Data Processing Method, Apparatus, Terminal, and Storage Medium

Abstract

An embodiment of the present application provides a data processing method, apparatus, terminal, and storage medium. The method includes: obtaining requirement information of first test data; determining a target data type of the first test data according to the requirement information; determining a target data construction template according to the target data type; constructing the first test data according to the target data construction template and the requirement information; performing validity verification on the first test data according to a verification database to obtain a verification result; if the verification result indicates that the first test data is valid data, testing a pipe release activation system according to the first test data to obtain a test result, which can improve the efficiency of constructing test data, thereby improving the efficiency of testing the pipe release activation system.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly to a data processing method, apparatus, terminal, and storage medium. Background Art

[0002] The unblocking and activation system is the core system of credit cards. At the same time, the list of customers to be unblocked and activated is also a key business opportunity project to be triggered before the first swipe. Due to the large number of currently connected channels and related parties, when testing the unblocking and activation system, it is usually necessary to construct the data of the unblocking and activation system. When constructing this data, a large number of dependent parties and call interfaces are required, resulting in low efficiency in data construction, and thus low efficiency in testing the unblocking and activation system. Summary of the Invention

[0003] Embodiments of this application provide a data processing method, apparatus, terminal, and storage medium, which can improve the efficiency of constructing test data, and thus improve the efficiency of testing the unblocking and activation system.

[0004] In a first aspect of the embodiments of this application, a data processing method is provided. The method includes:

[0005] Obtain the requirement information of the first test data;

[0006] Determine the target data type of the test data according to the requirement information;

[0007] Determine a target data construction template according to the target data type;

[0008] Construct the first test data according to the target data construction template and the requirement information

[0009] Verify the validity of the first test data according to a verification database to obtain a verification result;

[0010] If the verification result indicates that the first test data is valid data, test the unblocking and activation system according to the first test data to obtain a test result.

[0011] In combination with the first aspect, in a possible implementation manner, the determining the target data type of the test data according to the requirement information includes:

[0012] Extract keywords from the requirement information to obtain a keyword group;

[0013] Obtain the types of the keywords in the keyword group to obtain K keyword types;

[0014] Determine K reference data types according to the K keyword types and the keywords corresponding to each keyword type in the K keyword types;

[0015] Determine the target data type according to the K reference data types.

[0016] Combined with the first aspect, in a possible implementation manner, the determining the target data construction template according to the target data type includes:

[0017] Determine at least one reference data construction template according to the target data type, where the reference data construction template includes multiple sub-modules;

[0018] Determine at least one sub-module from each reference data construction template of the at least one reference data construction template according to the requirement information to obtain a sub-module set;

[0019] Obtain the first association relationship of the sub-modules in the sub-module set;

[0020] Combine the sub-modules in the sub-module set according to the first association relationship to obtain the target data construction template.

[0021] Combined with the first aspect, in a possible implementation manner, the obtaining the first association relationship of the sub-modules in the sub-module set includes:

[0022] Obtain the module description information of each sub-module in the sub-module set;

[0023] Determine the function information of each sub-module according to the module description information;

[0024] Determine the first association relationship of the sub-modules in the sub-module set according to the function information of each sub-module.

[0025] Combined with the first aspect, in a possible implementation manner, the method further includes:

[0026] Obtain the accuracy rate of the test result;

[0027] If the accuracy rate of the test result is lower than a preset threshold, determine the usage information of each sub-module according to the description information of each sub-module;

[0028] Determine the association relationship correction information according to the usage information of each sub-module;

[0029] Determine the second association relationship according to the association relationship correction information and the first association relationship;

[0030] Combining the sub - modules in the sub - module set according to the second association relationship to obtain the corrected target data construction template;

[0031] Constructing second test data according to the corrected target data construction template and the requirement information.

[0032] Combined with the first aspect, in a possible implementation, the method further includes:

[0033] Obtaining the current data volume of the first test data;

[0034] Determining a first moment for constructing the first test data according to the current data volume and the consumption rate of the first test data;

[0035] Constructing the first test data at the first moment.

[0036] Combined with the first aspect, in a possible implementation, the validating the first test data according to the verification database to obtain a verification result includes:

[0037] Comparing the first test data with the verification data in the verification database to obtain a comparison result;

[0038] Judging whether the verification data in the verification database is similar to the first test data according to the comparison result to obtain a similarity discrimination result;

[0039] Determining the similarity discrimination result as the verification result.

[0040] A second aspect of the embodiments of the present application provides a data processing device, and the device includes:

[0041] An obtaining unit, configured to obtain requirement information of first test data;

[0042] A first determining unit, configured to determine a target data type of the test data according to the requirement information;

[0043] A second determining unit, configured to determine a target data construction template according to the target data type;

[0044] A constructing unit, configured to construct first test data according to the target data construction template and the requirement information;

[0045] A validating unit, configured to validate the first test data according to a verification database to obtain a verification result;

[0046] A test unit, which is configured to test the tube unlocking activation system according to the first test data if the verification result indicates that the first test data is valid data, and obtain a test result.

[0047] In combination with the second aspect, in a possible implementation manner, the first determination unit is configured to:

[0048] Extract keywords from the requirement information to obtain a keyword group;

[0049] Obtain the types of the keywords in the keyword group to obtain K keyword types;

[0050] Determine K reference data types according to the K keyword types and the keywords corresponding to each keyword type in the K keyword types;

[0051] Determine the target data type according to the K reference data types.

[0052] In combination with the second aspect, in a possible implementation manner, the second determination unit is configured to:

[0053] Determine at least one reference data construction template according to the target data type, where the reference data construction template includes a plurality of sub-modules;

[0054] Determine at least one sub-module from each reference data construction template of the at least one reference data construction template according to the requirement information to obtain a sub-module set;

[0055] Obtain the first association relationship of the sub-modules in the sub-module set;

[0056] Combine the sub-modules in the sub-module set according to the first association relationship to obtain the target data construction template.

[0057] In combination with the second aspect, in a possible implementation manner, in terms of obtaining the first association relationship of the sub-modules in the sub-module set, the second determination unit is configured to:

[0058] Obtain the module description information of each sub-module in the sub-module set;

[0059] Determine the function information of each sub-module according to the module description information;

[0060] Determine the first association relationship of the sub-modules in the sub-module set according to the function information of each sub-module.

[0061] In combination with the second aspect, in a possible implementation manner, the apparatus is further configured to:

[0062] Obtain the accuracy rate of the test result;

[0063] If the accuracy rate of the test result is lower than a preset threshold, determine the usage information of each sub-module according to the description information of each sub-module;

[0064] Determine the associated relationship correction information according to the usage information of each sub-module;

[0065] Determine a second associated relationship according to the associated relationship correction information and the first associated relationship;

[0066] Combine the sub-modules in the sub-module set according to the second associated relationship to obtain the corrected target data construction template;

[0067] Construct second test data according to the corrected target data construction template and the requirement information.

[0068] Combined with the second aspect, in a possible implementation manner, the apparatus is further configured to:

[0069] Obtain the current data volume of the first test data;

[0070] Determine the first moment for constructing the first test data according to the current data volume and the consumption rate of the first test data;

[0071] Construct the first test data at the first moment.

[0072] Combined with the second aspect, in a possible implementation manner, the verification unit is configured to:

[0073] Compare the first test data with the verification data in the verification database to obtain a comparison result;

[0074] Judge whether the verification data in the verification database is similar to the first test data according to the comparison result to obtain a similarity discrimination result;

[0075] Determine the similarity discrimination result as the verification result.

[0076] A third aspect of the embodiments of the present application provides a terminal, including a processor, an input device, an output device, and a memory. The processor, the input device, the output device, and the memory are interconnected. Among them, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the step instructions in the first aspect of the embodiments of the present application.

[0077] The fourth aspect of the embodiments of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute some or all of the steps described in the first aspect of the embodiments of the present application.

[0078] The fifth aspect of the embodiments of the present application provides a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute some or all of the steps described in the first aspect of the embodiments of the present application. The computer program product can be a software installation package.

[0079] Implementing the embodiments of the present application has at least the following beneficial effects:

[0080] By obtaining the requirement information of the first test data, determining the target data type of the test data according to the requirement information, determining the target data construction template according to the target data type, constructing the first test data according to the target data construction template and the requirement information, validating the effectiveness of the first test data according to the verification database to obtain a verification result, if the verification result indicates that the first test data is valid data, then testing the pipe-unblocking activation system according to the first test data to obtain a test result. Therefore, the first test data can be automatically constructed according to the requirement information of the pipe-unblocking activation service, and the pipe-unblocking activation system can be tested according to the first test data, thereby improving the efficiency of testing the pipe-unblocking activation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0082] Figure 1 It is a schematic flowchart of a data processing method provided by an embodiment of the present application;

[0083] Figure 2 It is a schematic flowchart of another data processing method provided by an embodiment of the present application;

[0084] Figure 3 It is a schematic flowchart of another data processing method provided by an embodiment of the present application;

[0085] Figure 4 It is a schematic structural diagram of a terminal provided by an embodiment of the present application;

[0086] Figure 5 The embodiments of the present application provide a structural schematic diagram of a data processing device. Specific embodiments

[0087] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0088] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0089] Referring to "embodiments" in the present application means that specific features, structures or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described in the present application can be combined with other embodiments.

[0090] To better understand the data processing method provided by the embodiments of the present application, the solution management activation system to which the data processing method is applied will be briefly introduced below. The solution management activation system is the core system of credit cards. At the same time, the list of customers to be de-piped and activated is also a key business project to be triggered before the first swipe. Currently, there are many channels and related parties connected to the solution management activation system. After the solution management activation system is successfully built, it is necessary to test the solution management activation system. Since the system has a large capacity, a large amount of test data needs to be constructed to meet the test requirements. The data processing method provided by the embodiments of the present application is applied to a terminal device. The terminal device can be a computer, a server, a tablet computer, a mobile terminal, etc. The terminal device can determine the target data type of the test data according to the demand information of the solution management activation service in the solution management activation system. The terminal device determines the target data construction template according to the target data type of the test data. The terminal device constructs the test data according to the target data construction template and the demand information, so that the first test data can be automatically constructed, improving the efficiency when constructing the first test data.

[0091] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of a data processing method provided by an embodiment of this application. As Figure 1 shown, this method is applied to a terminal device, and the method includes the following steps:

[0092] 101. Obtain the requirement information of the first test data.

[0093] The first test data is test data corresponding to the de-piping activation service. If the service scenario of the de-piping activation service is different, the requirement information of the first test data is also different. For example, the service scenario is a credit card activation scenario for adult members in ordinary wage-earning families, etc.

[0094] The method for obtaining the requirement information can be to obtain the requirement information through user input, or to obtain the requirement information from the server side, or to obtain the requirement information through the input of management personnel, etc.

[0095] 102. Determine the target data type of the first test data according to the requirement information.

[0096] Keyword extraction can be performed on the requirement information to obtain corresponding keyword groups, and the target data type can be determined according to the types of keywords in the keyword groups and the information carried by the keywords themselves.

[0097] 103. Determine the target data construction template according to the target data type.

[0098] At least one reference data construction template can be determined from the database according to the target data type, and the target data construction template can be determined according to the above reference data construction template.

[0099] For example, at least one reference data construction template is determined from the database by matching according to the target data type. Or, at least one reference data construction template is determined from the database according to the similarity between the target data type and the data types of the data construction templates in the database. For example, the data construction templates corresponding to the data types with a similarity higher than a preset similarity threshold can be determined as the reference data construction templates. The preset similarity threshold is set by empirical values or historical data.

[0100] 104. Construct the first test data according to the target data construction template and the requirement information.

[0101] The characteristic information of the first test data can be determined according to the requirement information, and the first test data can be constructed according to the characteristic information and the target data construction template.

[0102] Among them, the method for determining the feature information according to the requirement information may be: the feature information may be, for example, a quantity feature, a quantity requirement feature, etc. The quantity feature can be understood as the quantity of the first test data, and the quantity requirement feature can be understood as the adjustment information of the first test data in different regions. For example, within the urban area, the adjustment information may be to increase the quantity of the first test data, as well as the increase amount of the data quantity in different urban areas. Within the rural area, the adjustment information may be to reduce the quantity of the first test data, as well as the reduction amount of the data quantity in the rural area, etc.

[0103] 105. Perform validity verification on the first test data according to the verification database to obtain a verification result.

[0104] 106. If the verification result indicates that the first test data is valid data, then test the pipe-unblocking activation system according to the first test data to obtain a test result.

[0105] Among them, the verification database may be a third-party trusted database, and this third-party trusted database may be a database authenticated by a trusted certification agency, etc.

[0106] In this example, by obtaining the requirement information of the first test data, determining the target data type of the test data according to the requirement information, determining the target data construction template according to the target data type, constructing the first test data according to the target data construction template and the requirement information, performing validity verification on the first test data according to the verification database to obtain a verification result, and if the verification result indicates that the first test data is valid data, then testing the pipe-unblocking activation system according to the first test data to obtain a test result. Therefore, the first test data can be automatically constructed according to the requirement information of the pipe-unblocking activation service, and the pipe-unblocking activation system can be tested according to the first test data, thereby improving the efficiency when testing the pipe-unblocking activation system.

[0107] In a possible implementation manner, a possible method for determining the target data type of the first test data according to the requirement information includes:

[0108] A1. Extract keywords from the requirement information to obtain a keyword group;

[0109] A2. Obtain the types of the keywords in the keyword group to obtain K keyword types;

[0110] A3. Determine K reference data types according to the K keyword types and the keywords corresponding to each keyword type in the K keyword types;

[0111] A4. Determine the target data type according to the K reference data types.

[0112] A general keyword extraction algorithm can be used to extract keywords from the requirement information to obtain a keyword group, and the keywords in the keyword group are keywords related to the data type.

[0113] Keywords correspond to keyword types, and the types of keywords can be identified to obtain keyword types. For example, for keywords A, B, and C, the categories of keywords A, B, and C can be identified to obtain the keyword type 1 corresponding to keyword A, the keyword type 2 corresponding to keyword B, and the keyword type 1 corresponding to keyword C. Since the types corresponding to keywords may be the same, K is a positive integer less than or equal to the total number of keywords in the keyword group.

[0114] The semantic information of the keyword and the keyword type can be combined to obtain combined information, which is information used to determine the reference data type. The method of combining the semantic information of the keyword and the keyword type can be to number the semantic information using a preset numbering method to obtain its corresponding number; combine the number with the keyword type to obtain the combined information. Then, according to the mapping relationship between the combined information and the data type, the reference data type corresponding to the combined information is determined.

[0115] The K reference data types can be combined as subtypes of the target data type to obtain the target data type. For example, the K reference data types can be understood as sub-data types included in the target data type. The target data types obtained by combining different reference data types are different.

[0116] In this example, by extracting keywords from the requirement information, a keyword group is obtained, the types of the keywords in the keyword group are obtained to obtain K keyword types, K reference data types are determined according to the K keyword types and the keywords corresponding to each keyword type in the K keyword types, and the target data type is determined according to the K reference data types. Thus, the target data type is determined through the K reference data types, improving the accuracy in determining the target data type.

[0117] In a possible implementation manner, a method for determining a target data construction template according to the target data type may include:

[0118] B1. According to the target data type, determine at least one reference data construction template, where the reference data construction template includes multiple sub-modules;

[0119] B2. Determine at least one sub-module from each reference data construction template for constructing the template from the at least one reference data according to the requirement information, so as to obtain a sub-module set;

[0120] B3. Obtain the first association relationship of the sub-modules in the sub-module set;

[0121] B4. Combine the sub-modules in the sub-module set according to the first association relationship to obtain the target data construction template.

[0122] The reference data construction template can be a template set manually in advance for constructing test data. The reference data template can include parameters for constructing multiple test data. Since the same data type can correspond to multiple similar scenarios or adjacent scenarios, the target data type can correspond to multiple reference data construction templates. Each reference data construction template includes multiple sub-modules. There can be the same sub-modules or different sub-modules in different reference data construction templates. The performance parameters of the same sub-modules are the same. For example, the description information of the sub-modules is the same, and the usage information of the sub-modules is also the same, etc. The description information of the sub-module can be understood as the performance description of the sub-module, and the usage information of the sub-module can be understood as the usage frequency when the sub-module is used, etc.

[0123] Since at least one reference data construction template can be the reference data construction template corresponding to scenarios with similar requirement information, at least one sub-module adapted to the requirement information can be determined from the multiple sub-modules of each reference data construction template according to the requirement information, so as to obtain a sub-module set. The method for determining at least one sub-module adapted to the requirement information from the multiple sub-modules of the reference data construction template according to the requirement information can be: multiple requirement directions in the requirement information can be obtained, and at least one sub-module can be determined from the multiple sub-modules of the reference data construction template according to the requirement direction. The requirement direction can be understood as the requirement focus. For example, regional requirements, the age group of users, the income information of users, the asset information of users, etc.

[0124] The first association relationship can be determined according to the description information of the sub-modules in the sub-module set. The first association relationship can be understood as the tightness between sub-modules. The closer the association relationship is, the closer the setting distance between sub-modules is. The more distant the association relationship is, the farther the setting distance between sub-modules is.

[0125] The sub-modules are combined according to the tightness of the first association relationship to obtain the target data construction template. The closer the association relationship between sub-modules is, the closer the distance between sub-modules is. The more distant the association relationship between sub-modules is, the farther the distance between sub-modules is.

[0126] In this example, at least one reference data construction template is determined according to the target data type, and at least one sub-module is determined from each reference data construction template of the at least one reference data construction template according to the requirement information to obtain a sub-module set, and the sub-modules in the sub-module set are combined according to the first association relationship between the sub-modules to obtain the target data construction template. Therefore, the target data construction template can be determined according to multiple reference data construction templates, improving the accuracy of determining the target data construction template.

[0127] In a possible implementation manner, a possible way to obtain the first association relationship of the sub-modules in the sub-module set includes:

[0128] C1. Obtain the module description information of each sub-module in the sub-module set;

[0129] C2. Determine the function information of each sub-module according to the module description information;

[0130] C3. Determine the first association relationship of the sub-modules in the sub-module set according to the function information of each sub-module.

[0131] Among them, the module description information of each sub-module can be determined from the module description information set stored in the database. For example, the module description information of the sub-module can be determined from the module description information through the sub-module identifier. Of course, it can also be that the module description information is carried in the attribute information of each sub-module itself, and then the module description information can be directly obtained from the attribute information. Of course, it can also be obtained in other ways. The module description information includes function information, usage information, creation information, etc.

[0132] The function information corresponding to the sub-module can be extracted from the module description information. The function information of the sub-modules can be compared to obtain a similarity, and the first association relationship is determined according to the similarity. Specifically, it can be: the higher the similarity between the function information of two sub-modules, the closer the first association relationship between the two sub-modules; the lower the similarity between the function information of two sub-modules, the more distant the first association relationship between the two sub-modules.

[0133] In this example, by obtaining the module description information of each sub-module and determining the first association relationship according to the function information in the module description information, the accuracy of determining the association relationship is improved.

[0134] In a possible implementation manner, when testing the solution pipe activation system, there may be a situation where the test data is deviated, resulting in poor accuracy of the test result. Then, the test data can also be corrected to improve the accuracy of the test, specifically as follows:

[0135] D1. Obtain the accuracy rate of the test result;

[0136] D2. If the accuracy rate of the test result is lower than the preset threshold, determine the usage information of each sub-module according to the description information of each sub-module;

[0137] D3. Determine the associated relationship correction information according to the usage information of each sub-module;

[0138] D4. Determine the second associated relationship according to the associated relationship correction information and the first associated relationship;

[0139] D5. Combine the sub-modules in the sub-module set according to the second associated relationship to obtain the corrected target data construction template;

[0140] D6. Construct the second test data according to the corrected target data construction template and the requirement information.

[0141] Among them, the preset threshold can be set through empirical values or historical data. The usage information may include the usage frequency and usage duration of the sub-module, etc.

[0142] The associated relationship correction information can be determined according to the usage frequency and usage duration. Specifically, the smaller the difference between the usage durations of two sub-modules, the closer their associated relationship; the smaller the difference between the usage frequencies, the closer their associated relationship; the larger the difference between the usage durations of two sub-modules, the more distant their associated relationship; the larger the difference between the usage frequencies, the more distant their associated relationship. Then, the associated relationship correction value can be determined according to the above relationship.

[0143] Of course, the usage frequency can also be understood as the frequency of the associated use of two modules. The higher the frequency of the associated use, the closer the associated relationship; the lower the frequency of the associated use, the more distant the associated relationship.

[0144] The first associated relationship can be adjusted according to the associated relationship correction information. For example, the first associated relationship between two sub-modules can be adjusted to be closer or more distant, and the adjusted first associated relationship is determined as the second associated relationship.

[0145] In this example, the first associated relationship is corrected by the obtained associated relationship correction information to obtain the second associated relationship, and the sub-modules in the sub-module set are combined according to the second associated relationship to obtain the corrected target data construction template, and finally the second test data is constructed, improving the accuracy of the test using the second test data.

[0146] In a possible implementation, the first test data can also be automatically generated. Specifically:

[0147] E1. Obtain the current data volume of the first test data;

[0148] E2. Determine the first moment for constructing the first test data according to the current data volume and the consumption rate of the first test data;

[0149] E3. Construct the first test data at the first moment.

[0150] Since the test data is used once and cannot be used again, the first moment for constructing the first test data is determined according to the current quantity and consumption rate, and the test data is constructed at the first moment, thereby improving the stability during testing.

[0151] In a possible implementation manner, a method for validating the effectiveness of the first test data according to a verification database to obtain a verification result includes:

[0152] F1. Compare the first test data with the verification data in the verification database to obtain a comparison result;

[0153] F2. Judge whether the verification data in the verification database is similar to the first test data according to the comparison result to obtain a similarity discrimination result;

[0154] F3. Determine the similarity discrimination result as the verification result.

[0155] Among them, when comparing the first test data with the verification data, a similarity comparison method can be used to obtain a comparison result, and the comparison result here is the similarity between the first test data and the verification data.

[0156] The similarity in the comparison result can be compared with a preset similarity threshold. If it is higher than the similarity threshold, it is determined that the first test data is similar to the verification data. If it is lower than the similarity threshold, it is determined that the first test data is not similar to the verification data.

[0157] The pipe-unbundling activation system provided by the embodiments of the present application can also perform unified interface visualization management of pipe-unbundling data, facilitating testers to obtain and use data information more efficiently; it integrates system functions such as pipe-unbundling whitelists, business opportunity push, and data generation simulators, making it more flexible and customizable to construct data for different scenarios.

[0158] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of another data processing method provided by the embodiments of the present application. As Figure 2 shown, this method is applied to a terminal device, and this method includes the following steps:

[0159] 201. Obtain the requirement information of the first test data;

[0160] 202. Extract keywords from the requirement information to obtain a keyword group;

[0161] 203. Obtain the types of keywords in the keyword group to obtain K keyword types;

[0162] 204. Determine K reference data types according to the K keyword types and the keywords corresponding to each keyword type in the K keyword types;

[0163] 205. Determine the target data type according to the K reference data types;

[0164] 206. Determine a target data construction template according to the target data type;

[0165] 207. Construct the first test data according to the target data construction template and the requirement information.

[0166] In this example, by extracting keywords from the requirement information, a keyword group is obtained, the types of keywords in the keyword group are obtained to obtain K keyword types, and K reference data types are determined according to the K keyword types and the keywords corresponding to each keyword type in the K keyword types. The target data type is determined according to the K reference data types, so that the target data type is determined through the K reference data types, improving the accuracy when determining the target data type.

[0167] Please refer to Figure 3 , Figure 3 which is a schematic flowchart of another data processing method provided by an embodiment of the present application. As Figure 3 shown, this method is applied to a terminal device, and the method includes the following steps:

[0168] 301. Obtain the requirement information of the first test data;

[0169] 302. Determine the target data type of the first test data according to the requirement information;

[0170] 303. Determine at least one reference data construction template according to the target data type, and the reference data construction template includes multiple sub-modules;

[0171] 304. Determine at least one sub-module from each reference data construction template of the at least one reference data construction template according to the requirement information to obtain a sub-module set;

[0172] 305. Obtain the module description information of each sub-module in the sub-module set;

[0173] 306. Determine the function information of each sub-module according to the module description information;

[0174] 307. Determine the first association relationship of the sub-modules in the sub-module set according to the function information of each sub-module;

[0175] 308. Combine the sub-modules in the sub-module set according to the first association relationship to obtain the target data construction template;

[0176] 309. Construct the first test data according to the target data construction template and the requirement information.

[0177] In this example, at least one reference data construction template is determined according to the target data type, and at least one sub-module is determined from each reference data construction template of the at least one reference data construction template according to the requirement information to obtain a sub-module set, and the sub-modules in the sub-module set are combined according to the first association relationship between the sub-modules to obtain the target data construction template. Therefore, the target data construction template can be determined according to multiple reference data construction templates, improving the accuracy of determining the target data construction template.

[0178] Consistent with the above embodiment, please refer to Figure 4 , Figure 4 which is a schematic structural diagram of a terminal provided by an embodiment of the present application. As shown in the figure, it includes a processor, an input device, an output device, and a memory. The processor, input device, output device, and memory are interconnected. Among them, the memory is used to store a computer program, and the computer program includes program instructions. The processor is configured to call the program instructions, and the above program includes instructions for performing the following steps;

[0179] Obtain the requirement information of the first test data;

[0180] Determine the target data type of the first test data according to the requirement information;

[0181] Determine the target data construction template according to the target data type;

[0182] Construct the first test data according to the target data construction template and the requirement information;

[0183] Verify the validity of the first test data according to the verification database to obtain a verification result;

[0184] If the verification result indicates that the first test data is valid data, the tube unlocking activation system is tested according to the first test data to obtain a test result.

[0185] The above mainly introduces the solution of the embodiment of the present application from the perspective of the execution process on the method side. It can be understood that in order for the terminal to implement the above functions, it includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments provided in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraint conditions of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0186] The embodiment of the present application can divide the functional units of the terminal according to the above method examples. For example, each functional unit can be divided corresponding to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. It should be noted that the division of units in the embodiment of the present application is illustrative, only a logical function division, and there may be other division methods in actual implementation.

[0187] Consistent with the above, please refer to Figure 5 , Figure 5 which is a schematic structural diagram of a data processing device provided by an embodiment of the present application. As Figure 5 shown, the device includes:

[0188] An acquisition unit 501, configured to acquire requirement information of the first test data;

[0189] A first determination unit 502, configured to determine a target data type of the test data according to the requirement information;

[0190] A second determination unit 503, configured to determine a target data construction template according to the target data type;

[0191] A construction unit 504, configured to construct the first test data according to the target data construction template and the requirement information;

[0192] A verification unit 505, configured to perform validity verification on the first test data according to a verification database to obtain a verification result;

[0193] A test unit 506 is configured to test the tube-unblocking activation system according to the first test data if the verification result indicates that the first test data is valid data, and obtain a test result.

[0194] In a possible implementation manner, the first determination unit 502 is configured to:

[0195] Extract keywords from the requirement information to obtain a keyword group;

[0196] Obtain the types of the keywords in the keyword group to obtain K keyword types;

[0197] Determine K reference data types according to the K keyword types and the keywords corresponding to each keyword type in the K keyword types;

[0198] Determine the target data type according to the K reference data types.

[0199] In a possible implementation manner, the second determination unit 503 is configured to:

[0200] Determine at least one reference data construction template according to the target data type, where the reference data construction template includes a plurality of sub-modules;

[0201] Determine at least one sub-module from each reference data construction template of the at least one reference data construction template according to the requirement information to obtain a sub-module set;

[0202] Obtain the first association relationship of the sub-modules in the sub-module set;

[0203] Combine the sub-modules in the sub-module set according to the first association relationship to obtain the target data construction template.

[0204] In a possible implementation manner, in terms of obtaining the first association relationship of the sub-modules in the sub-module set, the second determination unit 503 is configured to:

[0205] Obtain the module description information of each sub-module in the sub-module set;

[0206] Determine the function information of each sub-module according to the module description information;

[0207] Determine the first association relationship of the sub-modules in the sub-module set according to the function information of each sub-module.

[0208] In a possible implementation manner, the device is further configured to:

[0209] Obtain the accuracy rate of the test result;

[0210] If the accuracy rate of the test result is lower than a preset threshold, determine the usage information of each sub-module according to the description information of each sub-module;

[0211] Determine the associated relationship correction information according to the usage information of each sub-module;

[0212] Determine a second associated relationship according to the associated relationship correction information and the first associated relationship;

[0213] Combine the sub-modules in the sub-module set according to the second associated relationship to obtain the corrected target data construction template;

[0214] Construct second test data according to the corrected target data construction template and the requirement information.

[0215] In a possible implementation, the apparatus is further configured to:

[0216] Obtain the current data volume of the first test data;

[0217] Determine the first moment for constructing the first test data according to the current data volume and the consumption rate of the first test data;

[0218] Construct the first test data at the first moment.

[0219] In a possible implementation, the verification unit is configured to 506:

[0220] Compare the first test data with the verification data in the verification database to obtain a comparison result;

[0221] Judge whether the verification data in the verification database is similar to the first test data according to the comparison result to obtain a similarity discrimination result;

[0222] Determine the similarity discrimination result as the verification result.

[0223] An embodiment of the present application further provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute some or all of the steps of any one of the data processing methods described in the foregoing method embodiments.

[0224] An embodiment of the present application further provides a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program enables a computer to execute some or all of the steps of any one of the data processing methods described in the foregoing method embodiments.

[0225] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should understand that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0226] In the above embodiments, the descriptions of the respective embodiments have their own focuses. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0227] In several embodiments provided by this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical or other forms.

[0228] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0229] In addition, in each embodiment of the application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software program modules.

[0230] When the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, read-only memories (ROM), random access memories (RAM), mobile hard disks, magnetic disks, or optical discs.

[0231] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory, and the memory can include: flash drives, read-only memories, random access memories, magnetic disks, or optical discs, etc.

[0232] The above has introduced the embodiments of this application in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A data processing method, characterized in that, the method includes: Obtaining requirement information of first test data; Determining a target data type of the first test data according to the requirement information; Determining a target data construction template according to the target data type; Constructing first test data according to the target data construction template and the requirement information; Performing validity verification on the first test data according to a verification database to obtain a verification result; If the verification result indicates that the first test data is valid data, testing a solution tube activation system according to the first test data to obtain a test result; Wherein, the determining a target data construction template according to the target data type includes: Determining at least one reference data construction template according to the target data type, and the reference data construction template includes multiple sub-modules; Determining at least one sub-module from each reference data construction template of the at least one reference data construction template according to the requirement information to obtain a sub-module set; Obtaining a first association relationship of the sub-modules in the sub-module set; Combining the sub-modules in the sub-module set according to the first association relationship to obtain the target data construction template; The obtaining a first association relationship of the sub-modules in the sub-module set includes: Obtaining module description information of each sub-module in the sub-module set; Determining function information of each sub-module according to the module description information; Determining a first association relationship of the sub-modules in the sub-module set according to the function information of each sub-module, and the first association relationship is determined by a similarity degree of comparison of the function information of the sub-modules.

2. The method according to claim 1, characterized in that, the determining a target data type of the first test data according to the requirement information includes: Performing keyword extraction on the requirement information to obtain a keyword group; Obtaining types of keywords in the keyword group to obtain K keyword types; Determining K reference data types according to the K keyword types and keywords corresponding to each keyword type in the K keyword types; Determining the target data type according to the K reference data types.

3. The method according to claim 1 or 2, characterized in that, the method further includes: Obtaining an accuracy rate of the test result; If the accuracy rate of the test result is lower than a preset threshold, determining usage information of each sub-module according to the description information of each sub-module; Determining association relationship correction information according to the usage information of each sub-module; Determining a second association relationship according to the association relationship correction information and the first association relationship; Combining the sub-modules in the sub-module set according to the second association relationship to obtain the corrected target data construction template; Constructing second test data according to the corrected target data construction template and the requirement information.

4. The method according to claim 1, characterized in that, the method further includes: Obtaining a current data volume of the first test data; Determine a first moment for constructing the first test data according to the current data volume and the consumption rate of the first test data; Construct the first test data at the first moment.

5. The method according to claim 4, wherein, The validity verification of the first test data according to the verification database to obtain a verification result includes: Compare the first test data with the verification data in the verification database to obtain a comparison result; Judge whether the verification data in the verification database is similar to the first test data according to the comparison result to obtain a similarity discrimination result; Determine the similarity discrimination result as the verification result.

6. A data processing device, wherein, The device includes: An acquisition unit for acquiring requirement information of the first test data; A first determination unit for determining a target data type of the test data according to the requirement information; A second determination unit for determining a target data construction template according to the target data type; A construction unit for constructing the first test data according to the target data construction template and the requirement information; A verification unit for performing validity verification on the first test data according to the verification database to obtain a verification result; A test unit for, if the verification result indicates that the first test data is valid data, testing the pipe unlocking activation system according to the first test data to obtain a test result; wherein, the second determination unit is used for: Determine at least one reference data construction template according to the target data type, and the reference data construction template includes a plurality of sub-modules; Determine at least one sub-module from each reference data construction template of the at least one reference data construction template according to the requirement information to obtain a sub-module set; Obtain a first association relationship of the sub-modules in the sub-module set; Combine the sub-modules in the sub-module set according to the first association relationship to obtain the target data construction template; The second determination unit is further used for: Obtain the module description information of each sub-module in the sub-module set; Determine the function information of each sub-module according to the module description information; Determine a first association relationship of the sub-modules in the sub-module set according to the function information of each sub-module, and the first association relationship is determined by the similarity of the comparison of the function information of the sub-modules.

7. A terminal, wherein, It includes a processor, an input device, an output device and a memory, and the processor, the input device, the output device and the memory are interconnected. Among them, the memory is used to store a computer program, and the computer program includes program instructions. The processor is configured to call the program instructions to execute the method according to any one of claims 1-5.

8. A computer-readable storage medium, wherein, The computer-readable storage medium stores a computer program, and the computer program includes program instructions. When the program instructions are executed by a processor, the processor is caused to execute the method according to any one of claims 1-5.

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