CN114185770A - Method and device for generating test data, computer equipment and storage medium - Google Patents

Abstract

The application relates to a method, an apparatus, a computer device and a storage medium for generating test data. The method comprises the following steps: acquiring a data set corresponding to the test data, and generating a classification template based on a service scene corresponding to the data set, wherein the classification template comprises classification information; acquiring service scene identifications corresponding to the classification information, respectively acquiring field sets corresponding to the service scene identifications, and combining the field sets to obtain a scene template; establishing a corresponding relation between the classification template and the scene template, and combining the classification template and the scene template according to the corresponding relation to obtain a target template, wherein the target template comprises classification information and fields to be filled; and when a test data generation instruction is received, generating test data according to the field to be filled, wherein the test data corresponds to the classification information. By adopting the method, the classification template, the scene template and the field combination can be shared, the dependence of workers on professional service personnel is simplified, the efficiency of test data preprocessing is improved, and the test efficiency is further improved.

Description

Method, apparatus, computer equipment and storage medium for generating test data

technical field

The present application relates to the technical field of software testing, and in particular, to a method, apparatus, computer equipment and storage medium for generating test data.

Background technique

With the development of software testing technology, software testing technology has emerged, and software testing is based on test data. Testers need to prepare a large amount of test data during the testing process, and use these prepared test data to test each business. However, most testers have limited knowledge and cannot understand the processes of all businesses in the world. Therefore, in the cross-business system data When preparing, other business testers are required to assist, and their respective data preparation scripts/operations cannot be shared.

In the traditional technology, cross-domain test data is prepared by manual means, and the respective data preparation scripts/operations cannot be shared. At the same time, because developers, UAT acceptance personnel and other staff need test data when doing some testing and verification, and they are not very clear about the data flow of the business, they need to frequently find business personnel to assist in data creation, resulting in a decrease in overall efficiency.

SUMMARY OF THE INVENTION

Based on this, it is necessary to provide a method, an apparatus, a computer device and a computer-readable storage medium for generating test data that can provide cross-domain in response to the above technical problems.

In a first aspect, the present application provides a method for generating test data. The method includes:

acquiring a data set corresponding to the test data, and generating a classification template based on a business scenario corresponding to the data set, where the classification template includes classification information, and the classification information is used to classify the business scenario;

acquiring the business scenario identifier corresponding to the classification information, respectively acquiring the field sets corresponding to the business scenario identifiers, and combining the field sets to obtain a scenario template, where the scenario template corresponds to the business scenario identifier;

establishing a corresponding relationship between the classification template and the scene template, and combining the classification template and the scene template according to the corresponding relationship to obtain a target template, where the target template includes classification information and fields to be filled;

When a test data generation instruction is received, test data is generated according to the to-be-filled field, and the test data corresponds to the classification information.

In one embodiment, the generating a classification template based on the business scenario corresponding to the data set includes:

Obtain the business description data associated with the classification identification and the classification identification from the data set;

Generate the classification identification field based on the classification identification to obtain the classification identification field of the classification template;

A category description field of the category template is generated based on the business description data associated with the category identifier.

In one embodiment, the classification identification field is filled based on the classification identification, and the generation of the classification description field of the classification template based on the business description data associated with the classification identification includes:

Obtain the account type corresponding to the classification identifier, and determine the field attribute information of the classification description field based on the account type;

The classification description field is set according to the field attribute information, and the field to be filled for generating the test data is obtained.

In one of the embodiments, the generating test data according to the fields to be filled includes:

Obtain the test environment information and target classification information carried by the test data generation instruction;

Generate a test environment corresponding to the test data based on the test environment information;

In the test environment, a target template is obtained based on the target classification information, and the test data is generated based on fields to be filled in the target template.

In one embodiment, the combination of the fields of the field set to obtain the scene template includes:

obtaining a first business requirement corresponding to the business scenario identifier, and obtaining a basic data template based on the first business requirement, where the basic data template is generated according to the second business requirement;

Combining the fields of the basic data template obtained corresponding to the first business requirement to obtain a scene template corresponding to the first business requirement.

In one embodiment, the combination of fields of the basic data template obtained corresponding to the first business requirement to obtain the scene template corresponding to the first business requirement includes:

According to the field attributes of the basic data template, the data corresponding to the basic data template is generated, the data corresponding to the basic data template is detected, and it is determined that the data corresponding to the basic data template meets the preset conditions of the basic data template; and / or,

Obtain field attributes corresponding to the first business requirement based on the scene template corresponding to the first business requirement, generate data corresponding to the first business requirement according to the field attributes corresponding to the first business requirement, and generate data corresponding to the first business requirement. It is determined that the data corresponding to the first service requirement meets the preset conditions of the scene template corresponding to the first service requirement.

In a second aspect, the present application also provides an apparatus for generating test data. The device includes:

a classification template obtaining module, configured to obtain a data set corresponding to the test data, and generate a classification template based on a business scenario corresponding to the data set, where the classification template includes classification information, and the classification information is used to classify the business scenario;

A scenario template obtaining module, configured to obtain the business scenario identifier corresponding to the classification information, obtain the field sets corresponding to the business scenario identifiers respectively, combine the field sets to obtain a scenario template, the scenario template and the business scenario identifier Corresponding;

A target template generation module, configured to establish a corresponding relationship between the classification template and the scene template, and combine the classification template and the scene template according to the corresponding relationship to obtain a target template, where the target template includes classification information and to-be-to-be fill field;

The test data generation module is configured to generate test data according to the to-be-filled field when receiving the test data generation instruction, and the test data corresponds to the classification information.

In a third aspect, the present application also provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

acquiring a data set corresponding to the test data, and generating a classification template based on a business scenario corresponding to the data set, where the classification template includes classification information, and the classification information is used to classify the business scenario;

acquiring the business scenario identifier corresponding to the classification information, respectively acquiring the field sets corresponding to the business scenario identifiers, and combining the field sets to obtain a scenario template, where the scenario template corresponds to the business scenario identifier;

establishing a corresponding relationship between the classification template and the scene template, and combining the classification template and the scene template according to the corresponding relationship to obtain a target template, where the target template includes classification information and fields to be filled;

When a test data generation instruction is received, test data is generated according to the to-be-filled field, and the test data corresponds to the classification information.

In a fourth aspect, the present application also provides a computer-readable storage medium. The computer-readable storage medium has a computer program stored thereon, and when the computer program is executed by the processor, the following steps are implemented:

acquiring a data set corresponding to the test data, and generating a classification template based on a business scenario corresponding to the data set, where the classification template includes classification information, and the classification information is used to classify the business scenario;

acquiring the business scenario identifier corresponding to the classification information, respectively acquiring the field sets corresponding to the business scenario identifiers, and combining the field sets to obtain a scenario template, where the scenario template corresponds to the business scenario identifier;

establishing a corresponding relationship between the classification template and the scene template, and combining the classification template and the scene template according to the corresponding relationship to obtain a target template, where the target template includes classification information and fields to be filled;

When a test data generation instruction is received, test data is generated according to the to-be-filled field, and the test data corresponds to the classification information.

In a fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the following steps:

acquiring a data set corresponding to the test data, and generating a classification template based on a business scenario corresponding to the data set, where the classification template includes classification information, and the classification information is used to classify the business scenario;

acquiring the business scenario identifier corresponding to the classification information, respectively acquiring the field sets corresponding to the business scenario identifiers, and combining the field sets to obtain a scenario template, where the scenario template corresponds to the business scenario identifier;

establishing a corresponding relationship between the classification template and the scene template, and combining the classification template and the scene template according to the corresponding relationship to obtain a target template, where the target template includes classification information and fields to be filled;

When a test data generation instruction is received, test data is generated according to the to-be-filled field, and the test data corresponds to the classification information.

The above-mentioned method, device, computer equipment, storage medium and computer program product for generating test data obtain a data set corresponding to the test data, and generate a classification template based on a business scenario corresponding to the data set, wherein the classification template includes classification information, and the classification template includes classification information. The classification information is used to classify the business scenarios, so as to facilitate the selection of composite scenarios; obtain the business scenario identifiers corresponding to the classification information, respectively obtain the field sets corresponding to the business scenario identifiers, and combine the field sets to obtain a scenario template, the The scene template corresponds to the business scene identifier, which improves the efficiency of producing the scene template; establishes the corresponding relationship between the classification template and the scene template, and combines the classification template and the scene template according to the corresponding relationship to obtain the target template, the target template includes classification information and fields to be filled, and a target template is constructed to realize efficient value transfer; when receiving a test data generation instruction, test data is generated according to the fields to be filled, and the test data and the classification Corresponding information, when generating test data, select the target template according to the classification information to reduce user operations, and the combination of classification templates, scene templates and fields can be shared across fields, simplifying the user's dependence on business personnel, and improving the efficiency of test data preprocessing , thereby improving the test efficiency.

Description of drawings

1 is an application environment diagram of a method for generating test data in one embodiment;

2 is a schematic flowchart of a method for generating test data in one embodiment;

3 is a schematic flowchart of generating a classification template in one embodiment;

4 is a schematic flowchart of generating a classification description field in another embodiment;

5 is a schematic flowchart of generating a scene template in one embodiment;

6 is a schematic flowchart of template field detection in another embodiment;

7 is a schematic flow chart of generating test data in one embodiment;

8 is a schematic flowchart of a tester performing personal data testing in one embodiment;

9 is a schematic structural diagram of an apparatus for generating test data in one embodiment;

Figure 10 is a diagram of the internal structure of a computer device in one embodiment.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

The method for generating test data provided by the embodiment of the present application can be applied to the application environment shown in FIG. 1 . The terminal 102 communicates with the server 104 through the network. The data storage system may store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network server.

The server 104 obtains a data set corresponding to the test data, and generates a classification template based on a business scenario corresponding to the data set, where the classification template includes classification information, and the classification information is used to classify the business scenario; Business scenario identifiers, respectively acquiring the field sets corresponding to the business scenario identifiers, and combining the field sets to obtain a scenario template, where the scenario templates correspond to the business scenario identifiers; establishing a relationship between the classification template and the scenario template Corresponding relationship, combining the classification template and the scene template according to the corresponding relationship to obtain a target template, where the target template includes classification information and fields to be filled; when receiving the test data generation instruction, according to the fields to be filled Test data is generated, the test data corresponding to the classification information. The terminal 102 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, IoT devices and portable wearable devices, and the IoT devices can be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. . The portable wearable device may be a smart watch, a smart bracelet, a head-mounted device, or the like. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

In one embodiment, as shown in FIG. 2, a method for generating test data is provided, and the method is applied to the server 104 in FIG. 1 as an example for description, including the following steps:

Step 202: Acquire a data set corresponding to the test data, and generate a classification template based on a business scenario corresponding to the data set, where the classification template includes classification information, and the classification information is used to classify the business scenario.

The data set corresponding to the test data is the data set used to classify the scene state. It refers to aggregating the data to be processed, and the obtained data set conforms to the standard of the data to be processed, and the data set is used to represent an object or other organization or structure with referential meaning. The data set can be a data set of a certain customer type, or a set with a certain characteristic or a certain business, and can also be a specific customer name or a general customer set. If two customers have real-time communication software services, they can be set as the same type of customers, and both customers with real-time communication software services can belong to this category; further, if both customers belong to real-time communication software In the same field of communication software and the same scale, these two customers can be set as the same type of customers, and customers in the same field and scale can also belong to this category; further, if for a specific customer, also It can be divided according to each project group or project type of the customer to obtain a specific data set.

Business scenarios refer to specific business scenarios in a certain field or some related fields, which are the basis for realizing the operation of the overall business system. Business division in different fields. For example, when applying specific user operation behaviors for classification, "real-name registration of mailbox users" can be used as a business scenario, and "real-name registration of bank users" can also be used as a business scenario.

In an optional embodiment, the process of generating a classification template is the classification management of business scenarios, and the information used for classifying and managing business scenarios is classification information, and the classification information may be classification identifiers, or may be related to classification identifiers. Description information; classification information is information based on the set identifier of the data set corresponding to the test data. The description information of the set identifier can also be added as the classification information, and other fields to be tested can also be added to indicate the corresponding fields of the field. The data is static, and there is no need to generate test data according to the scenario. The classification information is set according to related services of the data set corresponding to the test data. For example: a set category is a broad first customer category with instant messaging software business and mailbox business, then the business scenario corresponding to the first customer category includes instant messaging software business and mailbox business; another set category is customer needs The second customer category tested, the second customer category only has two business scenarios of "user registration" and "user login", then the business scenarios corresponding to the second customer category set are "user registration" and "user login" two services Scenes.

In an optional embodiment, the process of generating a classification template is to fill in information such as each customer type, and this process lays a foundation for combining scene templates, which facilitates selection of composite scenes, and realizes multiple reuse of scene template data. Customer type and other information to meet customized needs.

Step 204: Acquire a business scenario identifier corresponding to the classification information, respectively acquire a field set corresponding to the business scenario identifier, and combine the field sets to obtain a scenario template.

The business scenario identifier corresponds to the scenario template and is used to represent a specific business scenario template. A business scenario can have multiple scenario templates, and multiple scenario templates of the same business scenario can be sorted according to numerical values, and corresponding names can also be designed. Setting the business scenario ID corresponding to the scenario template instead of setting the scenario ID based on the business scenario can improve fine-grainedness and enhance compatibility. Targeted scenario templates can be set for different customers, and when scheduling scenario templates, there are The advantages of efficiency and convenience are conducive to the debugging of multiple scene templates.

In an optional embodiment, the field set refers to the basic data template, which is the smallest unit of the function of carrying basic services to generate test data, and provides operation functions such as script execution, interface invocation, database operation, etc. Basic data template for business description data. The field set corresponding to the business scenario identifier refers to generating a basic data template for generating the business scenario identifier. Further, the field set is a template for generating basic data of business description data, and the basic data of business description data is the data that can be generated through a single interface call or a single table/dependent multi-table operation on a single business system, such as User data generated after user registration, customer data generated after user real-name, single-category credit data; the minimum unit data combination with strong coupling between multiple business systems can also be defined as basic business description data. For example: in the process of generating an account of a real-time communication software, account data can be generated through "registration", and "registration" corresponds to one or a series of operation instructions, and the corresponding column operation instructions are encapsulated into a basic data template as a whole.

In an optional embodiment, combining the field set is to reorganize each basic data template. During the reorganization process, you can choose to use data cleaning to remove duplicate fields. In an optional embodiment, a basic combination of data such as SQL statements and interface calls can be used, or multiple basic combination methods can be used for compounding and encapsulation to obtain a scene template. The step of generating a scene template is to assemble a plurality of basic data templates to form a business link operation instruction, including operation instructions corresponding to one or more basic data templates. For example, a real-time communication software has the property of storing change, and can generate a communication account with change. It can generate the relevant data of the communication account through a basic data template, and generate the relevant data of change scheduling through another data basic template. Optionally, the basic data template used to generate the communication account may include an operation instruction corresponding to "registration"; the basic template used to generate change scheduling may include "identity authentication", "binding bank card" and "recharge". corresponding operating instructions.

In an optional embodiment, the field set is used as the basic data of the template, and the fields are combined to construct a scene template, so as to improve the efficiency of producing the scene template. It further improves the reuse frequency of templates, and can better combine data across fields, realize cross-field data reorganization, and facilitate testers to perform data testing across business scenarios.

Step 206 , establishing a correspondence between the classification template and the scene template, and combining the classification template and the scene template according to the corresponding relationship to obtain a target template, where the target template includes classification information and fields to be filled.

In an optional embodiment, the establishment of the corresponding relationship between the classification template and the scene template can be carried out in a variety of ways, which can use data association, or establish data dependencies, and can also use other mappings. relationship, you can use combination, aggregation and other methods. A corresponding relationship between the classification template and the scene template is established, so that the values of the classification template and the scene template can be transmitted.

In an optional embodiment, the classification template and the scene template are combined according to the corresponding relationship, and the fields in the classification template and the scene template can be directly combined, and the combined template can be used as the target template to save costs; The fields in the template and scene template are transferred to another data storage location, and a new template is obtained. Using this new template as the target template is beneficial to increase data diversity and fine-grainedness, and avoid data confusion and program failures.

In an optional embodiment, the target template includes filled fields and fields to be filled, and the filled fields are at least used to represent classification information, and can also be used to represent that the fields are not used to generate test data. The field is only used to represent classification information, which means that most of the fields in the template are used to generate test data; and if the filled fields are not only used to represent classification information but also to represent some specific information, these specific information are not used. Just because the test data process is currently in progress does not mean that this specific information will never be involved in the test data process. As a result, the test data corresponding to the target template can be better controlled, and the generation process of the test data can be controlled in a high-fine-grained manner, so as to achieve the effect of accurately generating the test data. In addition, based on the recursive divide-and-conquer strategy, the target template can be quickly understood. Individual fields, no matter which field has a problem, can be quickly diagnosed.

Further, after generating the target template corresponding to the test data, it is not necessary to generate the corresponding test data immediately, but one or more templates in the classification template, the scene template, and the target template are stored in a data storage device such as a database. , the target template in the data storage device can still be debugged, and the user can send instructions through the terminal to set and debug one or more templates in the classification template, scene template, and target template to meet the needs of customers , to generate the required test data as high quality as possible. In an optional implementation manner, the target template can also be bound to be used for environmental data binding targets, environmental data cleaning templates, and environmental data restoration templates, so that users can better reuse target templates; optionally , the environmental data cleaning template is used to delete the generated data to ensure that it can be regenerated and used again next time; the environmental data restoration template is used to restore the test data to a certain state.

Step 208, when receiving the test data generation instruction, generate test data according to the fields to be filled, and the test data corresponds to the classification information.

In an optional embodiment, the process of generating test data according to the field to be filled is generated according to the field attribute of the field to be filled, and the test data that meets the requirements of the field attribute is generated, and the field attribute can be the data type of some information of the data. and data length, etc.; for example: when a field to be filled is student ID, ID number, phone number, etc., at least numerical test data will be generated according to this information, and the data length can be further limited.

In an optional embodiment, the process of generating test data according to the fields to be filled is the process of generating test data according to the field identifiers such as the field names of the fields to be filled, and the mapping can be performed according to the corresponding relationship according to the field identifiers, and according to The data generation rules mapped to generate test data. For example, when the field identifier of a field to be filled represents identity information such as student number, the generation rule of test data for identity information such as student number can be obtained according to the corresponding relationship, and the specific test data can be generated by using this generation rule.

In the above method for generating test data, a data set corresponding to the test data is obtained, and a classification template is generated based on a business scenario corresponding to the data set, the classification template includes classification information, and the classification information is used to classify the business scenarios, so as to facilitate the selection of compound scenarios; obtain the classification information For the corresponding business scenario identifiers, obtain the field sets corresponding to the business scenario identifiers respectively, and combine the field sets to obtain a scenario template. The scenario templates correspond to the business scenario identifiers to improve the efficiency of producing scenario templates; establish the correspondence between the classification templates and the scenario templates, Combine the classification template and the scene template according to the corresponding relationship to obtain the target template. The target template includes the classification information and the fields to be filled, and the target template is constructed to realize efficient value transfer; when the test data generation instruction is received, the test data is generated according to the fields to be filled. The test data corresponds to the classification information. When generating the test data, a target template is selected according to the classification information, so as to reduce the user operation and improve the generation efficiency.

In one embodiment, focusing on the overall structure of the classification template, as shown in Figure 3, generating the classification template based on the business scenario corresponding to the data set includes:

Step 302: Acquire the service description data associated with the classification identifier and the classification identifier from the data set.

The classification identifier is used to characterize classification information and classification templates. It can be identification information such as customer ID used to identify customers, or identification information such as customer category ID used to summarize user categories. The identification information can be the representation itself, It may also include some data or information associated with the identification itself; wherein the identification may be a combination of one or more of the data types such as string, integer, floating point and so on.

In an optional embodiment, the classification identifier and the service description data associated with the classification identifier can be directly obtained from the data set; the classification identifier can also be obtained only from the data set, according to the corresponding relationship between the classification identifier and at least one service description data. , to obtain service description data; further, a plurality of service description data may be obtained from the data set, and after these service description data are aggregated, a classification identifier is set for the aggregated data.

Step 304: Generate a classification identification field based on the classification identification, and obtain a classification identification field of the classification template.

Step 306 , based on the business description data associated with the classification identifier, generate a classification description field of the classification template.

There is a corresponding relationship between the classification identification field and the classification description field. The classification identification field can correspond to multiple classification description fields, and changing the combination of the classification description fields can also be mapped to the corresponding classification identification field. The classification identification field and the classification description field can have the same points, and they all belong to the classification template; the classification identification field and the classification description field can have complementary properties, and they can complement each other through the corresponding relationship.

In an optional embodiment, in the process of generating the corresponding field based on the classification identifier and the service description data, the means is not specifically limited, and the two may be the same or different. For specific implementation methods, they can construct their respective fields according to the field attributes, or realize this process according to data association, data nesting, etc.

In this embodiment, the classification template is constructed by the classification identification and the classification description data, and the classification identification and the classification description data are both related and complementary, which can improve the compatibility of the classification template, realize the reuse of data across fields, and support This feature to efficiently generate test data.

In one embodiment, emphasis is placed on describing the difference between the classification identification field and the classification description field, so that the structure of the classification template is clearer. The steps are shown in Figure 4. The classification identification field is filled based on the classification identification, and the business associated The taxonomy description fields of the description data generation taxonomy template include:

Step 402: Acquire the account type corresponding to the classification identifier, and determine the field attribute information of the classification description field based on the account type.

In an optional embodiment, in the process of acquiring the account type corresponding to the classification identifier, a corresponding data set is obtained according to the corresponding relationship between the classification identifier and a single account; it is also possible to summarize multiple accounts, and the same type of account All use the same or the same group of classification identifiers; among them, the account type can be the customer type.

In an optional embodiment, in the process of determining the field attribute information of the classification description field, data extraction is performed according to the business type corresponding to the account type, and then the corresponding field attribute information is obtained, and the field attribute information is used in the generation test. The data acts as restrictive data such as labels or conditional expressions, so that users can directly generate data in various fields.

Step 404: Set the classification description field according to the field attribute information, and obtain the field to be filled for generating the test data.

In this embodiment, the classification description field is set according to the account type, and testing can be performed based on the customer type, which can bring greater convenience to cross-domain customers, especially for developers and UAT acceptance personnel to do some testing and verification When they need to test data, and they are not very clear about the data flow of the business, after using the technical solution of this embodiment, there is no need to frequently ask testers to assist in data creation, resulting in higher overall efficiency.

In one embodiment, focusing on the generation of scene templates, it is constructed using basic data templates, as shown in Figure 5, combining field sets to obtain scene templates including:

Step 502: Obtain a first business requirement corresponding to the business scenario identifier, and obtain a basic data template based on the first business requirement, and the basic data template is generated according to the second business requirement.

Both the first business requirement and the second business requirement are requirements generated for specific business scenarios, and both have basic data templates that can be shared. The difference between the first business requirement and the second business requirement is that the scene template corresponding to the second business requirement has been generated, and the scene template corresponding to the second business requirement can be disassembled into multiple basic data templates; the corresponding , the scene template corresponding to the first business requirement has not been formed.

In an optional embodiment, acquiring the basic data template based on the first business requirement is obtained according to multiple basic data template identifiers in the first business requirement; ” and “user real name”, the corresponding basic data templates are obtained according to the two basic data template identifiers. After the basic data templates are combined, the scene template corresponding to the scene identifier can be obtained, and the scene Templates correspond to business scenario identifiers.

Step 504: Combine the fields of the basic data template obtained corresponding to the first business requirement to obtain a scene template corresponding to the first business requirement.

In an optional embodiment, the fields of the basic data template are discrete, and the fields of each basic data template need to be combined to obtain the required scene template; in an optional embodiment, each basic data template If there are duplicate fields, the duplicate fields need to be removed. Before, during or after the field combination of the basic data template, the overlapping fields should be removed.

In this embodiment, scene templates based on different business requirements are reused, so that the basic data templates in the scene templates can be reused again, and users can adjust the scene templates by themselves to realize the construction of scene templates corresponding to various business requirements, so as to improve the It is good to reuse these basic data templates across domains to generate the required data more efficiently.

In one embodiment, as shown in Figure 6, focusing on the detection of template fields, combining the fields of the basic data template obtained corresponding to the first business requirement to obtain the scene template corresponding to the first business requirement includes:

Step 602, according to the operation instructions corresponding to the fields of the basic data template, generate data corresponding to the basic data template, detect the data corresponding to the basic data template, and determine that the data corresponding to the basic data template meets the preset conditions of the basic data template;

and / or,

Step 604: Obtain field operation instructions corresponding to the first business requirement based on the scene template corresponding to the first business requirement, and generate data corresponding to the first business requirement according to the field operation instructions corresponding to the first business requirement. The data is detected, and it is determined that the data corresponding to the first service requirement meets the preset conditions of the scene template corresponding to the first service requirement.

In this embodiment, on the one hand, data detection can be performed according to a basic data template, and on the other hand, a scene template can be used for data detection. If the generated detection data meets corresponding preset conditions, a scene template can be generated. Through this method, the application can control the data scheduling in a high-level and fine-grained manner, and can analyze from the two dimensions of the basic data template and the scene template. If there is a problem with the basic data template, you only need to debug the basic data template. Only if there is a problem with the scene template, you only need to debug the process of combining the scene template and the basic data template. As a result, debugging can be performed more quickly to improve the efficiency of test data generation.

In one embodiment, as shown in FIG. 7 , generating test data according to the fields to be filled includes:

Step 702: Acquire test environment information and target classification information carried by the test data generation instruction.

Step 704: Generate a test environment corresponding to the test data based on the test environment information.

In an optional implementation manner, the test environment is obtained by modeling according to the test environment information, and is oriented to the relationship between the hardware performance and the computing power of the business system under different configurations; it can also be generated by synchronous use of clusters and modeling. The test environment corresponding to the test data.

Step 706 , in the test environment, obtain the target template based on the target classification information, and generate test data based on the fields to be filled in the target template.

In this embodiment, the test environment information and the target classification information are integrated to obtain the test data generation instruction, which can be generated with one click by selecting the customer type, which simplifies the complexity of data preparation, improves the efficiency of data preparation, and is more efficient Conducting automated tests lays the groundwork.

Each of the above embodiments has its corresponding focus, and each embodiment can be freely combined. In order to better describe the overall technical solution of the present application, a specific embodiment will be used to analyze and describe a specific description scene. . In this embodiment, testers need to prepare a large amount of test data during the testing process to test various scenarios, while testers can only quickly and efficiently prepare test data for specific fields, but data preparation based on cross-business systems requires With the assistance of other business testers, their respective data preparation scripts/operations cannot be shared, and in order to realize the business process of a test scenario, multiple business systems are required to form links, and tests are prepared on each system so that the business process can go through. Data, these test data are the combination of various basic business data, in this embodiment, the test data can be named as test scenario data, including case/rule data matched on platforms such as Mock.

In this embodiment of data testing, the problem to be solved is to enable business testers, developers, and UAT acceptance personnel to quickly and efficiently generate test data required by various business scenarios. In order to solve this problem, business scenarios can be managed according to the type of customer data and managed by selecting scenario templates. In order to facilitate the construction of scenario templates, a data base template can be set, and the data base template can be used as a data generation script. Test data can be provided for automated tests.

Different from the discussion of the functions in the above-mentioned embodiments, the present application will mainly focus on the overall operation flow and operation method. The method includes two parts: a template building step and a test data generating step, and the template building steps mainly include: defining a customer type template belonging to a classification template, creating a basic data template, combining the basic data templates to obtain a scene template, and binding the template. The process of obtaining the target template from the scene template and the customer type template.

1) Define customer type template based on fields. This process is equivalent to building a classification template, which can be regarded as defining the basic customer information fields, which are used to manage the key test data information of customer types, such as mobile phone numbers, ID numbers, bank card numbers, and addresses.

2) The process of creating a basic data template. This process is to template the data preparation scripts that the business testers usually work in, and template the scripts for the smallest unit of business data preparation in each business system to obtain a script preparation template and script preparation. Templates can be considered as atomic data templates. An atomic data template can aggregate multiple fields through SQL and/or interface calls. For example, when the basic data template corresponds to the process of "registered user data preparation", the basic data template can be used. Named as registration data template, including the two fields of "name" parameter and "mobile phone number" parameter; and when the basic data template corresponds to the process of "user real-name data preparation", the basic data template can be named as real-name data template, including There are three fields: "Mobile phone number" parameter, "ID card number" parameter and "Bank card number" parameter.

3) The process of combining basic data templates to obtain scene templates. In this process, multiple basic data templates are assembled based on business requirements, and data transfer between template data is done so as to form a common target template for cross-business link scenarios. The target template is also a script template. Equivalent to a molecular template. If it is considered that the registration data template and the real-name data template are combined, a registered and real-name account data can be generated for data testing.

After the scene template is obtained, it is also necessary to set the parameters in the scene template, that is, the variable field information in the template can be placed in the template parameters as variable parameters to generate test data or adjust the fields. The input parameter field name should be consistent with or correspond to the parameter field name defined in the classification template to realize data transmission.

After setting the parameters in the scene template, you can also select the debugging data template and execute according to the scene template: you can directly debug based on the basic data template or the scene data template. After debugging normally generates valid and accurate test data, set the template status to for release. The published templates can be used by users normally, or bound by customer type templates such as classified templates to obtain target templates.

4) Bind the scene template and the customer type template to obtain the target template. It mainly classifies and manages the data of various business scenarios, and binds the customer type to the scenario template published in step 3), so that users can easily find the business scenario data that needs to be generated, and quickly generate test data.

Before generating the target template, according to whether the scene template corresponding to the customer type template is released, determine whether the customer type template is available, and set the customer data fields required by the customer type template and their corresponding field attributes, such as: which fields are marked It is a fixed value of the customer type and cannot be changed, and includes an identification field for determining the customer type, such as an ID field.

After defining the field properties of the customer type template, you can set the parameters, set the default value for the business fields required by the customer type, set the default value for the identification field that uniquely determines the customer type, and set the default value or some random value for other fields. Generate value. After setting the parameters of the customer type template, bind the configured customer type template to the scene template to obtain the target template. The target template can also choose whether to bind the data cleaning template or the data restoration template according to the requirements.

Correspondingly, after having the target template, test data can be generated, and the required test data can be directly generated after the terminal where the user is located sends out the test data generation instruction. Specifically, the steps of generating test data include:

1) The user enters the program interface such as the page of the test data generation webpage through the terminal, selects the customer type on the program interface, and selects the test environment, and can directly generate the test data of this type in the corresponding test environment with one click.

2) If you need to generate batch test data, you can select the customer type and then set the number of generated data to generate test data in batches

3) Change the default data generation: If the default value of some variable fields is not suitable for adjustment after selecting the customer type, you can enter the default field data page to modify and then generate environmental data.

4) When the customer type data is created based on the test environment, the progress status and the execution of the template steps are displayed in real time. If the execution is wrong, you can easily view the reason for the failure of the analysis execution based on the front-end interface.

Therefore, in this embodiment, test data can be generated by selecting a customer type with one click, which simplifies the complexity of data preparation and improves the efficiency of data preparation; the test data preparation script is shared to solve the difficulty of data preparation across business systems ; Enable non-business testers (developers who are not familiar with the business/UAT acceptance personnel) to quickly generate the test data they want and provide test data for the execution of automated test scripts.

It should be understood that, although the steps in the flowcharts involved in the above embodiments are sequentially displayed according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order, and these steps may be performed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but may be executed at different times. The order of execution of these steps or stages is also not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the steps or stages in the other steps.

Based on the same inventive concept, an embodiment of the present application also provides an apparatus for generating test data for implementing the above-mentioned method for generating test data. The implementation solution for solving the problem provided by the device is similar to the implementation solution described in the above method, so the specific limitations in one or more embodiments of the device for generating test data provided below may refer to the above for generating test data. The limitation of the method is not repeated here.

In one embodiment, as shown in FIG. 9, a device for generating test data is provided. The device includes: a classification template acquisition module 902, a scene template acquisition module 904, a target template generation module 906, and a test data generation module 908: in:

A classification template obtaining module 902, configured to obtain a data set corresponding to the test data, and generate a classification template based on a business scenario corresponding to the data set, where the classification template includes classification information, and the classification information is used to classify the business scenario;

The scene template obtaining module 904 is configured to obtain a business scene identifier corresponding to the classification information, obtain a field set corresponding to the business scene identifier, and combine the field sets to obtain a scene template, and the scene template corresponds to the business scene identifier;

The target template generation module 906 is configured to establish a corresponding relationship between the classification template and the scene template, and combine the classification template and the scene template according to the corresponding relationship to obtain a target template, where the target template includes classification information and fields to be filled;

The test data generation module 908 is configured to generate test data according to the fields to be filled when receiving the test data generation instruction, and the test data corresponds to the classification information.

In an optional embodiment, the classification template obtaining module 902 includes: a data extraction unit, a first identification field obtaining unit, and an identification description field obtaining unit, wherein:

a data extraction unit, used to obtain the business description data associated with the classification identifier and the classification identifier from the data set;

a first identification field obtaining unit, configured to generate a classification identification field based on the classification identification, and obtain the classification identification field of the classification template;

The identification description field obtaining unit is used for generating the classification description field of the classification template based on the business description data associated with the classification identification.

In an optional embodiment, the identification description field acquisition unit includes: an attribute acquisition subunit and a field setting subunit;

The attribute obtaining subunit is used to obtain the account type corresponding to the classification identifier, and determine the field attribute information of the classification description field based on the account type;

The field setting subunit is used to set the classification description field according to the field attribute information, and obtain the field to be filled for generating the test data.

In an optional embodiment, the test data generation module 908 includes: an instruction acquisition unit, an environment generation unit and a test data generation unit, wherein:

The instruction acquisition unit is used to acquire the test environment information and target classification information carried by the test data generation instruction;

The environment generation unit is used to generate the test environment corresponding to the test data based on the test environment information;

The test data generating unit is used to obtain the target template based on the target classification information in the test environment, and generate test data based on the fields to be filled in the target template.

In an optional embodiment, the scene template obtaining module 904 includes a business requirement obtaining unit and a scene template combining unit, wherein:

a business requirement obtaining unit, configured to obtain a first business requirement corresponding to the business scenario identifier, and obtain a basic data template based on the first business requirement, and the basic data template is generated according to the second business requirement;

The scene template combining unit is configured to combine the fields of the basic data template obtained corresponding to the first business requirement to obtain the scene template corresponding to the first business requirement.

In an optional embodiment, the scene template combining unit includes: a first detection subunit, and/or a second detection subunit; wherein,

The first detection subunit is used to generate data corresponding to the basic data template according to the field operation instructions of the basic data template, to detect the data corresponding to the basic data template, and to determine that the data corresponding to the basic data template meets the preset conditions of the basic data template ;and / or,

The second detection sub-unit is configured to obtain an operation instruction corresponding to the first service requirement based on the scene template corresponding to the first service requirement, generate data corresponding to the first service requirement according to the operation instruction corresponding to the first service requirement, and perform an analysis on the first service requirement. The data corresponding to the demand is detected, and it is determined that the data corresponding to the first business demand meets the preset conditions of the scene template corresponding to the first business demand.

Each module in the above-mentioned apparatus for generating test data may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

In one embodiment, a computer device is provided, and the computer device may be a server, and its internal structure diagram may be as shown in FIG. 10 . The computer device includes a processor, memory, and a network interface connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The nonvolatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the execution of the operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store test data, and/or, to store templates, and the stored templates are used to generate test data. The network interface of the computer device is used to communicate with an external terminal through a network connection. The computer program, when executed by a processor, implements a method of generating test data.

Those skilled in the art can understand that the structure shown in FIG. 10 is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied. Include more or fewer components than shown in the figures, or combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is also provided, including a memory and a processor, where a computer program is stored in the memory, and the processor implements the steps in the foregoing method embodiments when the processor executes the computer program.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, implements the steps in the foregoing method embodiments.

In one embodiment, a computer program product is provided, including a computer program, which implements the steps in each of the above method embodiments when the computer program is executed by a processor.

It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all Information and data authorized by the user or fully authorized by the parties.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage In the medium, when the computer program is executed, it may include the processes of the above-mentioned method embodiments. Wherein, any reference to a memory, a database or other media used in the various embodiments provided in this application may include at least one of a non-volatile memory and a volatile memory. Non-volatile memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetic variable memory (Magnetoresistive Random Memory) Access Memory, MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory may include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration and not limitation, the RAM may be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM). The database involved in the various embodiments provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a blockchain-based distributed database, etc., but is not limited thereto. The processors involved in the various embodiments provided in this application may be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, data processing logic devices based on quantum computing, etc., and are not limited to this.

The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features It is considered to be the range described in this specification.

The above-mentioned embodiments only represent several embodiments of the present application, and the descriptions thereof are relatively specific and detailed, but should not be construed as a limitation on the scope of the patent of the present application. It should be pointed out that for those skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the scope of protection of the present application should be determined by the appended claims.

Claims (10)

1. A method of generating test data, the method comprising:

acquiring a data set corresponding to test data, and generating a classification template based on a service scene corresponding to the data set, wherein the classification template comprises classification information, and the classification information is used for classifying the service scene;

acquiring service scene identifications corresponding to the classification information, respectively acquiring field sets corresponding to the service scene identifications, and combining the field sets to obtain a scene template, wherein the scene template corresponds to the service scene identifications;

establishing a corresponding relation between the classification template and the scene template, and combining the classification template and the scene template according to the corresponding relation to obtain a target template, wherein the target template comprises classification information and fields to be filled;

and when a test data generation instruction is received, generating test data according to the field to be filled, wherein the test data corresponds to the classification information.

2. The method of claim 1, wherein generating a classification template based on the traffic scenario corresponding to the data set comprises:

acquiring a classification identifier and service description data associated with the classification identifier from the data set;

generating the classification identification field based on the classification identification to obtain the classification identification field of the classification template;

and generating a classification description field of the classification template based on the service description data associated with the classification identification.

3. The method of claim 2, wherein the class identifier field is populated based on the class identifier, and wherein generating the class description field of the class template based on the traffic description data associated with the class identifier comprises:

acquiring an account type corresponding to the classification identification, and determining field attribute information of the classification description field based on the account type;

and setting the classification description field according to the field attribute information to obtain a field to be filled for generating the test data.

4. The method of claim 1, wherein generating test data according to the field to be filled comprises:

acquiring test environment information and target classification information carried by the test data generation instruction;

generating a test environment corresponding to the test data based on the test environment information;

and in the test environment, acquiring a target template based on the target classification information, and generating the test data based on the field to be filled of the target template.

5. The method of any of claims 1 to 4, wherein the combining the field sets to obtain the scene template comprises:

acquiring a first service requirement corresponding to the service scene identifier, and acquiring a basic data template based on the first service requirement, wherein the basic data template is generated according to a second service requirement;

and combining the fields of the basic data template acquired corresponding to the first service requirement to obtain a scene template corresponding to the first service requirement.

6. The method according to claim 5, wherein the combining fields of the basic data template acquired corresponding to the first service requirement to obtain the scene template corresponding to the first service requirement includes:

generating data corresponding to the basic data template according to the operation instruction corresponding to the field of the basic data template, detecting the data corresponding to the basic data template, and determining that the data corresponding to the basic data template meets the preset condition of the basic data template; and/or the presence of a gas in the gas,

acquiring a field operation instruction corresponding to a first service requirement based on the scene template corresponding to the first service requirement, generating data corresponding to the first service requirement according to the field operation instruction corresponding to the first service requirement, detecting the data corresponding to the first service requirement, and determining that the data corresponding to the first service requirement meets the preset condition of the scene template corresponding to the first service requirement.

7. An apparatus for generating test data, the apparatus comprising:

the classification template acquisition module is used for acquiring a data set corresponding to the test data and generating a classification template based on a service scene corresponding to the data set, wherein the classification template comprises classification information, and the classification information is used for classifying the service scene;

a scene template obtaining module, configured to obtain service scene identifiers corresponding to the classification information, respectively obtain field sets corresponding to the service scene identifiers, and combine the field sets to obtain a scene template, where the scene template corresponds to the service scene identifiers;

the target template generation module is used for establishing a corresponding relation between the classification template and the scene template, and combining the classification template and the scene template according to the corresponding relation to obtain a target template, wherein the target template comprises classification information and fields to be filled;

and the test data generation module is used for generating test data according to the field to be filled when a test data generation instruction is received, wherein the test data corresponds to the classification information.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.

9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 6 when executed by a processor.

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