CN114185770A

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

Info

Publication number: CN114185770A
Application number: CN202111386569.2A
Authority: CN
Inventors: 刘涛; 张红; 张飞; 高希洋; 纳颖泉; 刘伟
Original assignee: Merchants Union Consumer Finance Co Ltd
Current assignee: Merchants Union Consumer Finance Co Ltd
Priority date: 2021-11-22
Filing date: 2021-11-22
Publication date: 2022-03-15

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 and device for generating test data, computer equipment and storage medium

Technical Field

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

Background

With the development of software testing technology, software testing technology has emerged, and software testing is performed based on test data. In the process of testing, a large amount of test data needs to be prepared by testers, each business is tested through the prepared test data, most testers have limited knowledge and cannot know the flow of all businesses in the world, so that other business testers are needed to assist in data preparation of the cross-business system, and respective data preparation scripts/operations cannot be shared.

In the conventional technology, cross-domain test data is prepared through manual means, and respective data preparation scripts/operations cannot be shared. Meanwhile, as developers, UAT (user authentication and maintenance) inspection personnel and other working personnel need to test data when performing some test verifications, the data flow of the services is not clear, and the service personnel need to be frequently found to assist in the number making, the overall efficiency is reduced.

Disclosure of Invention

In view of the above, there is a need to provide a method, an apparatus, a computer device and a computer readable storage medium for generating test data across domains.

In a first aspect, the present application provides a method of generating test data. The method comprises the following steps:

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.

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

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.

In one embodiment, the class identifier field is populated based on the class identifier, and the generating the class description field of the class template based on the traffic description data associated with the class identifier includes:

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.

In one embodiment, the generating test data according to the field to be filled includes:

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.

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

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.

In one embodiment, the obtaining the scene template corresponding to the first service requirement by combining the fields of the basic data template obtained corresponding to the first service requirement includes:

generating data corresponding to the basic data template according to the field attribute 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 attribute corresponding to a first service requirement based on a scene template corresponding to the first service requirement, generating data corresponding to the first service requirement according to the field attribute 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.

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

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.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:

In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:

In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:

According to the method, the device, the computer equipment, the storage medium and the computer program product for generating the test data, the data set corresponding to the test data is obtained, the classification template is generated based on the service scene corresponding to the data set, the classification template comprises classification information, and the classification information is used for classifying the service scene so as to be convenient for selecting a composite scene; acquiring service scene identifiers corresponding to the classification information, respectively acquiring field sets corresponding to the service scene identifiers, and combining the field sets to obtain a scene template, wherein the scene template corresponds to the service scene identifiers, so that the efficiency of producing the scene template is improved; establishing a corresponding relation between the classification template and the scene template, 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 constructing the target template to realize efficient value transmission; when a test data generation instruction is received, test data are generated according to the fields to be filled, the test data correspond to the classification information, when the test data are generated, a target template is selected according to the classification information, user operation is reduced, the classification template, the scene template and the field combination can be shared across the fields, dependence of users on service personnel is simplified, the efficiency of test data preprocessing is improved, and then the test efficiency is improved.

Drawings

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

FIG. 2 is a flow diagram illustrating a method for generating test data in one embodiment;

FIG. 3 is a flow diagram illustrating the generation of a classification template in one embodiment;

FIG. 4 is a schematic diagram of a process for generating a class description field in another embodiment;

FIG. 5 is a flow diagram illustrating the generation of a scene template in one embodiment;

FIG. 6 is a flow diagram illustrating the detection of template fields in another embodiment;

FIG. 7 is a schematic flow chart illustrating the generation of test data in one embodiment;

FIG. 8 is a schematic flow chart illustrating the process of a tester performing personal data testing in one embodiment;

FIG. 9 is a block diagram of an apparatus for generating test data according to one embodiment;

FIG. 10 is a diagram showing an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

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

The server 104 acquires a data set corresponding to the test data, and generates 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. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, and the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart car-mounted devices, and the like. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, and the like. The server 104 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.

In one embodiment, as shown in fig. 2, a method for generating test data is provided, which is illustrated by applying the method to the server 104 in fig. 1, and includes the following steps:

step 202, 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 includes classification information, and the classification information is used for classifying the service scene.

The data set corresponding to the test data is a data set for classifying the scene state. The method is characterized in that data to be processed are aggregated, and an obtained data set conforms to a standard of the data to be processed, wherein the data set is used for representing a certain object or other organizations or structures with reference meanings. The data set may be a data set of a certain client type, a set with a certain characteristic or a certain service, or a specific client name or a general-purpose client set. If two clients both have the service of the real-time communication software, the two clients can be set as the same type of client, and the clients with the service of the real-time communication software can belong to the category; further, if two clients both belong to the same field of real-time communication software and have the same scale, the two clients can be set as the same type of client, and the clients in the same field and scale can also belong to the same category; further, if a specific client is concerned, the data can be divided according to each item group or item type of the client to obtain a specific data set.

The service scenario refers to a scenario for a specific service in a certain field or some related fields, which is a basis for implementing the operation of the whole service system, and the service scenario may be a specific user operation behavior, or may be matched with service division in different fields in economics. For example, when a specific user operation behavior is applied to the division, the "real name registration of a mailbox user" may be used as a service scenario, and the "real name registration of a bank user" may also be used as a service scenario.

In an optional embodiment, the process of generating the classification template is classification management of the service scenario, and the information for the classification management of the service scenario is classification information, which may be a classification identifier or description information related to the classification identifier; the classification information is information based on a set identifier of a data set corresponding to the test data, description information of the set identifier can be added to serve as classification information, other fields to be tested can be added to indicate that data corresponding to the fields are static, and the test data does not need to be generated according to scenes. The classification information is set according to the related service of the data set corresponding to the test data. For example: one set class is a broad first client class which has real-time communication software service and mailbox service, and the service scene corresponding to the first client class comprises the real-time communication software service and the mailbox service; and another certain set type is a second client type which needs to be tested by the client, the second client type only has two service scenes of 'user registration' and 'user login', and the service scenes corresponding to the second client type set are two service scenes of 'user registration' and 'user login'.

In an optional embodiment, the process of generating the classification template is to fill information such as each client type, and the process lays a foundation for combining the scene template, so that a composite scene is convenient to select, multiple multiplexing of scene template data is realized, and customized requirements are met through the information such as the client type.

And 204, 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.

The service scene identifier is corresponding to the scene template and is used for representing the specific service scene template. A service scene may have a plurality of scene templates, and the plurality of scene templates of the same service scene may be sorted according to numerical values, or corresponding names may be designed respectively. The method has the advantages that the service scene identification corresponding to the scene template is set, the scene identification is not set based on the service scene, the fine granularity can be improved, the compatibility is enhanced, the scene template with pertinence can be set for different clients, the method has the advantages of high efficiency and convenience in scheduling the scene template, and the debugging of a plurality of scene templates is facilitated.

In an optional embodiment, the field set refers to a basic data template, which is a minimum unit of a function of carrying basic services to generate test data, and provides operation functions such as script execution, interface call, database operation, and the like, and is a basic data template for generating service description data. And the field set corresponding to the service scene identifier refers to generating a basic data template corresponding to the service scene identifier. Further, the field set is a template for generating basic data of the service description data, the basic data of the service description data is data that can be generated by single interface call or single table/dependent multi-table operation on a single service 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 of strong coupling between multiple service systems can also be defined as basic service description data. For example: in the generation process of a certain real-time communication software account, account data can be generated through registration, the registration corresponds to one or a series of operation instructions, and the corresponding column operation instructions are integrally packaged into a basic data template.

In an alternative embodiment, the field sets are combined, that is, the respective basic data templates are recombined, and during the process of recombination, a data cleaning means can be selected to remove the repeated fields. In an optional embodiment, a scene template can be obtained by using a basic combination mode of data such as SQL statements and interface calls, or by using a plurality of basic combination modes for compounding and packaging. And generating a scene template, namely assembling a plurality of basic data templates to form a service link operation instruction, wherein the service link operation instruction comprises operation instructions corresponding to one or more basic data templates. For example: the real-time communication software has the attribute of storing change, can generate a communication account with the change, and can generate related data of the communication account through one basic data template and generate related data of change scheduling through another basic data template. Optionally, the basic data template for generating the communication account may include an operation instruction corresponding to "registration"; the basic template for generating change scheduling can include operation instructions corresponding to 'identity authentication', 'bank card binding' and 'recharge'.

In an optional embodiment, the field set is used as basic data of the template, and the fields are combined to construct the scene template, so that the efficiency of producing the scene template is improved. The reuse frequency of the template is further improved, data combination can be better carried out in a cross-field mode, cross-field data recombination is achieved, and data testing is conveniently carried out by testers in a cross-business scene.

And step 206, 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.

In an optional embodiment, the establishing of the corresponding relationship between the classification template and the scene template may be implemented in various ways, and may use a data association way, a data dependency relation, other mapping relations, or a combination or aggregation way. And establishing a corresponding relation between the classification template and the scene template, so that the numerical 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, the fields in the classification template and the scene template can be directly combined, and the combined template is used as a target template, so that the cost is saved; the fields in the classification template and the scene template can be transmitted to another data storage position to obtain a new template, and the new template is used as a target template, so that the diversity and the fine granularity of data are increased, and the data confusion and the program fault are avoided.

In an optional embodiment, the target template includes a filled field and a field to be filled, the filled field is used for at least characterizing the classification information and can also be used for characterizing that the field is not used for generating the test data, if the filled field is used for only characterizing the classification information, the filled field indicates that the multi-digit segment in the template is used for generating the test data; whereas if the populated fields are used to characterize not only the classification information but also certain specific information, that specific information is not used in the currently ongoing test data flow, does not mean that specific information is never involved in the test data flow. Therefore, the test data corresponding to the target template can be better controlled, the generation process of the test data can be controlled at high fine granularity, the effect of accurately generating the test data is realized, in addition, all fields of the target template can be quickly known on the basis of strategies such as recursive divide-and-conquer, and the like, and the field can be quickly diagnosed no matter which field has a problem.

Further, after the target template corresponding to the test data is generated, the corresponding test data is not necessarily generated immediately, but one or more templates of the classification template, the scene template, and the target template may be stored in a data storage device such as a database, and the target template in the data storage device may still be debugged, and the user may send an instruction through the terminal to set and debug one or more templates of the classification template, the scene template, and the target template, so as to meet the requirements of the customer and generate the required test data with the highest quality. In an optional implementation manner, the target template may further be bound with a template for binding the environmental data with the target, cleaning the environmental data, and restoring the environmental data, so that the user can better reuse the target template; optionally, the environment data cleaning template is used for deleting the generated data to ensure that the data can be regenerated and reused next time; and restoring the environment data to the template, wherein the test data is restored to a certain state.

And step 208, 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.

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 test data conforming to the specification of the field attribute is generated, wherein the field attribute can be the data type, the data length and the like of some information of the data; for example: when a field to be filled is information such as a study number, an identification number, a telephone number and the like, numerical test data can be generated at least according to the information, and the data length can be further limited.

In an optional embodiment, the process of generating the test data according to the field to be filled is a process of generating the test data according to field identifiers such as a field name of the field to be filled, and the test data may be generated according to the mapping relation according to the field identifiers and according to the mapped data generation rule. For example: when the field identifier of a certain field to be filled represents identity information such as a school number, a generation rule of test data of the identity information such as the school number can be obtained according to the corresponding relationship, and the specific test data is generated by using the generation rule.

In the method for generating the test data, a data set corresponding to the test data is obtained, and a classification template is generated based on a service scene corresponding to the data set, wherein the classification template comprises classification information which is used for classifying the service scene so as to be convenient for selecting a composite scene; acquiring service scene identifications corresponding to the classification information, respectively acquiring field sets corresponding to the service scene identifications, combining the field sets to obtain a scene template, wherein the scene template corresponds to the service scene identifications, and the efficiency of producing the scene template is improved; establishing a corresponding relation between the classification template and the scene template, 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 constructing the target template to realize efficient value transmission; when a test data generation instruction is received, test data are generated according to the fields to be filled, the test data correspond to the classification information, and when the test data are generated, a target template is selected according to the classification information, so that user operation is reduced, and generation efficiency is improved.

In one embodiment, focusing on the overall construction of the classification template, as shown in fig. 3, generating the classification template based on the traffic scenario corresponding to the data set includes:

step 302, obtaining the classification identification and the service description data associated with the classification identification from the data set.

The classification identifier is used for representing classification information and a classification template, and can be identification information such as a client ID and the like used for identifying a client, or identification information such as a client category ID and the like used for summarizing a user category, and the identification information can represent the identifier per se, or can comprise some data or information associated with the identifier per se; the identifier may be one or more of a character string, an integer, a floating point, and the like.

In an optional embodiment, the service description data associated with the class identifier and the class identifier may be directly obtained from the data set; or only obtaining the classification identification from the data set, and obtaining the service description data according to the corresponding relation between the classification identification and at least one service description data; further, a plurality of service description data may be acquired from the data set, and after the service description data are aggregated, a classification identifier is set for the aggregated data.

And 304, generating a classification identification field based on the classification identification to obtain the classification identification field of the classification template.

Step 306, based on the service description data associated with the classification identifier, a classification description field of the classification template is generated.

The classification identification field and the classification description field are in corresponding relation, the classification identification field can correspond to a plurality of classification description fields, and the change of the combination mode of the classification description field can also be mapped to the corresponding classification identification field. The classification identification field and the classification description field can have the same point, and both belong to a classification template; the class identification field and the class description field may have complementary properties, which may be complemented by a correspondence.

In an optional embodiment, in the process of generating the corresponding field based on the classification identifier and the service description data, the means thereof is not particularly limited, and the two may be the same or different. For a specific implementation means, their respective fields may be constructed according to the field attributes, or the process may be implemented according to data association, data nesting, and the like.

In the embodiment, the classification template is constructed by the classification identification and the classification description data, and the classification identification and the classification description data have correlation and can be complemented, so that the compatibility of the classification template can be improved, the data multiplexing is realized across fields, and the function of efficiently generating the test data is supported.

In one embodiment, the step of describing the difference between the class identifier field and the class description field with emphasis to make the structure of the class template clearer is shown in fig. 4, where the class identifier field is populated based on the class identifier, and the step of generating the class description field of the class template based on the traffic description data associated with the class identifier includes:

step 402, obtaining the account type corresponding to the classification identifier, and determining 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 the single account; a plurality of account numbers can also be induced, and the same type of account numbers are identified by the same or the same group of groups; the account type may be a 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 service type corresponding to the account type, so as to obtain corresponding field attribute information, and the field attribute information is used as limiting data such as a label or a conditional expression when generating test data, so that a user can directly generate data in each field.

And step 404, setting a classification description field according to the field attribute information to obtain a field to be filled for generating the test data.

In the embodiment, the classification description field is set according to the account number type, testing can be performed based on the client type, great convenience can be brought to cross-field clients, particularly, data needs to be tested when some testing verification is performed on developers and UAT (user authentication and maintenance) acceptance staff, and the data flow of services is not clear.

In one embodiment, focusing on the generation of the scene template, which is constructed using the basic data template, as shown in fig. 5, combining the field sets to obtain the scene template includes:

step 502, a first service requirement corresponding to the service scene identifier is obtained, and a basic data template is obtained based on the first service requirement, wherein the basic data template is generated according to a second service requirement.

The first service requirement and the second service requirement are requirements generated aiming at specific service scenes, and both have basic data templates which can be shared. The difference between the first service requirement and the second service requirement is that a scene template corresponding to the second service requirement is generated, and the scene template corresponding to the second service requirement can be disassembled into a plurality of basic data templates; correspondingly, the scene template corresponding to the first service requirement is not formed.

In an optional embodiment, the basic data template is obtained based on the first service requirement, and is obtained according to a plurality of basic data template identifications in the first service requirement; for example: when the first service requirement comprises two basic data template identifications used for representing a 'registered user' and a 'user real name', corresponding basic data templates are respectively obtained according to the two basic data template identifications, and after the basic data templates are combined, a scene template corresponding to the scene identification can be obtained, wherein the scene template corresponds to the service scene identification.

And 504, 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.

In an optional embodiment, the fields of the basic data template are discrete, and the fields of the basic data templates need to be combined to obtain the required scene template; in an alternative embodiment, the duplicate fields of each basic data template are removed, and the overlapped fields are removed before, during or after the fields of the basic data template are combined.

In this embodiment, the scene templates based on different service requirements are multiplexed, so that the basic data templates in the scene templates are multiplexed again, and a user can adjust the scene templates by himself to construct the scene templates corresponding to various service requirements, thereby multiplexing the basic data templates across the fields better and generating the required data more efficiently.

In an embodiment, as shown in fig. 6, focusing on the detection of the template field, and combining the 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:

step 602, 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,

step 604, acquiring a field operation instruction corresponding to the 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.

In this embodiment, on one hand, data detection may be performed according to the basic data template, and on the other hand, data detection may be performed using the scene template, and if the generated detection data meets the corresponding preset condition, the scene template may be generated. By the means, the control data can be scheduled at high granularity, analysis can be carried out from two dimensions of the basic data template and the scene template, if the basic data template has a problem, only the basic data template needs to be debugged, and if only the scene template has a problem, only the process of combining the scene template and the basic data template needs to be debugged. Therefore, debugging can be carried out more quickly, and the efficiency of test data generation is improved.

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

step 702, obtaining test environment information and target classification information carried by the test data generation instruction.

Step 704, generating a test environment corresponding to the test data based on the test environment information.

In an optional implementation mode, the test environment is obtained by modeling according to test environment information and faces to the relationship between hardware performance and service system computing capacity under different configurations; and generating a test environment corresponding to the test data in a mode of synchronous use of clustering and modeling.

Step 706, in the testing environment, a target template is obtained based on the target classification information, and testing data is generated based on the field to be filled of the target template.

In the embodiment, the test environment information and the target classification information are integrated to obtain the test data generation instruction, and the test data generation instruction can be generated by selecting the client type and one key, so that the complexity of data preparation is simplified, the efficiency of data preparation is improved, and a foundation is laid for more efficiently carrying out automatic tests.

The above embodiments have corresponding emphasis points, and the embodiments can be freely combined, and in order to better describe the overall technical solution of the present application, a specific embodiment will be used to perform analysis and description in a specific description scenario. In this embodiment, a tester needs to prepare a large amount of test data to test each scenario in a test process, and the tester can only prepare test data for a specific field quickly and efficiently, but data preparation based on a cross-service system needs to be assisted by other service testers, respective data preparation scripts/operations cannot be shared, and to implement a service flow of a certain test scenario, a plurality of service systems are required to form a link, and test data prepared on each system for the service flow to be able to go through is a combination of each basic service data.

Under this embodiment of data testing, the difficult problem to be solved is: service testers, developers and UAT (user authentication and maintenance) acceptance personnel can quickly and efficiently generate test data required by each service scene. In order to solve the problem, a service scene can be managed according to the type of the client data, and a scene template is selected for management, and in order to construct the scene template, a data basic template can be set and used as data to generate a script mode, so that test data can be provided for automatic testing.

In distinction to the discussion of the effects of the above embodiments, the present application will focus primarily on the overall operational flow and method of operation. The method comprises two parts of template building step and test data generation step, wherein the template building step mainly comprises the following steps: defining a customer type template belonging to the classification template, creating a basic data template, combining the basic data templates to obtain a scene template, and binding the scene template and the customer type template to obtain a target template.

1) A customer type template is defined based on the fields. This process is equivalent to building a classification template, which may be considered as a customer information field defining the basis for managing customer type-critical test data information, such as: mobile phone number, identification card number, bank card number, address, etc.

2) Creating a basic data template, namely templating a data preparation script in the ordinary work of a service tester, templating the script prepared by minimum unit service data in each service system to obtain a script preparation template, wherein the script preparation template can be regarded as an atomic data template, and one atomic data template can be called by SQL and/or an interface to aggregate various fields, for example, when the basic data template corresponds to the flow of 'registered user data preparation', the basic data template can be named as a registered data template and comprises two fields of 'name' parameters and 'mobile phone number' parameters; when the basic data template corresponds to the process of 'user real name data preparation', the basic data template can be named as a real name data template and comprises three fields of 'mobile phone number' parameter, 'identification card number' parameter and 'bank card number' parameter.

3) And combining the basic data templates to obtain a scene template. In the process, a plurality of basic data templates are assembled based on service requirements, data transmission among template data is well done, so that a universal target template of a cross-service link scene is formed, and the target template belongs to a script template and is equivalent to a molecular template. If the enrollment data template is considered to be combined with the real-name data template, then an enrollment and real-name account data may be generated for data testing.

After the scene template is obtained, the parameter pieces in the scene template need to be set, that is, the variable field information in the template can be used as variable parameters to be placed in the template parameters for generating test data or adjusting the fields, and the transmitted parameter field names are kept consistent with or correspond to the parameter field names defined in the classification template, so that data transmission is realized.

After setting the parameter pieces in the scene template, the debugging data template can be selected, and the following steps are executed according to the scene template: the debugging can be directly carried out based on the basic data template or the scene data template, and after effective and accurate test data is normally generated by debugging, the template state is set to be issued. The issued template can be used by a user normally or bound by client type templates such as a classification template and the like to obtain a target template.

4) And binding the scene template and the client type template to obtain a target template. The data of various service scenes are classified and managed, and the client types are bound with the scene templates released in the step 3), so that a user can conveniently and rapidly find the service scene data to be generated and rapidly generate test data.

Before generating the target template, according to whether the scenario template corresponding to the client type template is published, determining whether the client type template is available, and setting client data fields and corresponding field attributes required by the client type template, for example: the fields are marked as fixed values of the client type and are not changeable and modifiable, and an identification field, such as an ID field, for determining the client type is included.

After defining the field attribute of the client type template, parameter setting can be carried out, default value setting is carried out on the service field required by the client type, default value setting is carried out on the identification field which uniquely determines the client type, and default value or some randomly generated values can be set on other fields. After the parameters of the client type template are set, the configured client type template is bound with a scene template to obtain a target template, and the target template can select whether to bind a data cleaning template or a data restoring template according to requirements.

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

1) a user enters program interfaces such as pages of the test data generation webpage through the terminal, selects a client type on the program interfaces, selects a test environment, and can directly generate the test data of the type in the corresponding test environment by one key.

2) If the batch test data needs to be generated, the client type can be selected and then the generated data number is set to generate the test data in batch

3) Change default data generation: if some variable field default values are not suitable for adjustment after the client type is selected, the environment data generation can be carried out after the default field data page is modified.

4) When the client type data is created based on the test environment, the progress status and the execution condition of the template step are displayed in real time. If the execution is wrong, the reason for the analysis execution failure can be conveniently checked based on the front-end interface.

Therefore, in the embodiment, the test data can be generated by selecting the client type and one key, so that the complexity of data preparation is simplified, and the efficiency of data preparation is improved; test data preparation scripts are shared, and the difficulty of preparing data by a cross-service system is solved; therefore, non-service testers (developers/UAT (user interface Unit) inspection personnel unfamiliar with services) can quickly generate the test data required by the testers and provide the test data for the execution of the automatic test script.

It should be understood that, although the steps in the flowcharts related to the embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the present application further provides a device for generating test data, which is used for implementing the method for generating test data mentioned above. The implementation scheme for solving the problem provided by the apparatus is similar to the implementation scheme described in the above method, so specific limitations in one or more embodiments of the apparatus for generating test data provided below may refer to the limitations in the above method for generating test data, and are not described herein again.

In one embodiment, as shown in FIG. 9, there is provided an apparatus for generating test data, the apparatus comprising: 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: wherein:

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 service scenario corresponding to the data set, where the classification template includes classification information, and the classification information is used to classify the service scenario;

a scene template obtaining module 904, 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;

a target template generating module 906, 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 a field to be filled;

the test data generating module 908 is configured to generate test data according to the field to be filled when receiving the test data generating instruction, where the test data corresponds to the classification information.

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

the data extraction unit is used for acquiring the classification identifier and the service description data associated with the classification identifier from the data set;

the first identification field acquisition unit is used for generating a classification identification field based on the classification identification to obtain the classification identification field of the classification template;

and the identification description field acquisition unit is used for generating a classification description field of the classification template based on the service description data associated with the classification identification.

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

the attribute acquisition subunit is used for acquiring the account types corresponding to the classification identifiers and determining field attribute information of the classification description fields based on the account types;

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

In an alternative embodiment, the test data generation module 908 comprises: the device comprises an instruction acquisition unit, an environment generation unit and a test data generation unit, wherein:

the instruction acquisition unit is used for acquiring test environment information and target classification information carried by the test data generation instruction;

the environment generating unit is used for generating a test environment corresponding to the test data based on the test environment information;

and the test data generation unit is used for acquiring the target template based on the target classification information and generating test data based on the field to be filled of the target template in the test environment.

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

the service requirement acquisition unit is used for 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 the scene template combination unit is used for combining the fields of the basic data template acquired corresponding to the first service requirement to obtain the scene template corresponding to the first service requirement.

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

the first detection subunit is configured to generate data corresponding to the basic data template according to the field operation instruction of 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 condition of the basic data template; and/or the presence of a gas in the gas,

and the second detection subunit is configured to obtain an operation instruction corresponding to the first service demand based on the scene template corresponding to the first service demand, generate data corresponding to the first service demand according to the operation instruction corresponding to the first service demand, detect the data corresponding to the first service demand, and determine that the data corresponding to the first service demand meets the preset condition of the scene template corresponding to the first service demand.

The respective modules in the above-described apparatus for generating test data may be wholly or partially implemented by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 10. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing test data and/or storing templates, which are used for generating test data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of generating test data.

Those skilled in the art will appreciate that the architecture shown in fig. 10 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

In an embodiment, a computer program product is provided, comprising a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

It should be noted that, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), Magnetic Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

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

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

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:

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

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

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:

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.