Test method and device of point of interest service module, electronic equipment and storage medium

Abstract

The present disclosure provides a test method and device of a point of interest service module, electronic equipment and storage medium, and relates to the technical fields of big data and map data processing. The specific implementation scheme is: obtaining a target point of interest identifier selected for this test and function information of the point of interest service module for this test; determining data attribute information involved in this test based on the function information; performing online-to-offline filling processing of test data based on the target point of interest identifier, the data attribute information and a preset attribute value replacement strategy; and testing the point of interest service module based on the test data after the filling processing. The technology of the present disclosure can effectively improve the stability of the test, ensure the authenticity of the test data obtained by the filling, simulate the real use scenario of the user, meet the test intention and improve the test efficiency.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, specifically to the fields of big data and map data processing, and particularly to a testing method, apparatus, electronic device, and storage medium for a point-of-interest service module. Background Technology

[0002] When the functionality of the Point of Interest (POI) service module of a location-based services (LBS) electronic map changes, it is necessary to use corresponding test data to test the changed functionality of the POI service module.

[0003] During existing technology testing, test data can be directly retrieved from storage to test the POI service module. The data in storage can be historical data generated when the electronic map provided services prior to this test. Since the data in storage is generated from real-world user interactions with the electronic map, it can simulate real-world user scenarios, ensuring the authenticity of the POI service module test. Summary of the Invention

[0004] This disclosure provides a testing method, apparatus, electronic device, and storage medium for a point-of-interest (POI) service module.

[0005] According to one aspect of this disclosure, a testing method for an interest point service module is provided, comprising:

[0006] This test uses the selected target point of interest identifier and the data type of functional information of the point of interest service module for this test.

[0007] Based on the aforementioned functional information, the data attribute information involved in this test is determined;

[0008] Based on the target point of interest identifier, the data attribute information data type, and the preset attribute value replacement strategy for the data corresponding to the data type, the online to offline database injection process of the test data is carried out.

[0009] The point of interest service module was tested based on the test data after the reservoir was filled.

[0010] According to another aspect of this disclosure, a testing apparatus for a point-of-interest service module is provided, comprising:

[0011] The acquisition module is used to acquire the target point of interest identifiers selected for this test, as well as the functional information of the point of interest service module for this test.

[0012] The determination module is used to determine the data attribute information involved in this test based on the functional information.

[0013] The database injection module is used to perform online-to-offline database injection of test data based on the target point of interest identifier, the data attribute information, and the preset attribute value replacement strategy.

[0014] The testing module is used to test the Point of Interest service module based on the test data after database injection.

[0015] According to another aspect of this disclosure, an electronic device is provided, comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the methods described above and any possible implementations.

[0019] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions for causing the computer to perform the methods described above and any possible implementation thereof.

[0020] According to another aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the aspects and any possible implementations described above.

[0021] According to the technology disclosed herein, the stability of testing can be effectively improved, the authenticity of test data obtained from database injection can be ensured, the real-world usage scenarios of users can be simulated, the testing intent can be met, and the testing efficiency can be improved.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0023] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0024] Figure 1 This is a schematic diagram based on the first embodiment of the present disclosure;

[0025] Figure 2 This is a schematic diagram according to the second embodiment of the present disclosure;

[0026] Figure 3 This is a schematic diagram of the test data injection process in the testing of a POI service module provided in this embodiment;

[0027] Figure 4 This is a schematic diagram according to the third embodiment of the present disclosure;

[0028] Figure 5 This is a schematic diagram according to the fourth embodiment of the present disclosure;

[0029] Figure 6 This is a block diagram of an electronic device used to implement the methods of the embodiments of this disclosure. Detailed Implementation

[0030] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0031] Obviously, the described embodiments are only some, not all, of the embodiments disclosed herein. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0032] It should be noted that the terminal devices involved in the embodiments of this disclosure may include, but are not limited to, smart devices such as mobile phones, personal digital assistants (PDAs), wireless handheld devices, and tablet computers; the display devices may include, but are not limited to, personal computers, televisions, and other devices with display functions.

[0033] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0034] In existing technologies, data is directly retrieved from storage to test the changed POI service module. Although this can simulate real-world user scenarios, the storage is publicly accessible and data can be easily deleted by others, resulting in very poor test stability.

[0035] Figure 1This is a schematic diagram based on the first embodiment of the present disclosure; as shown Figure 1 As shown, this embodiment provides a testing method for a POI service module, which can be applied to testing scenarios for POI service modules. Specifically, it may include the following steps:

[0036] S101. Obtain the target POI identifier selected for this test and the functional information of the POI service module for this test;

[0037] Specifically, the target POI identifier selected for this test and the functional information of the POI service module for this test can be determined by the testers and input into the POI service module's testing device. The functional information is used to identify the functions of the POI service module in this test.

[0038] S102. Based on the functional information, determine the data attribute information involved in this test;

[0039] Specifically, functional information can be considered as information from the perspective of the POI service module's functions, while data attribute information is information from the perspective of data storage in the corresponding data storage system. Based on this data attribute information, the corresponding test data can be obtained more accurately.

[0040] S103. Based on the target POI identifier, data attribute information, and preset attribute value replacement strategy, perform online-to-offline database injection of test data.

[0041] In this embodiment, to improve test stability, a preset attribute value replacement strategy can be used during the online-to-offline database injection process of test data. This strategy replaces the attribute values ​​of the relevant data attributes in the test data, ensuring that the attribute values ​​do not affect the test results when the POI service module tests the corresponding functional information. For example, if the test case verifies the name function of the POI service module, the attribute value of the name in the test data can be replaced with a custom value. This ensures that the name will not change due to changes in the actual data, thus improving test stability.

[0042] S104. Based on the test data after the reservoir filling process, test the POI service module.

[0043] Specifically, when testing the POI service module, the test data obtained after database injection is directly called, and the POI service module is run to test its performance in processing data of that data type in the test data.

[0044] The testing method for the POI service module in this embodiment can perform online-to-offline database injection of test data based on the target POI identifier, data attribute information, and a preset attribute value replacement strategy during each test. This yields the test data for the current test, and the POI service module is then tested based on this data, effectively improving test stability. Furthermore, the online-to-offline database injection process also references the target POI identifier and data attribute information, effectively ensuring the authenticity of the test data obtained through database injection. This simulates real-world user scenarios, aligns with testing objectives, and improves testing efficiency.

[0045] Figure 2 This is a schematic diagram based on the second embodiment of the present disclosure; as shown Figure 2 As shown, this embodiment provides a testing method for a POI service module. Figure 1 Based on the technical solutions of the embodiments, the technical solutions of this disclosure will be described in further detail. For example... Figure 2 As shown, the testing method for the POI service module in this embodiment may specifically include the following steps:

[0046] S201. Obtain the target POI identifier selected for this test and the functional information of the POI service module for this test;

[0047] S202. Based on the pre-established correspondence between functional information and data attribute information, determine the data attribute information involved in this test corresponding to the functional information. The data attribute information includes business data types.

[0048] For example, the business data types in this embodiment may include basic data, detailed data, relational data, and intervention data. Basic data includes basic data corresponding to POI identifiers and basic data corresponding to data source identifiers. Detailed data also includes detailed data corresponding to POI identifiers and detailed data corresponding to data source identifiers. Relational data may include relational data showing the correspondence between POI identifiers and their corresponding data source identifiers, and may also include relational data showing the correspondence between POI identifiers and their backup POI identifiers.

[0049] In this embodiment, the data source identifier refers to the identifier of the data source that provides data support for the display of the target POI. The data source identifier can also be identified as a UID identifier. Since multiple data sources provide data for the same POI in actual business scenarios, one target POI identifier can correspond to multiple data source identifiers, i.e., UID identifiers. Each data source identifier corresponds to one piece of source data, which can include many fields, such as dozens or even hundreds, including fields like name, address, phone number, comments, and images. The target data corresponding to the POI identifier can be obtained based on the source data of all data sources corresponding to all associated UID identifiers. For example, certain strategies or rules can be used to obtain the corresponding POI identifier data from all associated UID identifier data sources.

[0050] In other words, in an online storage system, the attribute values ​​of many fields in the target data corresponding to each POI are determined according to preset rules based on the attribute values ​​of the same or corresponding fields in the source data corresponding to one, two or more data source identifiers.

[0051] Both the target data and source data of the POI identifier can include basic data and detailed data. Basic data can include fields such as name, address, and phone number. Detailed data can include fields such as images and comments. Additionally, the target data of the POI identifier can include intervention data, which allows for rapid and mandatory modifications to the POI service module. Intervention data can restrict the mandatory and rapid modification of certain fields and corresponding attribute values ​​in the target data of the POI identifier. Furthermore, the online storage system also needs to store the two types of relationship data corresponding to each POI identifier.

[0052] In practical implementation, a correspondence table between functional information and data attribute information can be pre-established based on the mapping relationship between functional information and data attribute information. This table records each data attribute information corresponding to each functional information of the POI service module. Specifically, this data attribute information may include business data types and, further, target field information. Optionally, if the target field contains nested subfields in the actual application, target subfield information may also be included. Furthermore, if the target subfield contains nested subfields, information on the lower-level subfields within the target subfield may also be included, and so on, until the lowest-level subfield information, to facilitate accurate location of the corresponding data attribute information. In practical applications, one functional information can correspond to one, two, or more data attribute information. Specifically, it can correspond to one, two, or more business data types and their subordinate multiple field information.

[0053] Using this method, the data attribute information involved in this test can be accurately located, so as to accurately replace the attribute values ​​corresponding to the data attribute information and improve the accuracy of the obtained test data.

[0054] S203. Based on the target POI point of interest identifier and data attribute information, obtain the corresponding first test data from the online storage system;

[0055] S204. Based on the preset attribute value replacement strategy and data attribute information, the attribute values ​​corresponding to the data attribute information in the first test data are replaced to obtain the second test data.

[0056] S205. Write the second test data into the offline POI information storage system;

[0057] The online storage system in this embodiment refers to the online storage system of electronic maps. This method can ensure the authenticity of the first test data obtained.

[0058] In this embodiment, first test data is retrieved from the online storage system based on the target POI (Point of Interest) identifier and data attribute information. Then, according to a preset attribute value replacement strategy, the attribute values ​​of the data corresponding to the data attribute information in the first test data are replaced to obtain second test data. This way, when testing the POI service module using the second test data, the impact of the attribute values ​​of the data attribute information in the test data on the POI service module can be avoided, improving the stability of the test. Finally, the second test data is loaded into the offline POI information storage system for use during testing.

[0059] The above steps S203-S205 are as described above. Figure 1 One implementation of step S103 in the illustrated embodiment ensures that the test data can simulate the user's real usage scenarios while effectively improving the stability of the test.

[0060] Optionally, in one embodiment of this disclosure, steps S203 and S204 may specifically include the following various scenarios:

[0061] Scenario 1: When the business data type corresponding to the data attribute information includes relational data, taking the correspondence between the target POI identifier and at least two data source identifiers as an example, the corresponding step S203 may specifically include: based on the target POI identifier, obtaining the relational data including the correspondence between the target POI identifier and at least two data source identifiers, as well as the first target data corresponding to the target POI identifier and the source data corresponding to each data source identifier from the online storage system, as the first test data;

[0062] Correspondingly, step S204 includes: filtering the relationship data of the correspondence between the target POI identifier and at least two data source identifiers, the first target data corresponding to the target POI identifier, and the source data corresponding to each data source identifier obtained by filtering from the correspondence between the target POI identifier and at least two data source identifiers, as the second test data.

[0063] Scenario 2: When the business data type corresponding to the data attribute information includes relational data, taking the correspondence between the target POI identifier and at least two backup POI identifiers as an example, the corresponding step S203 may specifically include: based on the target point of interest identifier, obtaining the relational data including the correspondence between the target POI identifier and two backup POI identifiers, as well as the first target data corresponding to the target POI identifier and the second target data corresponding to each backup POI identifier from the online storage system, as the first test data.

[0064] Correspondingly, step S204 includes: filtering the relationship data of the correspondence between the target POI identifier and at least one backup POI identifier, the first target data corresponding to the target POI identifier, and the second target data corresponding to each of the filtered backup POI identifiers from the correspondence between the target POI identifier and the two backup POI identifiers, as the second test data.

[0065] The business data types corresponding to Scenarios 1 and 2 above are both relational data. The preset attribute value replacement strategy for relational data can be used to control the quantity. For example, the ratio of the correspondence between target POI identifiers and data source identifiers can be 1:N. The purpose of quantity control in this embodiment is to select M items from N information items using preset rules, where M <= N. The specific selection rules can be ascending order, descending order, or random. Ascending order or descending order refers to selecting M items based on the data source identifiers in descending order, or selecting M items based on the data source identifiers in ascending order. Alternatively, M items can be randomly selected from N data source identifiers. M can be any positive integer greater than or equal to 1, and is not limited here. When the correspondence data is the relationship data between the target POI identifier and two backup POI identifiers, the principle is the same as above, and will not be repeated here.

[0066] By replacing the attribute values ​​of the relational data as described above, the attribute values ​​of the relational data can be changed to avoid the influence of the relational data before replacement on the test data, thereby improving the stability of the test.

[0067] Scenario 3: When the business data type corresponding to the data attribute information includes the basic data corresponding to the source data identifier, the data attribute information also includes target field information. In this case, step S203 includes: based on the preset correspondence between POI identifiers and at least one data source identifier, obtaining at least one data source identifier corresponding to the target POI identifier; obtaining the data corresponding to the target field information in the basic data of the source data corresponding to each data source identifier from the online storage system, as the first test data. For example, specifically, the target field and the attribute value of the target field, and other target field-related data, can be obtained from the basic data of the source data corresponding to each data source identifier. The source data corresponding to each data source identifier is a piece of data that can include multiple data business types such as basic data and detail data. Specifically, the basic data includes data with multiple fields such as name, address, and phone number. The detail data includes data with multiple fields such as comments and images.

[0068] Correspondingly, step S204 includes: replacing the attribute values ​​of the fields corresponding to the target field information of each data source identifier in the first test data according to a preset attribute value replacement strategy, so that the attribute values ​​of the fields corresponding to the target field information of different data source identifiers are different, thus obtaining the second test data.

[0069] In other words, based on a preset attribute value replacement strategy, the attribute value of the target field in the source data corresponding to each data source identifier needs to be replaced, and it is also necessary to ensure that the attribute values ​​of the target field information corresponding to different data source identifiers are different after the replacement.

[0070] Optionally, if the data storage type of the target field's attribute value is a string, a keyword for the replacement value input by the user can be obtained. Then, a string generation tool is used to generate a replacement target string for the attribute value of the target field corresponding to each data source identifier, based on this keyword. This target string includes the keyword. For example, if the user inputs the keyword "ABC", the target strings generated by the string generation tool can be ABC1, ABC2, ABC3, etc. Alternatively, a keyword for the replacement value can be extracted based on the attribute value of the field corresponding to the target field information of each data source identifier. Then, following the same method as above, a replacement target string is generated for the attribute value of the target field corresponding to each data source identifier, based on this keyword. This will not be elaborated further here.

[0071] If the data storage type of the target field's attribute value is numeric, a replacement target value can be generated for each data source identifier's target field value based on a preset attribute value replacement strategy. For example, a preset attribute value replacement strategy could perform mathematical calculations on the original value of the target field before replacement, such as adding or subtracting 1, to obtain the replacement target value. Alternatively, other attribute value replacement strategies can be used in practical applications, which will not be elaborated upon here.

[0072] In practical applications, if the attribute value of the target field is of another data storage type, a corresponding attribute value replacement strategy can be set to replace the corresponding attribute value of the target field. Examples will not be elaborated here.

[0073] It should be noted that this third scenario can be used in combination with the first scenario above, when the data attribute information corresponding to the functional information includes both relational data and basic data corresponding to the source data identifier.

[0074] By adopting this approach, the attribute value of any target field in the basic data corresponding to each source data identifier can be replaced. After the replacement, the attribute value of a target field will be different for different source data identifiers. This can effectively ensure the rationality and effectiveness of the obtained second test data, thereby effectively improving the stability and efficiency of the test.

[0075] Scenario 4: When the business data type corresponding to the data attribute information includes the basic data corresponding to the target POI identifier, the data attribute information also includes target field information. In this case, step S203 includes: based on the target POI identifier, retrieving the data corresponding to the target field information in the basic data of the first target data corresponding to the target POI identifier from the online storage system, as the first test data; for example, specifically, data related to the target field, such as the target field and the attribute value of the target field, can be retrieved from the basic data of the first target data. The first target data corresponding to the target POI identifier is a piece of data that includes multiple data business types such as basic data and detailed data.

[0076] At this time, the corresponding step S204 includes: replacing the attribute values ​​of the fields corresponding to the target field information in the first test data according to a preset attribute value replacement strategy to obtain the second test data.

[0077] Unlike online storage systems where one target POI corresponds to multiple source data identifiers, in online storage systems, one target POI corresponds to only one first target data entry. For the basic data within the first target data, during attribute value replacement, the attribute values ​​of the fields corresponding to the target field information in the first test data are replaced according to a preset attribute value replacement strategy. Specifically, the attribute value replacement strategy can vary depending on the data storage type of the target field's attribute values. For details, please refer to the relevant description in scenario three above; it will not be repeated here.

[0078] By using this approach, the attribute value of any target field in the basic data corresponding to the target POI can be replaced, which can effectively ensure the rationality and effectiveness of the obtained second test data, thereby effectively improving the stability and efficiency of the test.

[0079] Scenario 5: When the business data type corresponding to the data attribute information includes the detailed data of the source data identifier, the data attribute information also includes target field information and lower-level target sub-field information. Correspondingly, step S203 includes: based on a preset correspondence between POI identifiers and at least one data source identifier, obtaining at least one data source identifier corresponding to the target POI identifier; and obtaining the data corresponding to the target field information and target sub-field information in the detailed data of the source data corresponding to each data source identifier from the online storage system, as the first test data. For example, specifically, the target field and its attribute values, and other target field-related data, can be obtained from the detailed data of each source data. In this embodiment, the attribute values ​​of the target field in the detailed data can be nested with one, two, or more sub-fields. Further optionally, in a similar manner, multiple sub-fields can be nested under the target sub-field of the target field, and the corresponding data attribute information can also include lower-level target sub-fields of the target sub-field. In some scenarios, such as when only the attribute values ​​of the target sub-field need to be replaced, when obtaining the first test data, only the corresponding target sub-field and its attribute values, and other target sub-field-related data, need to be obtained. However, in certain scenarios, the attribute value replacement strategy needs to replace not only the attribute values ​​corresponding to the parent target field but also the attribute values ​​of the child target fields. In this case, when obtaining the first test data, it is necessary to obtain not only the data corresponding to the target field information in the details data of the source data corresponding to each data source identifier, but also the data corresponding to the child target field information, as the first test data to ensure the comprehensiveness of the obtained data.

[0080] Correspondingly, step S204 may include: filtering at least one target attribute value from multiple attribute values ​​of the fields corresponding to the target field information of each source data in the first test data according to a preset filtering strategy; and / or replacing the attribute values ​​of the fields corresponding to the target sub-field information in the target field information of each source data in the first test data according to a preset attribute value replacement strategy, so that the attribute values ​​of the fields corresponding to the target sub-field information of different data source identifiers are different. Further, if the attribute values ​​of the target field information of the source data include multiple items, and each item includes target sub-field information, then the replacement in the above manner needs to ensure that the attribute values ​​of the fields corresponding to different target sub-field information are also different.

[0081] For example, in this scenario, when the detailed data is comments, the comment field in the source data corresponding to each data source identifier can include multiple comments. That is, comments are the target field, corresponding to multiple attribute values. Furthermore, the content of each comment can be stored as subfields, and the attribute values ​​of each subfield can be stored according to the corresponding data storage type.

[0082] For example, when the detailed data in this scenario is an image, the image field in the source data corresponding to each data source identifier can include multiple images. That is, the image serves as the target field, corresponding to multiple attribute values. Furthermore, the content of each image can be stored as a subfield. For example, it can include a subfield indicating the image size, and the attribute value of this subfield can be stored using a data storage type in a data format. It can also include a subfield indicating the reference pixels for the image display; for example, the attribute value of this subfield can be stored using a data storage type in a numeric format. In practical applications, different data storage types can be used to store the attribute values ​​of corresponding subfields in different scenarios, based on the different attribute values ​​to be stored. The data storage type for the attribute values ​​of subfields can also be a dictionary, a string, etc., which will not be elaborated further here.

[0083] In this scenario, selecting at least one target attribute value from multiple attribute values ​​corresponding to the target field information of each source data in the first test data, according to a preset filtering strategy, can be a quantity-customizable attribute value replacement strategy. Specifically, it can include the following two implementation methods:

[0084] The first approach involves selecting M attributes from N attributes based on their identifiers, arranged in ascending or descending order, or randomly, to meet the needs of the testing scenario. For example, using the ascending order customization method, if the original data with ID 1 in the test scenario requires 3 comments, but the actual online data has 10 comments with ID 1, then by specifying the sorting method, such as ascending order, the first 3 comments can be selected from the 10 actual online comments in reverse order to meet the testing requirements.

[0085] The second approach involves customizing rules based on different fields within the attribute values. For example, custom rules can be identified by a set G, where G = [greater than, equal to, less than, not greater than, not less than, not equal to, between two values, includes a specified prefix, includes specified content]. Fields can be identified by a set Z, where Z = [update time, image format, information score, field length]. Then, the total customization rule T = G * Z. This method allows users to filter M items from N values, meeting the needs of testing scenarios. In this example, the image field in the details data is used as an example. If it's a content field, the corresponding Z may not include the image format. Following this method, it's also possible to filter M items from N attribute values.

[0086] In this scenario, the attribute values ​​of the target sub-fields in the target field information of each source data in the first test data are replaced according to a preset attribute value replacement strategy. This ensures that when the attribute values ​​of the target sub-fields corresponding to different data source identifiers are different, since the target field contains nested sub-fields, it can be assumed that the attribute value content of the target field contains at least two formats of different data storage types, such as dictionary, array, string, and number. At this time, attribute value replacement can support different data storage types. The overall structure of attribute values ​​of sub-fields containing different data storage types can be viewed as a tree, and this overall structure can correspond to the attribute value of a certain field. Replacement of any leaf node and parent node of this tree structure is supported. For example, replacing the leaf node a["photo"]["num"][0] = 1 is supported. Replacement of the parent node is also supported, that is, replacing the entire set of attribute values ​​of sub-fields containing different data storage types. For example, replacing the parent node a["photo"] = {"url":"test","num":[2,3,1,4],"score":3} is supported. There are two ways to replace attribute values ​​with target values. The first way is for the user to specify the target value; the tool uses this value directly without making any modifications. The second way is an automated method. The tool automatically generates the target value by allowing the user to specify replacement rules. These rules vary depending on the data storage type of the attribute value.

[0087] For example, if the data storage type corresponding to the attribute value is a string, the tool will randomly generate a string based on the keyword specified by the user.

[0088] If the data storage type corresponding to the attribute value is an array or dictionary, an array set D can be pre-defined. For example, the array set D could be: =[["test1","test2","test3"],["test4","test5"],["test6","test7","tezt78","tezg5"]]. It also supports a set of filtering conditions F, which consists of three conditions: condition 1 is the array length (filtering array values ​​of a specific length in D); condition 2 specifies the array to be selected at index n in D (e.g., if n=2, the second array in D will be selected); and condition 3 randomly selects an array from D. Based on the array set D and the condition set F, an attribute value replacement strategy can be constructed. For example, this method can replace the attribute value of the "image size" subfield within the "image" field in the details data. An array can be randomly selected from the pre-defined array set as the replaced array to identify the image size, thus replacing the attribute value of the "image size" subfield. If the data storage type corresponding to the attribute value is numeric, the customized rule for the attribute value replacement strategy supports Q = [greater than, equal to, less than, not greater than, not less than, not equal to, between two values, not empty, randomly generated]. Based on any of the replacement strategies, the attribute values ​​of numeric subfields can be replaced reasonably and effectively.

[0089] For example, regarding the aforementioned limitations, when replacing the attribute values ​​of the image field in the detailed data of the source data, according to the above embodiments, the image can be directly replaced, or the attribute values ​​corresponding to the subfields under the image field can be replaced, such as the size of the image stored in numeric format, or the reference pixels for image display under the image field can be replaced. Furthermore, according to the above embodiments, the quantity can be directly customized, replacing the number of images under the image field.

[0090] For example, regarding the aforementioned limitations, when replacing attribute values ​​in the comment field of the detailed data in the source data, the quantity can be limited according to the above embodiment, restricting the number of comment entries in the comment field of a single source data entry. Alternatively, an attribute value replacement strategy can be employed simultaneously to replace the attribute value of a target subfield of the comment field in the source data of each data source identifier corresponding to the same POI.

[0091] In this scenario, attribute values ​​can be flexibly and freely replaced in the detailed data of the source data identifier, improving the rationality and validity of the test data, and thus effectively improving the stability and efficiency of the test.

[0092] Scenario 6: When the business data type corresponding to the data attribute information includes the detailed data of the target POI identifier, the data attribute information also includes target field information and lower-level target sub-field information. Correspondingly, step S203 includes: based on the target POI identifier, retrieving the target field information and the data corresponding to the target sub-field information from the detailed data of the first target data corresponding to the target POI identifier from the online storage system, as the first test data. Correspondingly, step S204 includes: filtering at least one target attribute value from multiple attribute values ​​of the fields corresponding to the target field information in the first test data according to a preset filtering strategy; and / or replacing the attribute values ​​of the fields corresponding to the target sub-field information in the first test data according to a preset attribute value replacement strategy.

[0093] The implementation method and effect of this situation can be referred to in the above situation five, and will not be repeated here.

[0094] Scenario 7: When the business data type corresponding to the data attribute information includes intervention data, the data attribute information also includes target field information. In this case, step S203 includes: based on the target POI identifier and the business data type, obtaining the intervention data corresponding to the target POI identifier from the online storage system as the first test data; correspondingly, step S204 includes: replacing the attribute values ​​of the fields corresponding to the target field information in the first test data according to a preset attribute value replacement strategy to obtain the second test data. Here, taking the intervention data including target field information as an example, the data that can be modified in the intervention data are those described in scenarios three to six above. In practical applications, some pre-data may modify relational data, in which case target field information may not be included; please refer to scenarios one and two above for details.

[0095] In other words, intervention data can modify any business data type from scenarios one through six above. Therefore, the attribute value replacement strategy for this intervention data can be based on the business data type to which the modified data belongs, referring to the relevant methods in each of the above scenarios to implement attribute value replacement processing, which will not be elaborated further here. Moreover, using this method, even when the business data type is intervention data, the corresponding test data can be obtained very accurately.

[0096] It should be noted that in practical applications, one type of functional information can correspond to a combination of multiple data attribute information. That is, scenarios one through seven above can be used in any combination based on the attribute information corresponding to the upgraded functional information.

[0097] S206. Test the POI service module based on the second test data written in the offline POI information storage system;

[0098] S207. After the test is completed, based on the target POI identifier, the second test data written in this test in the offline POI information storage system is destroyed.

[0099] In this embodiment, test data needs to be acquired according to steps S201-S205 described above for each test. Since the test data will be modified during the test, it becomes meaningless after the current test is completed. If it is not deleted in time, it may be coupled with other test data, affecting the testing of other test data. Moreover, if the deletion strategy is inappropriate and the test data is not completely deleted, it will also affect the testing of other test data. Based on this, in this embodiment, the second test data corresponding to the target POI identifier in the offline POI information storage system can be destroyed based on the target POI identifier.

[0100] Because, according to the processing method of this embodiment, the test data corresponding to the target POI identifier in the offline POI information storage system is promptly destroyed after each test, all data corresponding to the target POI identifier stored in the offline POI information storage system can be considered as second test data and need to be destroyed promptly. Specifically, this can be determined based on whether each piece of data in the offline POI information storage system corresponds to the target POI identifier. For example, whether the basic data is the basic data of the target POI, or the basic data in the data information corresponding to the data source identifier of the target POI identifier. Another example is whether the detailed data is the detailed data of the target POI, or the detailed data in the data information corresponding to the data source identifier of the target POI identifier. Yet another example is whether the relationship data involves the target POI identifier. And yet another example is whether the intervention data is the intervention data of the target POI. Based on the above methods, all data related to the target POI in the second test data written in the offline POI information storage system for this test can be obtained, and then the obtained data can be destroyed. This destruction method not only allows for the timely recovery of storage space in the offline POI information storage system, improving the management efficiency of storage space. It can also avoid coupling issues in tests with different test cases, effectively improving testing efficiency.

[0101] For example, the testing method of the POI service module in this embodiment can be based on test case during specific testing. For example, the test case can record the request to obtain test data from the online storage system, the test request for the POI service module to call the test data during testing, and the request to destroy the test data corresponding to the target POI identifier used in this test in the offline POI information storage system after testing.

[0102] In addition, the test cases include interface protocols for both the online storage system and the offline POI information storage system. Thus, when retrieving the first test data from the online storage system, information parsing is required based on the interface protocols to construct a request, and after obtaining the information, further parsing is performed to assemble the request body. Similarly, the test cases also include interface protocols for the offline POI information storage system. During database injection, information parsing is performed based on the interface protocols of the offline POI information storage system to write the second test data into the offline POI information storage system according to those protocols.

[0103] Figure 3 This is a schematic diagram illustrating the test data injection process during the testing of a POI service module provided in this embodiment. For example... Figure 3 As shown, execution can be controlled by a master controller and multiple workers.

[0104] For example, the data types involved in this test can be obtained in the master control module, such as... Figure 3 As shown, the data attribute information includes combinations of data attribute information 1, data attribute information 2, ..., data attribute information N. Then, worker1 retrieves the associated information through the target POI identifier. For example, if the attribute information is a target field in the basic data or detail data of the source data identifier, it retrieves the correspondence between the target POI identifier and the corresponding data source identifier, i.e., the UID identifier, based on the target POI identifier. Worker2 parses the information and constructs a data retrieval request based on the interface protocol of the online storage system in the test case. Based on the constructed retrieval request, after retrieving the data corresponding to each data attribute information from the online storage system, it parses the information, assembles the request body, and returns it to the master. Then, worker4 replaces the attribute values ​​of the data corresponding to each data attribute information according to the preset attribute value replacement strategy. Specifically, during replacement, one type of attribute value can be replaced at a time, or multiple data attribute values ​​can be replaced simultaneously to improve the efficiency of attribute value replacement. Worker3 then parses the information based on the interface protocol of the offline POI information storage system and writes the test data with replaced attribute values ​​into the offline POI information storage system.

[0105] During testing, the master controller can control the testing of the POI service module based on test data from the offline POI information storage system. For example, based on the call request of the POI service module in the test case, the master controller can call the POI service module and retrieve test data from the offline POI information storage system to test the test data.

[0106] Finally, based on step S207 of this embodiment, after the test is completed, the test data of this round of testing in the offline POI information storage system can be destroyed based on the target POI identifier to release storage space in a timely manner; and the coupling between different test case instances can be avoided to improve the stability and efficiency of the test.

[0107] The testing method for the POI service module in this embodiment retrieves first test data from the online storage system based on the target POI identifier and data attribute information during each test. Then, based on a preset attribute value replacement strategy corresponding to the data attribute information, the attribute values ​​corresponding to the data attribute information in the first test data are replaced to obtain second test data. Finally, the second test data is written into the offline POI information storage system. This effectively improves the authenticity of the second test data in the offline POI information storage system. Furthermore, due to the attribute value replacement process, the influence of specific attribute values ​​corresponding to data types on the test can be avoided, thus effectively improving the stability of the test. In addition, in this embodiment, the test data in the offline POI information storage system can be promptly destroyed after the test is completed. This releases storage space and avoids coupling between different test case instances, further effectively improving the stability and efficiency of the test.

[0108] Figure 4 This is a schematic diagram based on the third embodiment of this disclosure; as shown Figure 4 As shown, this embodiment provides a testing device 400 for a POI service module, including:

[0109] The acquisition module 401 is used to acquire the target point of interest identifier selected in this test and the functional information of the point of interest service module in this test.

[0110] The determination module 402 is used to determine the data attribute information involved in this test based on the functional information.

[0111] The database filling module 403 is used to perform online-to-offline database filling of test data based on the target point of interest identifier, the data attribute information and the preset attribute value replacement strategy.

[0112] The testing module 404 is used to test the Point of Interest (POI) service module based on the test data after database injection. The testing device 400 for the POI service module in this embodiment achieves the same implementation principle and technical effect as the aforementioned related method embodiments by employing the above-mentioned module. For details, please refer to the descriptions in the aforementioned related method embodiments; further elaboration will not be repeated here.

[0113] Figure 5This is a schematic diagram based on the fourth embodiment of the present disclosure; as shown Figure 5 As shown, this embodiment provides a testing device 500 for a POI service module. Figure 4 Based on the technical solutions of the illustrated embodiments, the technical solutions of this disclosure will be described in further detail. For example... Figure 5 As shown, the testing device 500 for the POI service module in this embodiment includes the above-mentioned... Figure 4 The modules with the same name and function shown are: Acquisition module 501, Determination module 502, Reservoir Processing module 503, and Test module 504.

[0114] like Figure 5 As shown, in one embodiment of this disclosure, the irrigation processing module 503 includes:

[0115] The acquisition unit 5031 is used to acquire the corresponding first test data from the online storage system based on the target interest point identifier and the data attribute information;

[0116] The replacement unit 5032 is used to replace the attribute values ​​corresponding to the data attribute information in the first test data based on the preset attribute value replacement strategy and the data attribute information to obtain the second test data.

[0117] The writing unit 5033 is used to write the second test data into the offline point of interest information storage system.

[0118] Further optionally, in one embodiment of this disclosure, the determining module 502 is configured to:

[0119] Based on the pre-established correspondence between functional information and data attribute information, the data attribute information involved in this test corresponding to the functional information is determined, and the data attribute information includes business data types.

[0120] Further optionally, in one embodiment of this disclosure, the acquisition unit 5031 is used to acquire, based on the target interest point identifier, relational data including the correspondence between the target interest point identifier and at least two data source identifiers, first target data corresponding to the target interest point identifier, and source data corresponding to each of the data source identifiers from the online storage system when the business data type includes relational data, as the first test data;

[0121] The replacement unit 5032 is used to filter the relationship data of the correspondence between the target point of interest identifier and at least two data source identifiers, the first target data corresponding to the target point of interest identifier, and the source data corresponding to each of the filtered data source identifiers from the correspondence between the target point of interest identifier and at least two data source identifiers, as the second test data.

[0122] Further optionally, in one embodiment of this disclosure, the acquisition unit 5031 is used for:

[0123] If the business data type includes relational data, based on the target interest point identifier, relational data including the correspondence between the target interest point identifier and two backup interest point identifiers, as well as the first target data corresponding to the target interest point identifier and the second target data corresponding to each of the backup interest point identifiers are obtained from the online storage system as the first test data;

[0124] The replacement unit 5032 is used to filter the relationship data of the correspondence between the target point of interest identifier and at least one backup point of interest identifier, the first target data corresponding to the target point of interest identifier, and the second target data corresponding to each of the filtered backup point of interest identifiers from the correspondence between the target point of interest identifier and the two backup point of interest identifiers, as the second test data.

[0125] Further optionally, in one embodiment of this disclosure, the acquisition unit 5031 is used for:

[0126] If the business data type includes intervention data, the data attribute information also includes target field information; based on the target point of interest identifier and the business data type, the intervention data corresponding to the target point of interest identifier is obtained from the online storage system as the first test data;

[0127] The replacement unit 5032 is used to replace the attribute values ​​of the fields corresponding to the target field information in the first test data according to the preset attribute value replacement strategy to obtain the second test data.

[0128] Further optionally, in one embodiment of this disclosure, the determining module 502 is configured to:

[0129] The acquisition unit is configured to, if the business data type includes basic data corresponding to the source data identifier, and the data attribute information further includes target field information; acquire at least one data source identifier corresponding to the target interest point identifier based on a preset correspondence between interest point identifiers and at least one data source identifier;

[0130] From the online storage system, obtain the data corresponding to the target field information in the basic data of the source data corresponding to each data source identifier, and use it as the first test data;

[0131] The replacement unit is used to replace the attribute values ​​of the fields corresponding to the target field information of each data source identifier in the first test data according to the preset attribute value replacement strategy, so that the attribute values ​​of the fields corresponding to the target field information of different data source identifiers are different, thereby obtaining the second test data.

[0132] Further optionally, in one embodiment of this disclosure, the acquisition unit 5031 is used for:

[0133] If the business data type includes basic data corresponding to the target point of interest identifier, the data attribute information also includes target field information; based on the target point of interest identifier, the data corresponding to the target field information in the basic data of the first target data corresponding to the target point of interest identifier is obtained from the online storage system and used as the first test data;

[0134] The replacement unit 5032 is used to replace the attribute values ​​of the fields corresponding to the target field information in the first test data according to the preset attribute value replacement strategy to obtain the second test data.

[0135] Further optionally, in one embodiment of this disclosure, the acquisition unit 5031 is used for:

[0136] If the business data type includes detailed data of the source data identifier, the data attribute information also includes target field information and lower-level target sub-field information; based on the preset correspondence between the point of interest identifier and at least one data source identifier, at least one data source identifier corresponding to the target point of interest identifier is obtained;

[0137] From the online storage system, obtain the target field information and the data corresponding to the target subfield information in the detailed data of the source data corresponding to each data source identifier, and use it as the first test data;

[0138] Replacement unit 5032, used for:

[0139] In the first test data, multiple attribute values ​​of the fields corresponding to the target field information of each of the source data are selected according to a preset filtering strategy to filter at least one target attribute value; and / or

[0140] The attribute values ​​of the fields corresponding to the target subfield information in the target field information of each of the source data in the first test data are replaced according to a preset attribute value replacement strategy, so that the attribute values ​​of the fields corresponding to the target subfield information of different data source identifiers are different; and if the target field information of the source data includes multiple target subfield information, the attribute values ​​of the fields corresponding to different target subfield information are also different.

[0141] Further optionally, in one embodiment of this disclosure, the acquisition unit 5031 is configured to, if the business data type includes detailed data of a target point of interest identifier, the data attribute information further includes target field information and lower-level target sub-field information; based on the target point of interest identifier, acquire from the online storage system the data corresponding to the target field information and the target sub-field information in the detailed data of the first target data corresponding to the target point of interest identifier, as the first test data;

[0142] Replacement unit 5032, used for:

[0143] From the first test data, multiple attribute values ​​of the field corresponding to the target field information are filtered according to a preset filtering strategy to select at least one target attribute value; and / or

[0144] The attribute values ​​of the corresponding fields of the target subfield information in the first test data and the target field information are replaced according to a preset attribute value replacement strategy.

[0145] Further optional, such as Figure 5 As shown, in one embodiment of this disclosure, the testing apparatus 500 for the POI service module further includes:

[0146] The destruction module 505 is used to destroy the second test data written into the offline POI information storage system for this test based on the target POI identifier.

[0147] The testing device 500 for the POI service module in this embodiment achieves the same implementation principle and technical effect as the above-mentioned related method embodiments by using the above-mentioned module. For details, please refer to the description of the above-mentioned related method embodiments, which will not be repeated here.

[0148] The acquisition, storage, and application of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0149] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0150] Figure 6A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0151] like Figure 6 As shown, device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 602 or a computer program loaded from storage unit 608 into random access memory (RAM) 603. RAM 603 may also store various programs and data required for the operation of device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0152] Multiple components in device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of monitors, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0153] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as the methods of this disclosure. For example, in some embodiments, the methods of this disclosure may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the methods of this disclosure described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the methods of this disclosure by any other suitable means (e.g., by means of firmware).

[0154] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0155] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0156] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0157] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0158] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0159] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0160] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0161] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A testing method for a point-of-interest (POI) service module, comprising: Obtain the target point of interest identifiers selected for this test, as well as the functional information of the point of interest service module for this test; Based on the aforementioned functional information, the data attribute information involved in this test is determined; the data attribute information is information from the perspective of data storage in the data storage system corresponding to the functional information; the data attribute information includes business data types; the business data types include basic data, detailed data, relational data, or intervention data; Based on the target point of interest identifier, the data attribute information, and the preset attribute value replacement strategy, the online-to-offline database injection process of the test data is carried out. The attribute value replacement strategy is used to replace the attribute values ​​of the data attribute information in the test data during the irrigation process. The point of interest service module was tested based on the test data after the reservoir was filled.

2. The method according to claim 1, wherein, Based on the target point of interest identifier, the data attribute information, and the preset attribute value replacement strategy, online-to-offline database injection of test data is performed, including: Based on the target point of interest identifier and the data attribute information, the corresponding first test data is obtained from the online storage system; Based on the preset attribute value replacement strategy and the data attribute information, the attribute values ​​corresponding to the data attribute information in the first test data are replaced to obtain the second test data. The second test data is written into the offline point of interest information storage system.

3. The method according to claim 2, wherein, Based on the aforementioned functional information, the data attribute information involved in this test is determined, including: Based on the pre-established correspondence between functional information and data attribute information, the data attribute information involved in this test corresponding to the functional information is determined, and the data attribute information includes business data types.

4. The method according to claim 3, wherein, If the business data type includes relational data, based on the target point of interest identifier and the data attribute information, the corresponding first test data is obtained from the online storage system, including: Based on the target point of interest identifier, relational data including the correspondence between the target point of interest identifier and at least two data source identifiers, as well as the first target data corresponding to the target point of interest identifier and the source data corresponding to each of the data source identifiers, are obtained from the online storage system as the first test data; Based on the preset attribute value replacement strategy and the data attribute information, the attribute values ​​corresponding to the data attribute information in the first test data are replaced to obtain the second test data, including: From the correspondence between the target point of interest identifier and at least two data source identifiers, the relationship data of the correspondence between the target point of interest identifier and at least one data source identifier, the first target data corresponding to the target point of interest identifier, and the source data corresponding to each of the filtered data source identifiers are selected as the second test data.

5. The method according to claim 3, wherein, If the business data type includes relational data, based on the target point of interest identifier and the data attribute information, the corresponding first test data is obtained from the online storage system, including: Based on the target point of interest identifier, relationship data including the correspondence between the target point of interest identifier and two backup point of interest identifiers, as well as first target data corresponding to the target point of interest identifier and second target data corresponding to each backup point of interest identifier are obtained from the online storage system as the first test data; Based on the preset attribute value replacement strategy and the data attribute information, the attribute values ​​corresponding to the data attribute information in the first test data are replaced to obtain the second test data, including: From the correspondence between the target point of interest identifier and the two backup point of interest identifiers, the relationship data of the correspondence between the target point of interest identifier and at least one backup point of interest identifier, the first target data corresponding to the target point of interest identifier, and the second target data corresponding to each of the backup point of interest identifiers obtained by filtering are selected as the second test data.

6. The method according to claim 3, wherein, If the business data type includes intervention data, the data attribute information also includes target field information; Based on the target point of interest identifier and the data attribute information, the corresponding first test data is obtained from the online storage system, including: Based on the target point of interest identifier and the business data type, the intervention data corresponding to the target point of interest identifier is obtained from the online storage system and used as the first test data. Based on the preset attribute value replacement strategy and the data attribute information, the attribute values ​​corresponding to the data attribute information in the first test data are replaced to obtain the second test data, including: The attribute values ​​of the fields corresponding to the target field information in the first test data are replaced according to the preset attribute value replacement strategy to obtain the second test data.

7. The method according to claim 3, wherein, If the business data type includes basic data corresponding to the source data identifier, the data attribute information also includes target field information; Based on the target point of interest identifier and the data attribute information, the corresponding first test data is obtained from the online storage system, including: Based on the preset correspondence between point of interest identifiers and at least one data source identifier, obtain at least one data source identifier corresponding to the target point of interest identifier; From the online storage system, obtain the data corresponding to the target field information in the basic data of the source data corresponding to each data source identifier, and use it as the first test data; Based on the preset attribute value replacement strategy, the attribute values ​​corresponding to the data attribute information in the first test data are replaced to obtain the second test data, including: The attribute values ​​of the fields corresponding to the target field information of each data source identifier in the first test data are replaced according to the preset attribute value replacement strategy, so that the attribute values ​​of the fields corresponding to the target field information of different data source identifiers are different, thus obtaining the second test data.

8. The method according to claim 3, wherein, If the business data type includes basic data corresponding to the target point of interest identifier, the data attribute information also includes target field information; Based on the target point of interest identifier and the data attribute information, the corresponding first test data is obtained from the online storage system, including: Based on the target point of interest identifier, the data corresponding to the target field information in the basic data of the first target data corresponding to the target point of interest identifier is obtained from the online storage system and used as the first test data; Based on the preset attribute value replacement strategy, the attribute values ​​corresponding to the data attribute information in the first test data are replaced to obtain the second test data, including: The attribute values ​​of the fields corresponding to the target field information in the first test data are replaced according to the preset attribute value replacement strategy to obtain the second test data.

9. The method according to claim 3, wherein, If the business data type includes detailed data of the source data identifier, the data attribute information also includes target field information and lower-level target sub-field information; Based on the target point of interest identifier and the data attribute information, the corresponding first test data is obtained from the online storage system, including: Based on the preset correspondence between point of interest identifiers and at least one data source identifier, obtain at least one data source identifier corresponding to the target point of interest identifier; From the online storage system, obtain the target field information and the data corresponding to the target subfield information from the detailed data of the source data corresponding to each data source identifier, and use them as the first test data; Based on the preset attribute value replacement strategy, the attribute values ​​corresponding to the data attribute information in the first test data are replaced, including: In the first test data, multiple attribute values ​​of the fields corresponding to the target field information of each of the source data are selected according to a preset filtering strategy to filter at least one target attribute value; and / or The attribute values ​​of the fields corresponding to the target subfield information in the target field information of each of the source data in the first test data are replaced according to a preset attribute value replacement strategy, so that the attribute values ​​of the fields corresponding to the target subfield information of different data source identifiers are different.

10. The method according to claim 3, wherein, If the business data type includes detailed data of the target point of interest identifier, the data attribute information also includes target field information and lower-level target sub-field information; Based on the target point of interest identifier and the data attribute information, the corresponding first test data is obtained from the online storage system, including: Based on the target point of interest identifier, the target field information and the data corresponding to the target sub-field information in the details data of the first target data corresponding to the target point of interest identifier are obtained from the online storage system and used as the first test data; Based on the preset attribute value replacement strategy, the attribute values ​​corresponding to the data attribute information in the first test data are replaced, including: From the first test data, multiple attribute values ​​of the field corresponding to the target field information are filtered according to a preset filtering strategy to select at least one target attribute value; and / or The attribute values ​​of the corresponding fields of the target subfield information in the first test data and the target field information are replaced according to a preset attribute value replacement strategy.

11. The method according to any one of claims 2-10, wherein, Based on the test data after the database filling process, after testing the point of interest service module, the method further includes: Based on the target point of interest identifier, the second test data written into the offline point of interest information storage system for this test is destroyed.

12. A testing apparatus for a point-of-interest (POI) service module, comprising: The acquisition module is used to acquire the target point of interest identifiers selected for this test, as well as the functional information of the point of interest service module for this test. The determination module is used to determine the data attribute information involved in this test based on the functional information; the data attribute information is information from the data storage perspective in the data storage system corresponding to the functional information; the data attribute information includes business data types; the business data types include basic data, detailed data, relational data, or intervention data; The database injection module is used to perform online-to-offline database injection of test data based on the target point of interest identifier, the data attribute information, and the preset attribute value replacement strategy. The attribute value replacement strategy is used to replace the attribute values ​​of the data attribute information in the test data during the irrigation process. The testing module is used to test the Point of Interest service module based on the test data after database injection.

13. The apparatus according to claim 12, wherein, The irrigation processing module includes: The acquisition unit is used to acquire the corresponding first test data from the online storage system based on the target point of interest identifier and the data attribute information; The replacement unit is used to replace the attribute values ​​corresponding to the data attribute information in the first test data based on the preset attribute value replacement strategy and the data attribute information to obtain the second test data. The writing unit is used to write the second test data into the offline point of interest information storage system.

14. The apparatus according to claim 13, wherein, The determining module is used for: Based on the pre-established correspondence between functional information and data attribute information, the data attribute information involved in this test corresponding to the functional information is determined, and the data attribute information includes business data types.

15. The apparatus according to claim 14, wherein, The acquisition unit is used for: If the business data type includes relational data, based on the target interest point identifier, relational data including the correspondence between the target interest point identifier and at least two data source identifiers, as well as the first target data corresponding to the target interest point identifier and the source data corresponding to each of the data source identifiers are obtained from the online storage system as the first test data; The replacement unit is used to filter the relationship data of the correspondence between the target point of interest identifier and at least two data source identifiers, the first target data corresponding to the target point of interest identifier, and the source data corresponding to each of the filtered data source identifiers from the correspondence between the target point of interest identifier and at least two data source identifiers, as the second test data.

16. The apparatus according to claim 14, wherein, The acquisition unit is used for: If the business data type includes relational data, based on the target interest point identifier, relational data including the correspondence between the target interest point identifier and two backup interest point identifiers, as well as first target data corresponding to the target interest point identifier and second target data corresponding to each of the backup interest point identifiers are obtained from the online storage system as the first test data; The replacement unit is used to filter the relationship data of the correspondence between the target point of interest identifier and at least one backup point of interest identifier, the first target data corresponding to the target point of interest identifier, and the second target data corresponding to each of the filtered backup point of interest identifiers from the correspondence between the target point of interest identifier and the two backup point of interest identifiers, as the second test data.

17. The apparatus according to claim 14, wherein, The acquisition unit is used for: If the business data type includes intervention data, the data attribute information also includes target field information; based on the target point of interest identifier and the business data type, the intervention data corresponding to the target point of interest identifier is obtained from the online storage system as the first test data; The replacement unit is used to replace the attribute values ​​of the fields corresponding to the target field information in the first test data according to the preset attribute value replacement strategy to obtain the second test data.

18. The apparatus according to claim 14, wherein, The acquisition unit is used for: If the business data type includes basic data corresponding to the source data identifier, the data attribute information also includes target field information; based on the preset correspondence between the point of interest identifier and at least one data source identifier, at least one data source identifier corresponding to the target point of interest identifier is obtained; From the online storage system, obtain the data corresponding to the target field information in the basic data of the source data corresponding to each data source identifier, and use it as the first test data; The replacement unit is used to replace the attribute values ​​of the fields corresponding to the target field information of each data source identifier in the first test data according to the preset attribute value replacement strategy, so that the attribute values ​​of the fields corresponding to the target field information of different data source identifiers are different, thereby obtaining the second test data.

19. The apparatus according to claim 14, wherein, The acquisition unit is used for: If the business data type includes basic data corresponding to the target point of interest identifier, the data attribute information also includes target field information; based on the target point of interest identifier, the data corresponding to the target field information in the basic data of the first target data corresponding to the target point of interest identifier is obtained from the online storage system and used as the first test data; The replacement unit is used to replace the attribute values ​​of the fields corresponding to the target field information in the first test data according to the preset attribute value replacement strategy to obtain the second test data.

20. The apparatus according to claim 14, wherein, The acquisition unit is used for: If the business data type includes detailed data of the source data identifier, the data attribute information also includes target field information and lower-level target sub-field information; based on the preset correspondence between the point of interest identifier and at least one data source identifier, obtain at least one data source identifier corresponding to the target point of interest identifier; From the online storage system, obtain the target field information and the data corresponding to the target subfield information from the detailed data of the source data corresponding to each data source identifier, and use them as the first test data; The replacement unit is used for: In the first test data, at least one target attribute value is selected from the multiple attribute values ​​of the fields corresponding to the target field information of each source data according to a preset filtering strategy. and / or The attribute values ​​of the fields corresponding to the target subfield information in the target field information of each of the source data in the first test data are replaced according to a preset attribute value replacement strategy, so that the attribute values ​​of the fields corresponding to the target subfield information of different data source identifiers are different.

21. The apparatus according to claim 14, wherein, The acquisition unit is used for: If the business data type includes detailed data of the target's subordinate point of interest identifiers, the data attribute information also includes target field information and target sub-field information; Based on the target point of interest identifier, the target field information and the data corresponding to the target sub-field information in the details data of the first target data corresponding to the target point of interest identifier are obtained from the online storage system and used as the first test data; The replacement unit is used for: From the first test data, multiple attribute values ​​of the field corresponding to the target field information are filtered according to a preset filtering strategy to select at least one target attribute value; and / or The attribute values ​​of the corresponding fields of the target subfield information in the first test data and the target field information are replaced according to a preset attribute value replacement strategy.

22. The apparatus according to any one of claims 13-21, wherein, The device further includes: The destruction module is used to destroy the second test data written into the offline point of interest information storage system for this test based on the target point of interest identifier.

23. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-11.

24. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-11.

25. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-11.

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