Data processing method, device, electronic device and storage device

Abstract

The present application discloses a data processing method, including: obtaining link data generated by executing a target use case; obtaining a basic feature set of failure attribution of the target use case based on the link data; obtaining the failure experience attribution of the target use case based on the basic feature set of failure attribution of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library, and the use case portrait includes a basic feature set of failure attribution and failure experience attribution; storing the failure experience attribution of the target use case and the basic feature set of failure attribution of the target use case as the use case portrait of the target use case in the use case portrait library. The above method is used to solve the problem of the difficulty in troubleshooting difficult use cases in the prior art.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a data processing method, apparatus, electronic device and storage device. Background Art

[0002] In functional testing, each project must go through the use case regression phase before going online. Once a use case fails, troubleshooting is often time-consuming and laborious. R&D personnel need to spend a lot of energy to locate problems in each link. They need to troubleshoot multiple links such as the test environment, the impact of code modifications, the stability of external dependencies, and test data pollution. The entire troubleshooting process relies on manual experience.

[0003] Under the existing technology, the debug system uses rule matching to perform attribution display, that is, by collecting the required data to match the qualified rules in the rule library, so as to determine the cause of failure.

[0004] The prior art has the following disadvantages:

[0005] 1. Simple rule matching methods can often only provide basic judgments, and are not effective for more complex scenarios, so they still need to rely on manual experience for troubleshooting.

[0006] 2. Since the troubleshooting process and results of each time are independent and the troubleshooting experience is not accumulated, when troubleshooting difficult use cases, it often depends on whether the R&D personnel are experienced. If newcomers take over the application, they will have no idea where to start when faced with new problems, which increases the difficulty of troubleshooting. Summary of the invention

[0007] The present application provides a data processing method, apparatus, electronic device and storage device to solve the problem of the difficulty in troubleshooting difficult use cases in the prior art.

[0008] The present application provides a data processing method, comprising:

[0009] Get the link data generated by executing the target use case;

[0010] According to the link data, a basic feature set of failure attribution of a target use case is obtained;

[0011] Obtaining the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library, and the use case portrait includes the failure attribution basic feature set and the failure experience attribution;

[0012] The failure experience attribution of the target use case and the failure attribution basic feature set of the target use case are stored in a use case portrait library as a use case portrait of the target use case.

[0013] Optionally, obtaining the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library includes:

[0014] Obtain a failure attribution recommendation list for the target use case based on the failure attribution basic feature set of the target use case and the use case portraits of historical failed use cases obtained from the use case portrait library;

[0015] According to the failure attribution recommendation list of the target use case, the failure experience attribution of the target use case is obtained.

[0016] Optionally, obtaining a failure attribution recommendation list for the target use case based on the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library includes:

[0017] Obtaining a use case portrait distance between the target use case and the historical failure use case based on the failure attribution basic feature set of the target use case and the failure attribution basic feature set of the historical failure use case obtained from the use case portrait library;

[0018] Based on the use case profile distance, obtain a recommended list of failure attribution for the target use case.

[0019] Optionally, obtaining the use case portrait distance between the target use case and the historical failure use case based on the failure attribution basic feature set of the target use case and the failure attribution basic feature set of the historical failure use case obtained from the use case portrait library includes:

[0020] According to the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of the target use case, and the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of historical failure use cases obtained from the use case portrait library, the use case portrait distance between the target use case and the historical failure use case is obtained.

[0021] Optionally, obtaining a failure attribution recommendation list of a target use case based on the use case profile distance includes:

[0022] Sort the use case profile distances from small to large;

[0023] Obtain the target historical failed use cases corresponding to the use case profile distances within a preset number of order;

[0024] Obtaining the failure attribution similarity between the target use case and the target historical failure use case according to the use case profile distance between the target historical failure use case and the target use case;

[0025] According to the failure attribution similarity, a recommended list of failure attribution for the target use case is obtained.

[0026] Optionally, obtaining the failure attribution similarity between the target use case and the target historical failure use case according to the use case portrait distance between the target historical failure use case and the target use case includes:

[0027] The failure attribution similarity between the target use case and the target historical failure case is obtained based on the use case portrait distance between the target historical failure use case and the target use case, the failure attribution basic features included in the failure attribution basic feature set of the target use case, and the weights of the failure attribution basic features.

[0028] Optionally, obtaining the failure experience attribution of the target use case according to the failure attribution recommendation list includes:

[0029] Receive evaluation feedback results for failure attribution of a target use case in the failure attribution recommendation list;

[0030] According to the evaluation feedback results, the failure experience attribution of the target use case is obtained.

[0031] Optionally, based on the evaluation feedback result, the failure experience attribution of the target use case is obtained, including:

[0032] Formatting and normalizing the evaluation feedback results;

[0033] Feature extraction is performed on the evaluation feedback results after formatting and normalization to obtain the failure experience attribution of the target use case.

[0034] The present application also provides a data processing device, comprising:

[0035] A link data acquisition unit, used to acquire link data generated by executing a target use case;

[0036] A failure attribution basic feature set obtaining unit, used to obtain a failure attribution basic feature set of a target use case according to the link data;

[0037] A failure experience attribution obtaining unit, used to obtain the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library; the use case portrait includes the failure attribution basic feature set and the failure experience attribution;

[0038] The attribution storage unit is used to store the failure experience attribution of the target use case and the failure attribution basic feature set of the target use case into the use case portrait library.

[0039] The present application also provides an electronic device, comprising:

[0040] processor;

[0041] The memory is used to store a program of the data processing method. After the device is powered on and the program of the data processing method is run by the processor, the following steps are performed:

[0042] Get the link data generated by executing the target use case;

[0043] According to the link data, a basic feature set of failure attribution of a target use case is obtained;

[0044] Obtaining the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library, and the use case portrait includes the failure attribution basic feature set and the failure experience attribution;

[0045] The failure experience attribution of the target use case and the failure attribution basic feature set of the target use case are stored in a use case portrait library as a use case portrait of the target use case.

[0046] The present application also provides a storage device storing a program of a data processing method, wherein the program is executed by a processor to perform the following steps:

[0047] Get the link data generated by executing the target use case;

[0048] According to the link data, a basic feature set of failure attribution of a target use case is obtained;

[0049] Obtaining the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library, and the use case portrait includes the failure attribution basic feature set and the failure experience attribution;

[0050] The failure experience attribution of the target use case and the failure attribution basic feature set of the target use case are stored in a use case portrait library as a use case portrait of the target use case.

[0051] Compared with the prior art, this application has the following advantages:

[0052] The present application provides a data processing method, which obtains the failure experience attribution of the target use case based on the basic feature set of the failure attribution of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; the failure experience attribution of the target use case and the basic feature set of the failure attribution of the target use case are stored in the use case portrait library as the use case portrait of the target use case. The data processing method provided by the present application combines the use case portrait of the historical failed use case when obtaining the failure experience attribution of the target use case, so that the obtained failure experience attribution is more accurate and the speed of troubleshooting difficult use cases is accelerated; in addition, the failure experience attribution of the target use case and the basic feature set of the failure attribution of the target use case are stored in the use case portrait library as the use case portrait of the target use case, and by establishing a use case portrait method, each troubleshooting result and troubleshooting experience are recorded and associated, which provides a reference for subsequent problem troubleshooting and reduces the difficulty of problem troubleshooting. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flowchart of a data processing method provided in the first embodiment of the present application.

[0054] Figure 2 It is a schematic diagram of a scenario for implementing the first embodiment of the present application.

[0055] Figure 3 It is a schematic diagram of a data processing device provided in the first embodiment of the present application.

[0056] Figure 4 It is a schematic diagram of an electronic device provided in the first embodiment of the present application. DETAILED DESCRIPTION

[0057] Many specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present invention, so the present invention is not limited to the specific implementation disclosed below.

[0058] The first embodiment of the present application provides a data processing method. Figure 1 Provide explanation.

[0059] like Figure 1 As shown, in step S101, link data generated by executing the target use case is obtained.

[0060] This step provides the prerequisite for obtaining the basic feature set of failure attribution for the target use case by acquiring link data.

[0061] The target use case refers to a failure use case for which a basic feature set of failure attribution and failure experience attribution need to be obtained.

[0062] When the result of a test case is different from the expected data after execution, it means that this test case is a failed case. For example, when testing an application, a normal test case is to send a request to obtain a price adjustment discount for a certain product. Under normal circumstances, the discount information obtained is certain, but in a certain online version, the discount information returned is abnormal. This means that this test case is a failed case. When a test case fails to execute, it is necessary to analyze the cause of its failure, that is, to perform failure attribution analysis on the failed case.

[0063] In specific implementation, the link data generated by executing the target use case can be obtained by collecting link data during the execution of the target use case. Figure 2 The system collects link data. Figure 2 As shown, in step 1, the user inputs the target use case into the use case execution module, and the use case execution module executes the target use case. In step 2, the link data collection module collects the basic data of the entire link. The collected data may include: test environment information, execution process data, result data collection, whether it is a main use case, etc.

[0064] A. Test environment information

[0065] In order to detect whether there is a problem with the test environment, if there is a problem, it will cause this request to be abnormal, which will naturally cause abnormal execution results.

[0066] B. Execution process data

[0067] That is, the system needs to detect whether there is any abnormality in the link from test data preparation to sending requests, to obtaining returns, and then to executing verification during the execution process, and whether it may be a problem with the test platform itself.

[0068] C. Result Data Collection

[0069] Includes: coredump file exception log, benchmark configuration (such as the address of other applications to be accessed, the number of execution threads, etc.).

[0070] D. Is it a main use case

[0071] If the target use case to be executed is a non-mainline use case, it may also be written in code branch 1. Since code branch 1 has not been merged into the mainline version, and code branch 2 of the target use case may not contain the functions of code branch 1, the target use case will also fail.

[0072] like Figure 1 As shown, in step S102, a failure attribution basic feature set of a target use case is obtained according to the link data.

[0073] The failure attribution basic feature set includes the basic attribution of the target use case and the failure features extracted according to the generated link data.

[0074] After collecting link data, the collected link data can be attributed and matched to obtain the basic attribution of the target use case, such as the appearance of coredump files, branch use cases, test environment service anomalies, execution process anomalies, abnormal logs of the tested application, differences between configuration files and the baseline environment, etc. It is also possible to extract features from the basic attribution and the collected link data to obtain failure features. The basic attribution and failure features of the target use case form the basic feature set of failure attribution of the target use case, and then store the basic feature set of failure attribution of the target use case in the use case portrait library for experience precipitation.

[0075] In specific implementation, the Jieba word segmentation algorithm can be used to perform natural language processing on the basic attribution and collected link data to obtain failure features.

[0076] like Figure 2 As shown, in step 3, basic attribution and failure features are obtained according to the collected link data, and a failure attribution basic feature set is generated.

[0077] like Figure 1 As shown, in step S103, the failure experience attribution of the target use case is obtained based on the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library.

[0078] The use case portrait may refer to a portrait drawn by integrating all historical data of failed use cases, which can describe the past and present of the failed use case. The use case portrait includes a basic feature set of failure attribution and failure experience attribution. The role of the use case portrait includes: according to the failure experience attribution included in the use case portrait, obtaining the improvement plan corresponding to the failure experience attribution and providing the improvement plan to the user; or directly prompting the possible failure attribution and providing the corresponding improvement plan to the user when a similar use case appears next time.

[0079] The failure experience attribution may refer to the failure attribution of the target use case obtained based on the failure experience attribution of the historical failed use cases and the failure attribution basic feature set of the target use case.

[0080] The step of obtaining the failure experience attribution of the target use case based on the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library includes:

[0081] Obtain a failure attribution recommendation list for the target use case based on the failure attribution basic feature set of the target use case and the use case portraits of historical failed use cases obtained from the use case portrait library;

[0082] According to the failure attribution recommendation list of the target use case, the failure experience attribution of the target use case is obtained.

[0083] After obtaining the basic feature set of failure attribution of the target use case, the failure experience attribution of the target use case can be obtained by combining the use case portraits of historical failed use cases obtained from the use case portrait library.

[0084] The step of obtaining a failure attribution recommendation list for the target use case based on the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library includes:

[0085] According to the failure attribution basic feature set of the target use case and the failure attribution basic feature set of the historical failed use cases obtained from the use case portrait library, the use case portrait distance between the target use case and the historical failed use cases in the use case portrait library is obtained;

[0086] Based on the use case profile distance, obtain a recommended list of failure attribution for the target use case.

[0087] The use case profile distance may refer to a weighted Euclidean distance, which refers to the real distance between two points in an m-dimensional space, or the natural length of a vector (i.e., the distance from the point to the origin).

[0088] The obtaining, based on the failure attribution basic feature set of the target use case and the failure attribution basic feature set of the historical failed use cases obtained from the use case portrait library, the use case portrait distance between the target use case and the historical failed use cases includes:

[0089] According to the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of the target use case, and the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of historical failure use cases obtained from the use case portrait library, the use case portrait distance between the target use case and the historical failure use case is obtained.

[0090] The failure attribution recommendation list of the target use case is obtained according to the use case portrait distance, including:

[0091] Sort the use case profile distances from small to large;

[0092] Obtain the target historical failed use cases corresponding to the use case profile distances within a preset number of order;

[0093] Obtaining the failure attribution similarity between the target use case and the target historical failure use case according to the use case profile distance between the target historical failure use case and the target use case;

[0094] Obtain a failure attribution recommendation list for the target use case according to the failure attribution similarity.

[0095] Since the smaller the use case portrait distance between two use cases indicates that the failure attributions between the two use cases are closer, therefore, taking the failure experience attribution of the historical failed use cases corresponding to the use case portrait distances with small use case portrait distances as the recommended failure attributions can make the obtained failure attributions of the target use case more accurate.

[0096] For example, if there are use case portraits of 5 historical failed use cases in the use case portrait library, namely use case portrait 1, use case portrait 2, use case portrait 3, use case portrait 4, and use case portrait 5, the use case portrait distance between use case portrait 1 and the target use case is d1, the use case portrait distance between use case portrait 2 and the target use case is d2, the use case portrait distance between use case portrait 3 and the target use case is d3, the use case portrait distance between use case portrait 4 and the target use case is d4, and the use case portrait distance between use case portrait 5 and the target use case is d5, and d1 < d3 < d5 < d2 < d4, then the historical failed use cases with the top 3 use case portrait distances can be used as the target historical failed use cases, that is, the target historical failed use cases include historical failed use case 1, historical failed use case 3, and historical failed use case 5.

[0097] In order to facilitate users to view the failure attribution recommendation list during manual feedback, first obtain the failure attribution similarity between the target use case and the target historical failed use case according to the use case portrait distance between the target historical failed use case and the target use case; then obtain the failure attribution recommendation list of the target use case according to the failure attribution similarity.

[0098] Specifically, the failure attribution similarity between the target use case and the target historical failed use case can be obtained according to the use case portrait distance between the target historical failed use case and the target use case, the failure attribution basic features included in the failure attribution basic feature set of the target use case, the failure attribution basic features included in the failure attribution basic feature set of the target historical failed use case, and the weights of the failure attribution basic features.

[0099] The failure attribution similarity between the target use case and the historical failed use cases in the use case portrait library is shown as follows:

[0100] Target use case x Use case 1 (failed to execute at time A) => Similarity 0.7

[0101] Target use case x Use case 2 (failed to execute at time A) => Similarity 0.22

[0102] Among them, both use case 1 and use case 2 are historical failed use cases.

[0103] Such as Figure 2As shown, in step 4, the failure attribution similarity between the target use case and the historical failure use cases is calculated, and in step 5, a failure attribution recommendation list of the target use case is obtained based on the failure attribution similarity.

[0104] Obtaining the failure experience attribution of the target use case according to the failure attribution recommendation list includes:

[0105] Receive evaluation feedback results for failure attribution of a target use case in the failure attribution recommendation list;

[0106] According to the evaluation feedback results, the failure experience attribution is obtained.

[0107] In the specific implementation, the evaluation feedback results can be conducted through a manual feedback mechanism or a feedback mechanism based on machine learning modeling. Since the machine learning closed loop cannot solve the human troubleshooting experience, the feedback mechanism based on machine learning modeling can only be applied to certain simple scenarios.

[0108] Users rate the failure attributions given by the system, that is, give useful or useless evaluations. These feedback results will be attributed to key-value features and recorded in the use case portrait, so as to change the weight and provide more accurate adjustments for the next recommendation ranking.

[0109] like Figure 2 As shown, in step 6, after obtaining the failure attribution recommendation list, the user can evaluate and feedback the failure attribution in the failure attribution recommendation list, and feed back the feedback result to the system.

[0110] According to the evaluation feedback results, the failure experience attribution is obtained, including:

[0111] Formatting and normalizing the evaluation feedback results;

[0112] Feature extraction is performed on the evaluation feedback results after formatting and normalization to obtain the failure experience attribution.

[0113] The system collects evaluation feedback results, formats and normalizes the feedback results, and then extracts features from the formatted and normalized evaluation feedback results to obtain failure experience attribution.

[0114] Formatting refers to processing input data into a standard format, such as processing a text into a JSON structure with relevant information: input data, description, weight, primary key, and value.

[0115] Normalization is a way to simplify data. For example, if the data value range is very large, it will eventually be normalized to the range of [0,1] in order to perform weight processing and facilitate calculation.

[0116] like Figure 1 As shown, in step S104, the failure experience attribution of the target use case and the failure attribution basic feature set of the target use case are stored in a use case portrait library as a use case portrait of the target use case.

[0117] It should be noted that the failure attribution basic feature set of the target use case can be stored in the use case portrait library in this step, or it can be stored in the use case portrait library after the failure attribution basic feature set of the target use case is obtained.

[0118] like Figure 2 As shown, in step 7, the use case portrait update module stores the failure experience attribution of the target use case into the use case portrait library.

[0119] So far, the first embodiment of the present application has been introduced in detail. The data processing method provided by the first embodiment of the present application combines the basic feature set of failure attribution of historical failed use cases when obtaining the failure experience attribution of the target use case, so that the obtained failure experience attribution is more accurate and the speed of troubleshooting difficult use cases is accelerated; in addition, the failure experience attribution of the target use case and the basic feature set of failure attribution of the target use case are stored in the use case portrait library as a use case portrait. By establishing a use case portrait method, each troubleshooting result and troubleshooting experience are recorded and associated, which provides a reference for subsequent problem troubleshooting and reduces the difficulty of problem troubleshooting; in the preferred embodiment, an artificial feedback mechanism is introduced to improve the accuracy of attribution recommendation.

[0120] Corresponding to the data processing method provided in the first embodiment of the present application, the second embodiment of the present application also provides a data processing device.

[0121] like Figure 3 As shown, the data processing device comprises:

[0122] A link data acquisition unit 301 is used to acquire link data generated by executing a target use case;

[0123] A failure attribution basic feature set obtaining unit 302 is used to obtain a failure attribution basic feature set of a target use case according to the link data;

[0124] The failure experience attribution obtaining unit 303 is used to obtain the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library, and the use case portrait includes the failure attribution basic feature set and the failure experience attribution;

[0125] The attribution storage unit 304 is used to store the failure experience attribution of the target use case and the failure attribution basic feature set of the target use case into the use case portrait library.

[0126] Optionally, the failure experience attribution obtaining unit is specifically used to:

[0127] Obtain a failure attribution recommendation list for the target use case based on the failure attribution basic feature set of the target use case and the use case portraits of historical failed use cases obtained from the use case portrait library;

[0128] According to the failure attribution recommendation list of the target use case, the failure experience attribution of the target use case is obtained.

[0129] Optionally, the failure experience attribution obtaining unit is specifically used to:

[0130] Obtaining a use case portrait distance between the target use case and the historical failure use case based on the failure attribution basic feature set of the target use case and the failure attribution basic feature set of the historical failure use case obtained from the use case portrait library;

[0131] Based on the use case profile distance, obtain a recommended list of failure attribution for the target use case.

[0132] Optionally, the failure experience attribution obtaining unit is specifically used to:

[0133] According to the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of the target use case, and the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of historical failure use cases obtained from the use case portrait library, the use case portrait distance between the target use case and the historical failure use case is obtained.

[0134] Optionally, the failure experience attribution obtaining unit is specifically used to:

[0135] Sort the use case profile distances from small to large;

[0136] Obtain the target historical failed use cases corresponding to the use case profile distances within a preset number of order;

[0137] Obtaining the failure attribution similarity between the target use case and the target historical failure use case according to the use case profile distance between the target historical failure use case and the target use case;

[0138] According to the failure attribution similarity, a recommended list of failure attribution for the target use case is obtained.

[0139] Optionally, the failure experience attribution obtaining unit is specifically used to:

[0140] The failure attribution similarity between the target use case and the target historical failure case is obtained based on the use case portrait distance between the target historical failure use case and the target use case, the failure attribution basic features included in the failure attribution basic feature set of the target use case, and the weights of the failure attribution basic features.

[0141] Optionally, the failure experience attribution obtaining unit is specifically used to: receive evaluation feedback results of failure attribution of target use cases in the failure attribution recommendation list;

[0142] According to the evaluation feedback results, the failure experience attribution of the target use case is obtained.

[0143] Optionally, the failure experience attribution obtaining unit is specifically used to:

[0144] Formatting and normalizing the evaluation feedback results;

[0145] Feature extraction is performed on the evaluation feedback results after formatting and normalization to obtain the failure experience attribution of the target use case.

[0146] It should be noted that for the detailed description of the device provided in the second embodiment of the present application, reference can be made to the relevant description of the first embodiment of the present application, which will not be repeated here.

[0147] Corresponding to the data processing method provided in the first embodiment of the present application, the third embodiment of the present application also provides an electronic device.

[0148] like Figure 4 As shown, the electronic device comprises:

[0149] Processor 401;

[0150] The memory 402 is used to store the program of the data processing method. After the device is powered on and the program of the data processing method is run by the processor, the following steps are performed:

[0151] Get the link data generated by executing the target use case;

[0152] According to the link data, a basic feature set of failure attribution of a target use case is obtained;

[0153] Obtaining the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library, and the use case portrait includes the failure attribution basic feature set and the failure experience attribution;

[0154] The failure experience attribution of the target use case and the failure attribution basic feature set of the target use case are stored in a use case portrait library as a use case portrait of the target use case.

[0155] Optionally, obtaining the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library includes:

[0156] Obtain a failure attribution recommendation list for the target use case based on the failure attribution basic feature set of the target use case and the use case portraits of historical failed use cases obtained from the use case portrait library;

[0157] According to the failure attribution recommendation list of the target use case, the failure experience attribution of the target use case is obtained.

[0158] Optionally, obtaining a failure attribution recommendation list for the target use case based on the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library includes:

[0159] Obtaining a use case portrait distance between the target use case and the historical failure use case based on the failure attribution basic feature set of the target use case and the failure attribution basic feature set of the historical failure use case obtained from the use case portrait library;

[0160] Based on the use case profile distance, obtain a recommended list of failure attribution for the target use case.

[0161] Optionally, obtaining the use case portrait distance between the target use case and the historical failure use case based on the failure attribution basic feature set of the target use case and the failure attribution basic feature set of the historical failure use case obtained from the use case portrait library includes:

[0162] According to the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of the target use case, and the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of historical failure use cases obtained from the use case portrait library, the use case portrait distance between the target use case and the historical failure use case is obtained.

[0163] Optionally, obtaining a failure attribution recommendation list of a target use case based on the use case profile distance includes:

[0164] Sort the use case profile distances from small to large;

[0165] Obtain the target historical failed use cases corresponding to the use case profile distances within a preset number of order;

[0166] Obtaining the failure attribution similarity between the target use case and the target historical failure use case according to the use case profile distance between the target historical failure use case and the target use case;

[0167] According to the failure attribution similarity, a recommended list of failure attribution for the target use case is obtained.

[0168] Optionally, obtaining the failure attribution similarity between the target use case and the target historical failure use case according to the use case portrait distance between the target historical failure use case and the target use case includes:

[0169] The failure attribution similarity between the target use case and the target historical failure case is obtained based on the use case portrait distance between the target historical failure use case and the target use case, the failure attribution basic features included in the failure attribution basic feature set of the target use case, and the weights of the failure attribution basic features.

[0170] Optionally, obtaining the failure experience attribution of the target use case according to the failure attribution recommendation list includes:

[0171] Receive evaluation feedback results for failure attribution of a target use case in the failure attribution recommendation list;

[0172] According to the evaluation feedback results, the failure experience attribution of the target use case is obtained.

[0173] Optionally, based on the evaluation feedback result, the failure experience attribution of the target use case is obtained, including:

[0174] Formatting and normalizing the evaluation feedback results;

[0175] Feature extraction is performed on the evaluation feedback results after formatting and normalization to obtain the failure experience attribution of the target use case.

[0176] It should be noted that for the detailed description of the electronic device provided in the third embodiment of the present application, reference can be made to the relevant description of the first embodiment of the present application, which will not be repeated here.

[0177] Corresponding to the data processing method provided in the first embodiment of the present application, the fourth embodiment of the present application further provides a storage device storing a program of the data processing method, the program is executed by a processor to perform the following steps:

[0178] Get the link data generated by executing the target use case;

[0179] According to the link data, a basic feature set of failure attribution of a target use case is obtained;

[0180] Obtaining the failure experience attribution of the target use case based on the failure attribution basic feature set of the target use case and the failure attribution basic feature set of historical failed use cases obtained from a use case portrait library; wherein the use case portrait library stores portraits of historical failed use cases;

[0181] The failure experience attribution of the target use case and the failure attribution basic feature set of the target use case are stored in the use case portrait library.

[0182] It should be noted that for the detailed description of the storage device provided in the fourth embodiment of the present application, reference can be made to the relevant description of the first embodiment of the present application, which will not be repeated here.

[0183] Although the present application is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present application. Any technical personnel in this field may make possible changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims of the present application.

[0184] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0185] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0186] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory media such as modulated data signals and carrier waves.

[0187] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

Claims

1. A data processing method, comprising: Acquire link data generated by executing a target use case, wherein the target use case is a test case whose execution result is different from expected data, and the link data refers to at least one of the following data: test environment information, execution process data, result data collection, and whether it is a main use case; According to the link data, a basic feature set of failure attribution of a target use case is obtained; Obtaining the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library, and the use case portrait includes the failure attribution basic feature set and the failure experience attribution; The failure experience attribution of the target use case and the failure attribution basic feature set of the target use case are stored in a use case portrait library as a use case portrait of the target use case.

2. According to the method of claim 1, obtaining the failure experience attribution of the target use case based on the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library comprises: Obtain a failure attribution recommendation list for the target use case based on the failure attribution basic feature set of the target use case and the use case portraits of historical failed use cases obtained from the use case portrait library; According to the failure attribution recommendation list of the target use case, the failure experience attribution of the target use case is obtained.

3. The method according to claim 2, wherein obtaining a failure attribution recommendation list of the target use case based on the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library comprises: Obtaining a use case portrait distance between the target use case and the historical failure use case based on the failure attribution basic feature set of the target use case and the failure attribution basic feature set of the historical failure use case obtained from the use case portrait library; Based on the use case profile distance, obtain a recommended list of failure attribution for the target use case.

4. The method according to claim 3, wherein obtaining the use case profile distance between the target use case and the historical failure use case based on the failure attribution basic feature set of the target use case and the failure attribution basic feature set of the historical failure use case obtained from the use case profile library comprises: According to the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of the target use case, and the failure attribution basic features and the weights of the failure attribution basic features contained in the failure attribution basic feature set of historical failure use cases obtained from the use case portrait library, the use case portrait distance between the target use case and the historical failure use case is obtained.

5. According to the method of claim 3, obtaining a failure attribution recommendation list of a target use case according to the use case profile distance comprises: Sort the use case profile distances from small to large; Obtain the target historical failed use cases corresponding to the use case profile distances within a preset number of order; Obtaining the failure attribution similarity between the target use case and the target historical failure use case according to the use case profile distance between the target historical failure use case and the target use case; According to the failure attribution similarity, a recommended list of failure attribution for the target use case is obtained.

6. The method according to claim 5, wherein obtaining the failure attribution similarity between the target use case and the target historical failure use case based on the use case profile distance between the target historical failure use case and the target use case comprises: The failure attribution similarity between the target use case and the target historical failure case is obtained based on the use case portrait distance between the target historical failure use case and the target use case, the failure attribution basic features included in the failure attribution basic feature set of the target use case, and the weights of the failure attribution basic features.

7. According to the method of claim 2, obtaining the failure experience attribution of the target use case according to the failure attribution recommendation list comprises: Receive evaluation feedback results for failure attribution of a target use case in the failure attribution recommendation list; According to the evaluation feedback results, the failure experience attribution of the target use case is obtained.

8. The method according to claim 7, obtaining the failure experience attribution of the target use case according to the evaluation feedback result, comprising: Formatting and normalizing the evaluation feedback results; Feature extraction is performed on the evaluation feedback results after formatting and normalization to obtain the failure experience attribution of the target use case.

9. A data processing device, comprising: A link data acquisition unit is used to acquire link data generated by executing a target use case, wherein the target use case is a test case whose execution result is different from the expected data, and the link data refers to at least one of the following data: test environment information, execution process data, result data collection, and whether it is a main use case; A failure attribution basic feature set obtaining unit, used to obtain a failure attribution basic feature set of a target use case according to the link data; A failure experience attribution obtaining unit, used to obtain the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library; the use case portrait includes the failure attribution basic feature set and the failure experience attribution; The attribution storage unit is used to store the failure experience attribution of the target use case and the failure attribution basic feature set of the target use case into the use case portrait library.

10. An electronic device, comprising: processor; The memory is used to store a program of the data processing method. After the device is powered on and the program of the data processing method is run by the processor, the following steps are performed: Acquire link data generated by executing a target use case, wherein the target use case is a test case whose execution result is different from expected data, and the link data refers to at least one of the following data: test environment information, execution process data, result data collection, and whether it is a main use case; According to the link data, a basic feature set of failure attribution of a target use case is obtained; Obtaining the failure experience attribution of the target use case according to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library; wherein the use case portrait of the historical failed use case is stored in the use case portrait library, and the use case portrait includes the failure attribution basic feature set and the failure experience attribution; The failure experience attribution of the target use case and the failure attribution basic feature set of the target use case are stored in a use case portrait library as a use case portrait of the target use case.

11. A storage device storing a program of a data processing method, wherein the program is executed by a processor to perform the following steps: Acquire link data generated by executing a target use case, wherein the target use case is a test case whose execution result is different from expected data, and the link data refers to at least one of the following data: test environment information, execution process data, result data collection, and whether it is a main use case; According to the link data, a basic feature set of failure attribution of a target use case is obtained; According to the failure attribution basic feature set of the target use case and the use case portrait of the historical failed use case obtained from the use case portrait library, the failure experience attribution of the target use case is obtained; wherein, The use case portrait library stores use case portraits of historical failed use cases, and the use case portraits include a failure attribution basic feature set and failure experience attribution; The failure experience attribution of the target use case and the failure attribution basic feature set of the target use case are stored in a use case portrait library as a use case portrait of the target use case.

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