" and "white screen". The first question type can be question type 1, which can be a question type that can represent that the first question belongs to a web page container (e.g., Webview).

[0059] If the obtained word segments include the pre-defined correspondence between multiple question types and multiple keywords, including the correspondence between keywords such as "crash" and question type 2, then the first question type is question type 2. Question type 2 can be a type that indicates the first question is related to client operation or to communication between the client and the front-end (or corresponding server). That is, the crash might be caused by a problem in the target application's client-side runtime logic, or it might be caused by the client receiving information containing incorrect parameters from a front-end (or server). Specifically, this can be determined through the target application's runtime dataset.

[0060] Accordingly, in one implementation, the feedback content includes the question text content describing the first question input by the target user, and the first question type is determined based on the question text content and the correspondence between multiple preset question types and multiple keywords.

[0061] In another implementation, the issue feedback server can determine the first issue type based on the issue text content and reference issue types. Specifically, the issue feedback server can use a preset issue type determination algorithm to determine the first issue type based on the issue text content and reference issue types. Here, the reference issue type is the issue type to which the issue selected by the target user from the reference issues provided by the target application belongs.

[0062] In one implementation, to ensure the accuracy of the problem type corresponding to the first problem, the problem feedback server can also send the aforementioned problem feedback content (and the first problem type) to the corresponding problem feedback client. The problem feedback client displays the problem feedback content (and the first problem type) so that staff can make a second determination of the problem type corresponding to the first problem, thereby better ensuring the accuracy of the problem type corresponding to the first problem.

[0063] After the issue feedback server determines the first issue type corresponding to the first issue, it can send the first issue type to the target program, which then obtains the first issue type. In another implementation, if the issue feedback server also obtains the aforementioned issue feedback screenshot, it can send the screenshot to the target program, which can then obtain the screenshot.

[0064] After the target program obtains the first problem type, in step S220, based on the user identifier of the target user, it retrieves the target application's runtime dataset from the runtime data management platform corresponding to the target application. The runtime dataset includes events triggered by the target user's actions during the target application's operation. It is understood that when the target user of the target application submits a problem report, they have authorized the target program, granting the target program the permission to retrieve the target application's runtime dataset from the runtime data management platform corresponding to the target application based on the target user's user identifier.

[0065] In one embodiment, the runtime dataset includes a log dataset and / or a tracking dataset. If the runtime dataset includes a log dataset, the event includes log events; if the runtime dataset includes a tracking dataset, the event includes tracking events. In one implementation, the log events in the log dataset may include technology-related events, such as log events characterizing whether a page of the target application was successfully opened. The tracking events in the tracking dataset may include business-related events, such as tracking events characterizing the exposure rate or number of times a page of the target application was opened.

[0066] In one embodiment, the target application is a client application with an embedded web page container that supports displaying web pages using web page technology on the target application.

[0067] Step S220 may include the following steps 11-12:

[0068] In step 11, the client runtime dataset is obtained from the first log management platform and / or the first event tracking management platform of the target application's client and added to the runtime dataset. The first log management platform may store a dataset of logs generated by the target application's client during operation within a preset first time period (referred to as the first log dataset for clarity). This first log dataset may include log events triggered by the target user's actions during client operation. The first event tracking management platform may store a dataset of event tracking generated by the target application's client during operation within the first time period (referred to as the first event tracking dataset for clarity). This first event tracking dataset may include event tracking triggered by the target user's actions during client operation. The first time period can be set according to actual needs, such as within the past week or within the past N days.

[0069] The target program can obtain the client runtime dataset (which may include the log dataset and / or event tracking dataset generated during the client's operation within a first time period) from the first log management platform and / or the first event tracking management platform of the target application's client, and include it in the runtime dataset.

[0070] In one implementation, log data from the target application's client can be initially stored locally on the device where the client resides, and then uploaded to the corresponding primary log management platform. Similarly, event tracking data from the target application's client can be uploaded to the corresponding primary event tracking management platform after the event is triggered. Understandably, the uploading of this data requires authorization from the target user.

[0071] In step 12, obtain the running datasets of each front-end from the second log management platform and / or the second event tracking management platform corresponding to each front-end of the web page container, and include them in the running dataset.

[0072] The target application can embed one or more web page containers. Different web page containers can correspond to different front-ends or the same front-end.

[0073] Each frontend's second log management platform can store a log dataset (referred to as the second log dataset for clarity) generated during the operation of the corresponding frontend involved in the target application within a preset second time period. This second log dataset can include log events triggered by the target user's actions during the operation of the corresponding frontend. Each frontend's second event tracking management platform can store an event tracking dataset (referred to as the second event tracking dataset for clarity) generated during the operation of the corresponding frontend involved in the target application within a preset second time period. This second event tracking dataset can include event tracking triggered by the target user's actions during the operation of the corresponding frontend. This second time period can be set according to actual needs, such as within the past week or within the past N days.

[0074] The target program can obtain the runtime datasets of each front-end from the second log management platform and / or the second event tracking management platform corresponding to each front-end of the web page container (which may include the log datasets and / or event tracking datasets generated during the operation of each front-end involved in the target application within the second time period) and include them in the runtime dataset.

[0075] In another embodiment, the target application is a pure client application. Step S220 may include the following step 13: In step 13, the client runtime dataset is obtained from the target application's client log management platform and / or client event tracking management platform and included in the runtime dataset. For a target application that is a pure client application, the client runtime dataset obtained by the target program may include the log dataset and / or event tracking dataset generated during the client's operation of the target application.

[0076] In this context, it can be understood that the term "pure client application" refers to a client application that does not have an embedded web page container, as opposed to a client application developed using hybrid development technology. This term does not have any other limiting meaning.

[0077] In another embodiment, the target application is a web application (e.g., a browser). Step S220 may include the following step 14: In step 14, obtain the runtime datasets of each front-end from the front-end log management platform and / or the front-end event tracking management platform involved in the target application, and include them in the runtime dataset. For a target application that is a web application, the runtime datasets of each front-end involved in the target application obtained by the target program may include the log datasets and / or event tracking datasets generated during the operation of each front-end involved in the target application.

[0078] Then, in step S230, based on the first problem type and the pre-defined correspondence between multiple problem types and event names, several key event names corresponding to the first problem type are determined.

[0079] Understandably, the approach to troubleshooting problems in a target application (i.e., locating the root cause of the problem) is generally quite universal. For each type of problem, the cause can be determined and preliminarily located by examining certain specific events related to the target application. Correspondingly, the target program's pre-defined data storage space can store the mapping between multiple problem types and multiple event names. These events can include log events and / or event tracking points related to the target application.

[0080] After the target program obtains the first problem type, it can match the first problem type with multiple problem types in the preset correspondence between multiple problem types and multiple event names. If the match is successful (that is, there is a problem type in the correspondence that corresponds to the first problem type), then the event name of the event corresponding to the problem type that successfully matches the first problem type in the preset correspondence between multiple problem types and multiple event names is determined as several key event names corresponding to the first problem type.

[0081] Next, in step S240, based on several key event names and the running dataset, the source of the first problem is determined. In this step, the target program can traverse the running dataset based on several key event names to determine whether the running dataset includes the key events corresponding to those key event names, and to determine the event parameters of the key events included in the running dataset. Combined with preset problem location rules, the source of the first problem is determined.

[0082] In one embodiment, considering the large amount of running data contained in the acquired running dataset, in order to reduce data processing consumption and improve the efficiency of locating feedback problems, step S240 may include the following steps 21-23:

[0083] In step 21, the time when the first problem occurred is determined.

[0084] In one implementation, step 21 may include: if the problem feedback content includes a screenshot of the problem feedback uploaded by the target user, the screenshot may carry the time at which the screenshot was taken. Accordingly, the target program can determine the occurrence time based on the time carried in the screenshot, wherein the screenshot is an image captured by the target user in response to the first problem (e.g., the prompt information of the first problem and / or the problem interface corresponding to the first problem). In this implementation, the time carried in the screenshot can be determined as the occurrence time of the first problem.

[0085] In another implementation, step 21 may include: if the problem feedback content does not include a screenshot of the problem feedback, determining the occurrence time based on the reporting time of the problem feedback content. In this implementation, the target program can obtain the reporting time of the problem feedback content from the aforementioned problem feedback platform, and then determine that reporting time as the occurrence time of the first problem.

[0086] Then, in step 22, based on the occurrence time, the target runtime subset corresponding to the occurrence time is determined from the runtime dataset. In this step, the target program can determine the time range corresponding to the occurrence time based on the occurrence time. The start time of this time range is the time corresponding to the third duration before the occurrence time, and the end time of this time range is the time corresponding to the fourth duration after the occurrence time. Then, the runtime data within the time range corresponding to the occurrence time is determined from the runtime dataset and included in the target runtime subset corresponding to the occurrence time. The third duration and the fourth duration can be the same or different, and can be set according to actual needs. For example, the third duration and the fourth duration can be the same, which is 15 minutes.

[0087] In step 23, based on several key event names and a subset of target runtime data, the source of the first problem is determined. In this step, the target program can traverse the subset of target runtime data based on several key event names to determine whether the subset includes the key events corresponding to those key event names, and to determine the event parameters of the key events included in the subset. Combined with preset problem location rules, the source of the first problem is determined. By determining the target subset of runtime data from the runtime dataset—that is, filtering out runtime data outside the aforementioned time range of occurrence time—the workload of traversing the runtime data can be reduced, which can, to some extent, reduce the consumption of the problem location process and improve location efficiency.

[0088] In one embodiment, step S240 may include the following steps 31-32: In step 31, based on several key event names, the running dataset is traversed to obtain the traversal result.

[0089] Understandably, the runtime dataset may include a log dataset and / or an event tracking dataset. The log dataset may include log events triggered by the target user during the runtime of the target application, and these log events include the corresponding event names and event parameters. The event tracking dataset may include event tracking events triggered by the target user during the runtime of the target application, and these event tracking events include the corresponding event names and event parameters.

[0090] The aforementioned key event names determined by the target program may include key log event names and / or key event tracking names. Correspondingly, if the runtime dataset includes both log datasets and event tracking datasets, the target program can traverse the runtime dataset based on the key event names, that is, traverse the runtime datasets obtained from each runtime data management platform corresponding to the target application (the log management platform and event tracking management platform of the target application's client, and / or the log management platform and event tracking management platform of each frontend involved in the target application) to obtain the traversal results.

[0091] Next, in step 32, based on the traversal results and the preset problem location rules, the source of the first problem is determined. The preset problem location rules include the problem location rules corresponding to the first problem type. These preset problem location rules may also include location rules corresponding to other problem types. After obtaining the traversal results, the target program can determine the source of the first problem based on the traversal results and the location rules corresponding to the first problem type in the preset problem location rules.

[0092] In one implementation, the localization rules corresponding to each problem type in the preset problem localization rules may include: information describing the specific problem source corresponding to the corresponding problem type when the event corresponding to the specified event name in the running dataset is missing, and / or information describing the specific problem source corresponding to the corresponding problem type when the event parameters (or the time interval between at least two events corresponding to specific event names) of the event corresponding to the specific event name in the running dataset are abnormal (e.g., do not conform to the preset normal range value).

[0093] In one embodiment, the target application is a client application with an embedded web page container that supports displaying web pages using web page technology on the target application.

[0094] Step 32 may specifically include: based on the problem location rules corresponding to the first problem type, if it is determined that the traversal result represents the key event corresponding to the first key event name among the missing key event names in the running dataset, then the problem source corresponding to the first problem is determined to be the client part of the target application.

[0095] For example, if the first problem type is a problem type that represents a problem related to a web page container (e.g., Webview), the source of the problem corresponding to the first problem may include: a problem of the client of the target application, or a problem of a certain front-end corresponding to the web page container embedded in the target application, or a problem of the network environment in which the target application is located.

[0096] The target program can search for the key events corresponding to each key event name during the process of traversing the running dataset. Based on the problem localization rules corresponding to the first problem type, if it is determined that the traversal result indicates that the running dataset is missing the key event corresponding to the first key event name (e.g., the client's webview_load_finish), that is, the target application's client did not report the event named webview_load_finish, then it can be considered that the target application's client Webview initialization process has not been completed. Accordingly, the source of the problem corresponding to the first problem is determined to be the client part of the target application.

[0097] In another embodiment, step 32 may specifically include: based on the problem location rules corresponding to the first problem type, if it is determined that the traversal result represents the key event corresponding to the second key event name among the missing key event names in the running dataset, then the problem source corresponding to the first problem is determined to be the front-end part corresponding to the web page container of the target application.

[0098] Continuing with the previous example, the target program can search for key events corresponding to each key event name while traversing the dataset. Based on the problem localization rules corresponding to the first problem type, if the traversal result indicates that the dataset is missing a key event corresponding to a second key event name (e.g., `window.onLoad` on the frontend), meaning that a frontend of the target application has not reported an event named `window.onLoad`, indicating a problem with the business logic of that frontend, then the source of the problem corresponding to the first problem is determined to be the frontend of the target application that did not report the event named `window.onLoad`. In one implementation, the corresponding frontend's JS error can also be determined based on the events corresponding to several key event names.

[0099] In another embodiment, step 32 may specifically include: based on the problem location rules corresponding to the first problem type, if it is determined that the traversal result represents the missing key event corresponding to the third key event name and / or the key event corresponding to the fourth key event name in the running dataset, or if it is determined that the traversal result represents the time interval between the key event corresponding to the third key event name and the key event corresponding to the fourth key event name exceeds a preset time threshold, then the problem source corresponding to the first problem is determined to be a network environment problem of the target application.

[0100] Following the previous example, the target program can search for the key events corresponding to each key event name during the process of traversing the running dataset. Based on the problem localization rules corresponding to the first problem type, if it is determined that the traversal result indicates that the running dataset is missing the key event corresponding to the third key event name (e.g., webview_tcp_start) and / or the key event corresponding to the fourth key event name (e.g., webview_dns_start), that is, the events with the event names webview_tcp_start and / or webview_dns_start were not successfully reported, it can be considered that the connection between the target application's client and the front end is interrupted (i.e., failed). Then it can be determined that the source of the problem corresponding to the first problem type is a problem with the network environment in which the target application is located, that is, the network signal in which the target application is located is poor, or there is a problem with the network operator's DNS / TCP.

[0101] If the traversal results indicate that the time interval between the critical event corresponding to the third critical event name (e.g., webview_tcp_start) and the critical event corresponding to the fourth critical event name (e.g., webview_dns_start) in the running dataset exceeds a preset time threshold, that is, both the event named webview_tcp_start and the event named webview_dns_start were successfully reported, but the time interval between their successful triggering exceeds the preset time threshold, it can be considered that the connection between the target application's client and the front end has timed out. Accordingly, it can be determined that the source of the problem corresponding to the first problem type is a problem with the network environment of the target application.

[0102] If the source of the problem corresponding to the first problem type is determined to be a network environment issue of the target application, then the occurrence of the first problem can be considered unrelated to the target application. In this case, the target application can be prompted to pay attention to its network environment. Correspondingly, the target application can output information prompting the target user to check the network of the device where the target application is located, so as to help the user solve the problem more quickly.

[0103] In one embodiment, the method may further include the following step: sending a prompt message to the developer corresponding to the aforementioned problem source. In this implementation, after determining the problem source corresponding to the first problem, a prompt message is sent to the developer corresponding to the problem source, prompting the developer to maintain and improve the client and / or frontend involved in the target application by referring to the corresponding runtime dataset. For example, if the problem source corresponding to the first problem is determined to be a problem involving the client of the target application, a prompt message is sent to the developer of the client involved in the target application, so that the developer of the client can maintain and improve the client involved in the target application by referring to the corresponding runtime dataset. This reduces the manpower cost of finding problems to a certain extent. In another implementation, the prompt message may also carry a first problem type and / or several key event names to better assist developers in identifying and improving problems.

[0104] In this embodiment, by combining user feedback regarding the first problem encountered by the target application, and with user authorization, the corresponding runtime datasets generated by the target application (its clients and / or front-ends) during the user's use of the target application can be obtained from the various runtime data management platforms corresponding to the target application. Then, based on the first problem type initially determined by the user feedback and the obtained runtime datasets, and according to the pre-defined correspondence between multiple problem types and event names, the source of the first problem can be automatically determined. This achieves automated location of the source of the reported problem, reduces the time and manpower costs consumed in the problem location process to a certain extent, and further improves the problem-solving efficiency of the target application.

[0105] The foregoing description describes specific embodiments of this specification; other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than those shown in the embodiments, and the desired result may still be achieved. Furthermore, the processes depicted in the drawings do not necessarily need to follow the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0106] Corresponding to the above method embodiments, this specification provides a feedback problem location device 300, the schematic block diagram of which is shown below. Figure 3 As shown, it includes:

[0107] The first acquisition module 310 is configured to acquire a first problem type corresponding to a first problem that occurs in the target application, wherein the first problem type is determined based on the problem feedback content uploaded by the target application in response to the first problem;

[0108] The second acquisition module 320 is configured to acquire the runtime dataset of the target application from the runtime data management platform corresponding to the target application based on the user identifier of the target user of the target application. The runtime dataset includes events triggered by the target user's operation during the operation of the target application.

[0109] The first determining module 330 is configured to determine several key event names corresponding to the first problem type based on the first problem type and the preset correspondence between multiple problem types and event names of multiple events.

[0110] The second determining module 340 is configured to determine the source of the problem corresponding to the first problem based on the several key event names and the running dataset.

[0111] In one optional implementation, the problem feedback content includes the problem text content described by the target user, and the first problem type is determined based on the problem text content and the correspondence between a plurality of preset problem types and a plurality of keywords.

[0112] In one optional implementation, the problem feedback content further includes: a reference problem type, which is the problem type to which the problem selected by the target user from the reference problems provided by the target application belongs; the first problem type is determined based on the problem text content and the reference problem type.

[0113] In one alternative implementation, the runtime dataset includes a log dataset and / or a tracking dataset; if the runtime dataset includes a log dataset, the events include log events; if the runtime dataset includes a tracking dataset, the events include tracking events.

[0114] In one alternative implementation, the target application is a client application with an embedded web page container, the web page container supporting the display of web pages using web page technology on the target application;

[0115] The second acquisition module 320 is specifically configured to acquire the client running dataset from the first log management platform and / or the first tracking point management platform of the target application's client and include it in the running dataset;

[0116] Obtain the runtime datasets of each frontend from the second log management platform and / or the second event tracking platform corresponding to each frontend of the web page container, and include them in the runtime datasets.

[0117] In one alternative embodiment, the second determining module 340 includes:

[0118] The first determining unit (not shown in the figure) is configured to determine the occurrence time of the first problem;

[0119] The second determining unit (not shown in the figure) is configured to determine, based on the occurrence time, a target subset of running data corresponding to the occurrence time from the running dataset;

[0120] The third determining unit (not shown in the figure) is configured to determine the source of the problem corresponding to the first problem based on the names of the several key events and the target runtime data subset.

[0121] In one optional implementation, the first determining unit is specifically configured to determine the occurrence time based on the time carried in the problem feedback screenshot if the problem feedback content includes a problem feedback screenshot uploaded by the target user, wherein the problem feedback screenshot is an image captured by the target user in response to the prompt information of the first problem;

[0122] If the problem feedback content does not include the problem feedback screenshot, the occurrence time is determined based on the reporting time of the problem feedback content.

[0123] In one alternative embodiment, the second determining module 340 includes:

[0124] The traversal unit (not shown in the figure) is configured to traverse the running dataset based on the aforementioned key event names to obtain the traversal results;

[0125] The fourth determining unit (not shown in the figure) is configured to determine the source of the first problem based on the traversal results and the preset problem location rules, wherein the preset problem location rules include the problem location rules corresponding to the first problem type.

[0126] In one alternative implementation, the target application is a client application with an embedded web page container, the web page container supporting the display of web pages using web page technology on the target application;

[0127] The fourth determining unit is specifically configured to, based on the problem location rules corresponding to the first problem type, determine that if the traversal result indicates that the running dataset is missing the key event corresponding to the first key event name among the several key event names, then determine that the source of the problem corresponding to the first problem is the client part of the target application.

[0128] In an optional implementation, the fourth determining unit is further configured to, based on the problem location rules corresponding to the first problem type, determine that if the traversal result indicates that the running dataset is missing the key event corresponding to the second key event name among the several key event names, the problem source corresponding to the first problem is the front-end part corresponding to the webpage container of the target application.

[0129] In an optional implementation, the fourth determining unit is further configured to, based on the problem location rules corresponding to the first problem type, determine that the source of the problem corresponding to the first problem is a network environment problem of the target application, if the traversal result indicates that the running dataset is missing the key event corresponding to the third key event name and / or the key event corresponding to the fourth key event name among the several key event names, or if the traversal result indicates that the time interval between the key event corresponding to the third key event name and the key event corresponding to the fourth key event name exceeds a preset time threshold.

[0130] The above-described apparatus embodiments correspond to the method embodiments, and detailed descriptions can be found in the description of the method embodiments section, which will not be repeated here. The apparatus embodiments are derived based on the corresponding method embodiments and have the same technical effects as the corresponding method embodiments; detailed descriptions can be found in the corresponding method embodiments.

[0131] The following is for reference. Figure 4 It shows a schematic diagram of the structure of an electronic device 400 suitable for implementing the embodiments of this specification. Figure 4 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments described in this specification.

[0132] like Figure 4 As shown, electronic device 400 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 401, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 402 or a program loaded from storage device 408 into random access memory (RAM) 403. RAM 403 also stores various programs and data required for the operation of electronic device 400. Processing device 401, ROM 402, and RAM 403 are interconnected via bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0133] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows electronic device 400 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 An electronic device 400 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 4 Each box shown can represent a device or multiple devices as needed.

[0134] In particular, according to embodiments of this specification, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this specification include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 409, or installed from storage device 408, or installed from ROM 402. When the computer program is executed by processing device 401, it performs the functions defined in the methods of embodiments of this specification.

[0135] This specification also provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the feedback problem localization method provided in this specification.

[0136] It should be noted that the computer-readable medium described in the embodiments of this specification may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the embodiments of this specification, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the embodiments of this specification, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-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 computer-readable signal medium may be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (Radio Frequency), etc., or any suitable combination thereof.

[0137] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: obtain a first problem type corresponding to a first problem encountered by the target application, wherein the first problem type is determined based on the problem feedback content uploaded by the target application regarding the first problem; obtain the runtime dataset of the target application from the runtime data management platform corresponding to the target application based on the user identifier of the target user of the target application, the runtime dataset including events triggered by the target user during the operation of the target application; determine several key event names corresponding to the first problem type based on the first problem type and a preset correspondence between multiple problem types and event names; and determine the problem source corresponding to the first problem based on the several key event names and the runtime dataset.

[0138] Computer program code for performing the operations of the embodiments of this specification can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0139] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments for storage media and computing devices are basically similar to the method embodiments, so they are described more simply; relevant parts can be referred to the descriptions of the method embodiments.

[0140] Those skilled in the art will recognize that the functions described in the embodiments of the present invention in one or more of the above examples can be implemented using hardware, software, firmware, or any combination thereof. When implemented in software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium.

[0141] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, or improvements made based on the technical solutions of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for locating feedback problems, comprising: Obtain the first problem type corresponding to the first problem that occurs in the target application, wherein the first problem type is determined based on the problem feedback content uploaded by the target application in response to the first problem; the target application is a client application with an embedded web page container, and the web page container supports displaying web pages on the target application using web page technology; Based on the user identifier of the target user of the target application, the runtime dataset of the target application is obtained from the runtime data management platform corresponding to the client of the target application and each front-end of the web page container. The runtime dataset includes events triggered by the target user's operation during the operation of the target application. Based on the first question type and the pre-defined correspondence between multiple question types and event names, determine several key event names corresponding to the first question type; Based on the aforementioned key event names and the running dataset, the source of the problem corresponding to the first problem is determined, wherein the source of the problem includes at least one of the following: the client part of the target application, the front-end part corresponding to the web page container, and the network environment in which the target application is located; The step of determining the source of the first problem based on the plurality of key event names and the running dataset includes: traversing the running dataset based on the plurality of key event names to obtain traversal results; determining the source of the first problem based on the traversal results and preset problem location rules, wherein the preset problem location rules include problem location rules corresponding to a first problem type; the step of determining the source of the first problem based on the traversal results and preset problem location rules includes: based on the problem location rules corresponding to the first problem type, if it is determined that the traversal results indicate that the running dataset is missing a key event corresponding to the first key event name among the plurality of key event names, then the source of the first problem is determined to be the client part of the target application.

2. The method as described in claim 1, wherein, The feedback content includes the question text content describing the first question input by the target user. The first question type is determined based on the question text content and the correspondence between multiple preset question types and multiple keywords.

3. The method as described in claim 1, wherein, The problem feedback content also includes: a reference problem type, which is the problem type to which the problem selected by the target user from the reference problems provided by the target application belongs; the first problem type is determined based on the problem text content and the reference problem type.

4. The method of claim 1, wherein, The runtime dataset includes a log dataset and / or a tracking dataset. If the runtime dataset includes a log dataset, the events include log events; if the runtime dataset includes a tracking dataset, the events include tracking events.

5. The method of claim 4, wherein, The step of obtaining the runtime dataset of the target application from the runtime data management platform corresponding to each front-end of the target application's client and the webpage container includes: Obtain the client runtime dataset from the first log management platform and / or the first event tracking management platform of the target application's client, and include it in the runtime dataset; Obtain the running datasets of each frontend from the second log management platform and / or the second event tracking platform corresponding to each frontend of the web page container, and include them in the running datasets.

6. The method of claim 1, wherein, The process of determining the source of the first problem based on the aforementioned key event names and the running dataset includes: Determine when the first problem occurred; Based on the occurrence time, a target subset of running data corresponding to the occurrence time is determined from the running dataset; Based on the aforementioned key event names and the target runtime data subset, the source of the problem corresponding to the first problem is determined.

7. The method of claim 6, wherein, Determining the time of occurrence of the first problem includes: If the problem feedback content includes a screenshot of the problem feedback uploaded by the target user, then the occurrence time is determined based on the time carried by the problem feedback screenshot, wherein the problem feedback screenshot is an image captured by the target user in response to the first problem; If the problem feedback content does not include the problem feedback screenshot, the occurrence time is determined based on the reporting time of the problem feedback content.

8. The method of claim 1, further comprising: Based on the problem location rules corresponding to the first problem type, if it is determined that the traversal result represents the missing key event corresponding to the second key event name among the several key event names in the running dataset, then the problem source corresponding to the first problem is determined to be the front-end part corresponding to the web page container of the target application.

9. The method of claim 1, further comprising: Based on the problem location rules corresponding to the first problem type, if it is determined that the traversal result indicates that the running dataset is missing the key event corresponding to the third key event name and / or the key event corresponding to the fourth key event name among the several key event names, or if it is determined that the traversal result indicates that the time interval between the key event corresponding to the third key event name and the key event corresponding to the fourth key event name exceeds a preset time threshold, then the problem source corresponding to the first problem is determined to be a network environment problem of the target application.

10. The method of claim 1, further comprising: Based on the source of the problem, a notification message is sent to the developer corresponding to that source.

11. A device for locating feedback problems, comprising: The first acquisition module is configured to acquire a first problem type corresponding to a first problem that occurs in the target application, wherein the first problem type is determined based on the problem feedback content uploaded by the target application in response to the first problem; the target application is a client application with an embedded web page container, and the web page container supports displaying web pages on the target application using web page technology; The second acquisition module is configured to acquire the runtime dataset of the target application from the runtime data management platform corresponding to the client of the target application and each front-end of the web page container based on the user identifier of the target user of the target application. The runtime dataset includes events triggered by the target user's operation during the operation of the target application. The first determining module is configured to determine several key event names corresponding to the first problem type based on the first problem type and a preset correspondence between multiple problem types and event names of multiple events. The second determining module is configured to determine the source of the problem corresponding to the first problem based on the several key event names and the running dataset, wherein the source of the problem includes at least one of the following: the client part of the target application, the front-end part corresponding to the web page container, and the network environment in which the target application is located; The step of determining the source of the first problem based on the plurality of key event names and the running dataset includes: traversing the running dataset based on the plurality of key event names to obtain traversal results; determining the source of the first problem based on the traversal results and preset problem location rules, wherein the preset problem location rules include problem location rules corresponding to a first problem type; the step of determining the source of the first problem based on the traversal results and preset problem location rules includes: based on the problem location rules corresponding to the first problem type, if it is determined that the traversal results indicate that the running dataset is missing a key event corresponding to the first key event name among the plurality of key event names, then the source of the first problem is determined to be the client part of the target application.

12. An electronic device comprising a memory and a processor, wherein, The memory stores executable code, and when the processor executes the executable code, it implements the method of any one of claims 1-10.

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