CN116303102B - Test data generation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The disclosure relates to a method and a device for generating test data, electronic equipment and a storage medium, and belongs to the technical fields of financial science and technology, information technology industry and program test. The method comprises the following steps: acquiring metadata of a plurality of production fields included in the production data; acquiring a generation requirement of test data, and extracting a plurality of test fields included in the test data from the generation requirement; determining a production field corresponding to the test field, and obtaining a generation rule of the test field based on metadata of the production field corresponding to the test field; generating a plurality of field values of the test field according to the generation rule of the test field; the plurality of field values of each test field are taken as test data. Therefore, metadata of the production field corresponding to the test field can be considered to obtain a generation rule of the test field so as to generate a plurality of field values of the test field, and the test field with higher similarity with the production field can be obtained, namely, the test data with higher similarity with the production data can be obtained.
Description
Technical Field
The present disclosure relates to the technical field of financial science and technology, information technology industry, and program testing, and in particular, to a method and apparatus for generating test data, an electronic device, and a computer readable storage medium.
Background
At present, with the continuous development of internet technology, the development and iteration of application programs are frequent. In order to ensure the normal operation of the application program, the application program is often required to be tested by adopting test data before the application program is formally put into use. However, the method for generating test data in the related art has a problem that the generated test data has low similarity with production data, and affects the test effect of the application program.
Disclosure of Invention
The disclosure provides a method, a device, an electronic device and a computer readable storage medium for generating test data, so as to at least solve the problem that the similarity between the generated test data and production data is low in the related art. The technical scheme of the present disclosure is as follows:
according to a first aspect of an embodiment of the present disclosure, there is provided a method for generating test data, including: acquiring metadata of a plurality of production fields included in production data, acquiring generation requirements of test data, extracting a plurality of test fields included in the test data from the generation requirements, determining the production fields corresponding to the test fields, obtaining generation rules of the test fields based on the metadata of the production fields corresponding to the test fields, generating a plurality of field values of the test fields according to the generation rules of the test fields, and taking the field values of each test field as the test data.
In one embodiment of the disclosure, the determining the production field corresponding to the test field includes: and extracting a production field corresponding to the test field from the generation requirement.
In one embodiment of the disclosure, the determining the production field corresponding to the test field includes: identifying that a target field exists in a plurality of production fields, wherein the field name of the target field is the same as the field name of the test field, and/or the field class of the target field is the same as the field class of the test field; and determining the target field as a production field corresponding to the test field.
In one embodiment of the present disclosure, the metadata of the production field includes N valued intervals of a field value of the production field, where N is a positive integer; the generating rule of the test field is obtained based on the metadata of the production field corresponding to the test field, and the generating rule comprises the following steps: and determining N value intervals of the production field corresponding to the test field as the N value intervals of the test field.
In one embodiment of the present disclosure, the metadata of the production field further includes a duty ratio of an ith value interval of field values of the production field, wherein the duty ratio of the ith value interval is a ratio between a number of field values within the ith value interval and a total number of field values of the production field;
The generating rule of the test field is obtained based on the metadata of the production field corresponding to the test field, and the generating rule further comprises: and determining the duty ratio of the ith value interval of the production field corresponding to the test field as the duty ratio of the jth value interval of the test field, wherein the ith value interval is the same as the jth value interval, the duty ratio of the jth value interval is the ratio of the number of field values in the jth value interval to the total number of field values of the test field, and both i and j are positive integers not greater than N.
In one embodiment of the present disclosure, the metadata of the production field includes a duty cycle of the production field, wherein the duty cycle of the production field is a ratio between a total number of field values of the production field and a total number of the production data;
the generating rule of the test field is obtained based on the metadata of the production field corresponding to the test field, and the generating rule comprises the following steps: and determining the duty ratio of the production field corresponding to the test field as the duty ratio of the test field, wherein the duty ratio of the test field is the ratio of the total number of field values of the test field to the total number of test data.
In an embodiment of the present disclosure, the generating rule of the test field is obtained based on metadata of a production field corresponding to the test field, and the generating rule further includes: extracting a total number of the test data from the generated demand; the product between the duty cycle of the test field and the total number of test data is determined as the total number of field values of the test field.
In one embodiment of the present disclosure, the metadata of the production field includes a field class of the production field; the metadata of the plurality of production fields included in the acquired production data includes: if the field value of the production field accords with a target rule in a rule set, determining a field category corresponding to the target rule as the field category of the production field; or if the field value of the production field does not accord with each rule in the rule set, determining the setting category as the field category of the production field.
According to a second aspect of the embodiments of the present disclosure, there is provided a test data generating apparatus, including: an acquisition module configured to acquire metadata of a plurality of production fields included in the production data; the extraction module is configured to acquire the generation requirement of the test data and extract a plurality of test fields included in the test data from the generation requirement; the determining module is configured to determine a production field corresponding to the test field and obtain a generation rule of the test field based on metadata of the production field corresponding to the test field; the generating module is configured to generate a plurality of field values of the test field according to the generating rule of the test field, and take the plurality of field values of each test field as the test data.
In one embodiment of the present disclosure, the determining module is further configured to: and extracting a production field corresponding to the test field from the generation requirement.
In one embodiment of the present disclosure, the determining module is further configured to: identifying that a target field exists in a plurality of production fields, wherein the field name of the target field is the same as the field name of the test field, and/or the field class of the target field is the same as the field class of the test field; and determining the target field as a production field corresponding to the test field.
In one embodiment of the present disclosure, the metadata of the production field includes N valued intervals of a field value of the production field, where N is a positive integer; the determination module is further configured to: and determining N value intervals of the production field corresponding to the test field as the N value intervals of the test field.
In one embodiment of the present disclosure, the metadata of the production field further includes a duty ratio of an ith value interval of field values of the production field, wherein the duty ratio of the ith value interval is a ratio between a number of field values within the ith value interval and a total number of field values of the production field;
The determination module is further configured to: and determining the duty ratio of the ith value interval of the production field corresponding to the test field as the duty ratio of the jth value interval of the test field, wherein the ith value interval is the same as the jth value interval, the duty ratio of the jth value interval is the ratio of the number of field values in the jth value interval to the total number of field values of the test field, and both i and j are positive integers not greater than N.
In one embodiment of the present disclosure, the metadata of the production field includes a duty cycle of the production field, wherein the duty cycle of the production field is a ratio between a total number of field values of the production field and a total number of the production data;
the determination module is further configured to: and determining the duty ratio of the production field corresponding to the test field as the duty ratio of the test field, wherein the duty ratio of the test field is the ratio of the total number of field values of the test field to the total number of test data.
In one embodiment of the present disclosure, the determining module is further configured to: extracting a total number of the test data from the generated demand; the product between the duty cycle of the test field and the total number of test data is determined as the total number of field values of the test field.
In one embodiment of the present disclosure, the metadata of the production field includes a field class of the production field; the acquisition module is further configured to: if the field value of the production field accords with a target rule in a rule set, determining a field category corresponding to the target rule as the field category of the production field; or if the field value of the production field does not accord with each rule in the rule set, determining the setting category as the field category of the production field.
According to a third aspect of embodiments of the present disclosure, there is provided an electronic device, comprising: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method of generating test data as described in the first aspect.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform the method of generating test data as described in the previous first aspect.
The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects: the production field corresponding to the test field can be determined, and the metadata of the production field corresponding to the test field is considered to obtain the generation rule of the test field so as to generate a plurality of field values of the test field, so that the test field with higher similarity with the production field can be obtained, and the test data with higher similarity with the production data can be obtained.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure and do not constitute an undue limitation on the disclosure.
Fig. 1 is a flow chart illustrating a method of generating test data according to a first embodiment of the present disclosure.
Fig. 2 is a flow chart of a method of generating test data according to a second embodiment of the present disclosure.
Fig. 3 is a flow chart illustrating a method of generating test data according to a third embodiment of the present disclosure.
Fig. 4 is a block diagram of a test data generation system according to a first embodiment of the present disclosure.
Fig. 5 is a block diagram of a test data generating apparatus according to a first embodiment of the present disclosure.
Fig. 6 is a block diagram of an electronic device, according to an example embodiment.
Detailed Description
In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
The data acquisition, storage, use, processing and the like in the technical scheme of the present disclosure all conform to the relevant regulations of the national laws and regulations.
Fig. 1 is a flow chart illustrating a method of generating test data according to a first embodiment of the present disclosure.
As shown in fig. 1, a method for generating test data according to a first embodiment of the present disclosure includes the following steps:
in step S101, metadata of a plurality of production fields included in production data is acquired.
It should be noted that, the execution subject of the test data generation method of the present disclosure is an electronic device. The method for generating test data according to the embodiment of the present disclosure may be performed by the apparatus for generating test data according to the embodiment of the present disclosure, and the apparatus for generating test data according to the embodiment of the present disclosure may be configured in any electronic device to perform the method for generating test data according to the embodiment of the present disclosure.
It should be noted that the production data includes a plurality of production fields. The production data and the production field are not limited too much, for example, the production data can comprise bank production data, insurance production data, hospital production data and the like, and the production field can comprise name, age, mailbox, mobile phone number, amount and the like.
It should be noted that different production fields may correspond to the same metadata, or may correspond to different metadata. Metadata is not overly restricted. For example, metadata may include a field name of a production field, a field category, a data format, a distribution of field values of the production field, and so forth.
The distribution of the field values of the production field may include statistics of the central tendency of the field values of the production field (such as mean, median, etc.), statistics of the degree of dispersion of the field values of the production field (such as variance, standard deviation, etc.), and statistics of the distribution form of the field values of the production field (such as bias coefficient, standard score, etc.).
In one embodiment, the metadata of the production field includes a field class of the production field. The metadata of a plurality of production fields included in the production data is obtained, wherein the metadata comprises field categories corresponding to target rules and determined to be field categories of the production fields if field values of the production fields meet the target rules in the rule set, or set categories are determined to be field categories of the production fields if the field values of the production fields do not meet each rule in the rule set. Therefore, whether the field value of the production field accords with any rule in the rule set can be identified, if so, the field category corresponding to the target rule is determined as the field category of the production field, and if not, the set category is determined as the field category of the production field.
It should be noted that, the rule set includes a plurality of rules, the target rule is any rule in the rule set, and a corresponding relationship between each rule in the rule set and the field category may be established in advance. The rule set and the set category are not excessively limited.
For example, the rule set includes rules 1 to 3, wherein a correspondence is provided between rule 1 and a field class mailbox, a correspondence is provided between rule 2 and a field class name, and a correspondence is provided between rule 3 and a field class phone number. The field class mailbox, the name and the mobile phone number are all constraint classes, and the set classes are non-constraint classes.
If the field value of the production field a accords with the rule 1, determining a field type mailbox corresponding to the rule 1 as the field type of the production field a.
If the field value of the production field b accords with the rule 2, determining the field category name corresponding to the rule 2 as the field category of the production field b.
If the field value of the production field c accords with the rule 3, determining the field type mobile phone number corresponding to the rule 3 as the field type of the production field c.
If the field values of the production field d do not meet the rules 1 to 3, determining the unconstrained category as the field category of the production field d.
In step S102, a generation requirement of the test data is acquired, and a plurality of test fields included in the test data are extracted from the generation requirement.
It should be noted that the generation requirement includes a plurality of test fields included in the test data. The generation requirement can be set by a developer and a user, and is not limited excessively, for example, the generation requirement can further comprise the total number of test data, the total number of field values of the test fields, the generation mode, the data format, the data source, the category of the data source and the like. The generating party may include batch generation, stream generation, and the like, and the data format may include JSON (JavaScript Object Notation, JS object numbered musical notation), XML (Extensible Markup Language ), CSV (common-Separated Values), and the like. It should be noted that JavaScript is a programming language.
It should be noted that, the related content of the test field may refer to the related content of the production field, which is not described herein.
In step S103, a production field corresponding to the test field is determined, and a rule for generating the test field is obtained based on metadata of the production field corresponding to the test field.
It should be noted that, the number of production fields corresponding to one test field may be at least one, for example, if the number of production fields is M, the number of production fields corresponding to one test field may be 1, 2 to M. Wherein M is a positive integer. The production fields corresponding to the different test fields may be the same or different.
In the embodiment of the disclosure, determining the production field corresponding to the test field may include the following several possible implementations:
mode 1, extracting a production field corresponding to a test field from a generation requirement.
In some examples, the generation requirement includes a correspondence between a test field and a production field. For example, the generating requirement includes a correspondence between the test field e and the production field a, and further includes a correspondence between the test field f and the production fields b and c, and further includes a correspondence between the test field g and the production field a, b, c, d, where the production field a corresponding to the test field e, the production fields b and c corresponding to the test field f, and the production field a, b, c, d corresponding to the test field g may be extracted from the generating requirement.
Therefore, the method can directly extract the production field corresponding to the test field from the generation requirement.
And 2, identifying that a target field exists in the plurality of production fields, wherein the field name of the target field is the same as the field name of the test field, and/or the field category of the target field is the same as the field category of the test field, and determining the target field as the production field corresponding to the test field.
For example, the field name of the production field a is SEGMENT2, the field type is mailbox, the field name of the production field b is SEGMENT3, the field type is mailbox, the field name of the production field c is SEGMENT4, the field type is mobile phone number, the field name of the test field e is SEGMENT2, the field type is mailbox, the field name of the test field f is SEGMENT5, and the field type is mobile phone number.
The field name of the production field a can be identified to be the same as the field name of the test field e, the field types of the production fields a and b are the same as the field type of the test field e, and the production fields a and b are determined to be the production fields corresponding to the test field e.
The field type of the production field c can be identified to be the same as the field type of the test field f, and the production field c is determined to be the production field corresponding to the test field f.
Thus, the method can determine the target field with the consistent field name and/or field category with the production field as the production field corresponding to the test field.
It should be noted that the rule for generating the test field is not limited too much, and may include, for example, a field type of the test field, a data type, a data format, a distribution of field values of the test field, and the like.
In one embodiment, the generating rule of the test field is obtained based on the metadata of the production field corresponding to the test field, and the generating rule of the test field is determined by the metadata of the production field corresponding to the test field.
For example, a field type of the production field c corresponding to the test field f may be determined as a field type of the test field f, a data type of the production field c may be determined as a data type of the test field f, a data format of the production field c may be determined as a data format of the test field f, and a distribution of field values of the production field c may be determined as a distribution of field values of the test field f.
In step S104, a plurality of field values of the test field are generated in accordance with the generation rule of the test field, and the plurality of field values of each test field are used as test data.
It should be noted that, according to the rule for generating the test field, generating the plurality of field values of the test field may be implemented by any data generating method in the related art, which is not limited herein. For example, the generation rule of the test field may be input into the data generation model, and a plurality of field values of the test field may be output by the data generation model.
In one embodiment, the method further comprises determining S data sources of the test data, performing format conversion on the test data according to the category of the t data sources to obtain t conversion data, and storing the t conversion data into the t data sources. Wherein S is a positive integer, and t is a positive integer not greater than S. Therefore, in the method, the format conversion can be carried out on the test data according to the type of the data source to obtain the conversion data, so that the conversion data is matched with the type of the data source.
In summary, according to the method for generating test data provided by the embodiment of the present disclosure, metadata of a plurality of production fields included in production data is obtained, a generation requirement of the test data is obtained, a plurality of test fields included in the test data are extracted from the generation requirement, a production field corresponding to the test field is determined, a generation rule of the test field is obtained based on the metadata of the production field corresponding to the test field, a plurality of field values of the test field are generated according to the generation rule of the test field, and a plurality of field values of each test field are used as the test data. Therefore, the production field corresponding to the test field can be determined, the metadata of the production field corresponding to the test field is considered to obtain the generation rule of the test field so as to generate a plurality of field values of the test field, and the test field with higher similarity with the production field can be obtained, namely, the test data with higher similarity with the production data can be obtained.
Fig. 2 is a flow chart of a method of generating test data according to a second embodiment of the present disclosure.
As shown in fig. 2, a method for generating test data according to a second embodiment of the present disclosure includes the following steps:
s201, metadata of a plurality of production fields included in the production data is acquired.
S202, obtaining the generation requirement of the test data, and extracting a plurality of test fields included in the test data from the generation requirement.
S203, determining a production field corresponding to the test field.
The relevant content of steps S201-S203 can be seen in the above embodiments, and will not be described here again.
S204, determining N value intervals of the production field corresponding to the test field as N value intervals of the test field.
In an embodiment of the present disclosure, metadata of a production field includes N valued intervals of a field value of the production field, where N is a positive integer. The generation rule of the test field comprises N value intervals of the test field.
In one embodiment, the metadata of the production field further includes a duty ratio of an ith value interval of field values of the production field, wherein the duty ratio of the ith value interval is a ratio between a number of field values within the ith value interval and a total number of field values of the production field, i being a positive integer not greater than N.
The method comprises the steps of obtaining a generation rule of a test field based on metadata of a production field corresponding to the test field, and determining the duty ratio of an ith value interval of the production field corresponding to the test field as the duty ratio of a jth value interval of the test field, wherein the ith value interval is identical to the jth value interval, the duty ratio of the jth value interval is a ratio between the number of field values in the jth value interval and the total number of field values of the test field, and both i and j are positive integers not larger than N. It is understood that the rule for generating the test field includes the duty ratio of N valued intervals of the test field. Therefore, the method can determine the duty ratio of the value interval of the production field corresponding to the test field as the duty ratio of the value interval of the test field, so that the duty ratio of the value interval of the test field is similar to the duty ratio of the value interval of the production field, and the method is beneficial to obtaining the test field with higher similarity with the production field.
For example, if the field type of the production field c corresponding to the test field f is a name, the value interval of the field value of the production field c may include a surname, a limp name, and a rare word surname, if the total number of the field values of the production field c is 100, the number of the field values of the surname of the production field c is 20, the number of the field values of the limp name of the production field c is 10, the number of the field values of the rare word surname of the production field c is 1, the ratio of the surname of the production field c is 20%, the ratio of the limp surname is 10%, and the ratio of the rare word surname is 1%.
The surname, the prune surname and the uncommon surname can be determined as the value interval of the test field f, 20% is determined as the duty ratio of the surname of the test field f, 10% is determined as the duty ratio of the prune surname of the test field f, and 1% is determined as the duty ratio of the uncommon surname of the test field f.
For example, if the field type of the production field c corresponding to the test field f is an amount, the value interval of the field value of the production field c may include (0, 100), (100, 200), (200, 300), (300, 400), and if the field value of the production field c is 100, the number of field values in (0, 100) of the production field c is 10, the number of field values in (100, 200) of the production field c is 50, the number of field values in (200, 300) of the production field c is 30, and the number of field values in (300, 400) of the production field c is 20, the (0, 100) of the production field c accounts for 10%, the (100, 200) accounts for 50%, the (200, 300) accounts for 30%, and the (300, 400) accounts for 20%.
(0, 100], (100, 200], (200, 300], (300, 400) may be determined as the value interval of the test field f, and 10% may be determined as the duty ratio of (0, 100) of the test field f, 50% may be determined as the duty ratio of (100, 200) of the test field f, 30% may be determined as the duty ratio of (200, 300) of the test field f, and 20% may be determined as the duty ratio of (300, 400) of the test field f.
S205, generating a plurality of field values of the test fields according to the generation rule of the test fields, and taking the field values of each test field as test data.
The relevant content of step S205 may be referred to the above embodiments, and will not be described herein.
In summary, according to the method for generating test data provided by the embodiment of the present disclosure, N value intervals of a production field corresponding to a test field may be determined as N value intervals of the test field, so that the value intervals of the test field are similar to the value intervals of the production field, which is helpful to obtain a test field with higher similarity to the production field.
Fig. 3 is a flow chart illustrating a method of generating test data according to a third embodiment of the present disclosure.
S301, metadata of a plurality of production fields included in production data is acquired.
S302, obtaining the generation requirement of the test data, and extracting a plurality of test fields included in the test data from the generation requirement.
S303, determining a production field corresponding to the test field.
The relevant content of steps S301 to S303 can be seen in the above embodiments, and will not be described here again.
S304, determining the duty ratio of the production field corresponding to the test field as the duty ratio of the test field, wherein the duty ratio of the test field is the ratio between the total number of field values of the test field and the total number of test data.
In an embodiment of the present disclosure, the metadata of the production field includes a duty cycle of the production field, wherein the duty cycle of the production field is a ratio between a total number of field values of the production field and a total number of production data. The generation rule of the test field includes a duty cycle of the test field.
In one embodiment, the generating rule of the test field is obtained based on metadata of a production field corresponding to the test field, and the generating rule further comprises extracting total amount of test data from the generating requirement, and determining a product between a duty ratio of the test field and the total amount of the test data as total amount of field values of the test field. It will be appreciated that the generation rule of the test field includes the total number of field values of the test field. Thus, the product between the duty cycle of the test field and the total number of test data may be determined as the total number of field values of the test field in the method.
For example, if the total number of field values of the production field c corresponding to the test field f is 100 and the total number of production data is 1000, the duty ratio of the production field c is 10%, and 10% may be determined as the duty ratio of the test field f.
The total number of test data can be extracted from the test requirement to 10000, and the product 1000 of 10% and 10000 can be determined as the total number of field values of the test field f.
In some examples, determining the product of the duty cycle of the j-th value interval of the test field and the total number of field values of the test field as the number of field values within the j-th value interval of the test field is further included.
For example, if the total number of field values of the test field f is 1000, the value interval of the test field f includes (0, 100), (100, 200), (200, 300), (300, 400), and the ratio of (0, 100) of the test field f is 10%, the ratio of (100, 200) is 50%, the ratio of (200, 300) is 30%, and the ratio of (300, 400) is 20%.
The product 100 of 10% and 1000 may be determined as the number of field values within (0, 100) of the test field f, the product 500 of 50% and 1000 may be determined as the number of field values within (100, 200) of the test field f, the product 300 of 30% and 1000 may be determined as the number of field values within (200, 300) of the test field f, and the product 200 of 20% and 1000 may be determined as the number of field values within (300, 400) of the test field f.
S305, generating a plurality of field values of the test fields according to the generation rule of the test fields, and taking the field values of each test field as test data.
The relevant content of step S305 may be referred to the above embodiments, and will not be described herein.
In summary, according to the method for generating test data provided by the embodiment of the present disclosure, the duty ratio of the production field corresponding to the test field is determined as the duty ratio of the test field, so that the duty ratio of the test field is similar to the duty ratio of the production field, and the method is conducive to obtaining the test field with higher similarity to the production field.
On the basis of any of the above embodiments, as shown in fig. 4, the test data generating system includes a metadata acquiring module, a generating rule generating module, a data generating engine module, a data converting module, a data storing module and a control panel module.
The metadata acquisition module acquires metadata of a plurality of production fields included in the production data, and sends the metadata of the plurality of production fields to the generation rule generation module and the data storage module.
The generation rule generation module extracts a plurality of test fields included in the test data from the generation requirement of the test data, determines production fields corresponding to the test fields, obtains the generation rule of the test fields based on metadata of the production fields corresponding to the test fields, and sends the generation rule of the test fields to the data generation engine module and the data storage module.
The data generation engine module generates a plurality of field values of the test fields according to the generation rules of the test fields, takes the field values of each test field as test data, and sends the test data to the data conversion module.
The data conversion module determines S data sources of the test data, performs format conversion on the test data according to the category of the t data sources to obtain the t conversion data, and stores the t conversion data into the t data sources.
The data storage module stores metadata of the production fields and generation rules of the test fields into a database, receives generation requirements of the test data sent by the control panel module, and sends the generation requirements of the test data to the generation rule generation module.
Fig. 5 is a block diagram of a test data generating apparatus according to a first embodiment of the present disclosure.
As shown in fig. 5, the test data generating apparatus 500 of the embodiment of the present disclosure includes: an acquisition module 501, an extraction module 502, a determination module 503, and a generation module 504.
The acquisition module 501 is configured to acquire metadata of a plurality of production fields included in production data;
the extracting module 502 is configured to obtain a generation requirement of test data, and extract a plurality of test fields included in the test data from the generation requirement;
the determining module 503 is configured to determine a production field corresponding to the test field, and obtain a generation rule of the test field based on metadata of the production field corresponding to the test field;
The generating module 504 is configured to generate a plurality of field values of the test field according to the generating rule of the test field, and take the plurality of field values of each of the test fields as the test data.
In one embodiment of the present disclosure, the determining module 503 is further configured to: and extracting a production field corresponding to the test field from the generation requirement.
In one embodiment of the present disclosure, the determining module 503 is further configured to: identifying that a target field exists in a plurality of production fields, wherein the field name of the target field is the same as the field name of the test field, and/or the field class of the target field is the same as the field class of the test field; and determining the target field as a production field corresponding to the test field.
In one embodiment of the present disclosure, the metadata of the production field includes N valued intervals of a field value of the production field, where N is a positive integer; the determining module 503 is further configured to: and determining N value intervals of the production field corresponding to the test field as the N value intervals of the test field.
In one embodiment of the present disclosure, the metadata of the production field further includes a duty ratio of an ith value interval of field values of the production field, wherein the duty ratio of the ith value interval is a ratio between a number of field values within the ith value interval and a total number of field values of the production field;
The determining module 503 is further configured to: and determining the duty ratio of the ith value interval of the production field corresponding to the test field as the duty ratio of the jth value interval of the test field, wherein the ith value interval is the same as the jth value interval, the duty ratio of the jth value interval is the ratio of the number of field values in the jth value interval to the total number of field values of the test field, and both i and j are positive integers not greater than N.
In one embodiment of the present disclosure, the metadata of the production field includes a duty cycle of the production field, wherein the duty cycle of the production field is a ratio between a total number of field values of the production field and a total number of the production data;
the determining module 503 is further configured to: and determining the duty ratio of the production field corresponding to the test field as the duty ratio of the test field, wherein the duty ratio of the test field is the ratio of the total number of field values of the test field to the total number of test data.
In one embodiment of the present disclosure, the determining module 503 is further configured to: extracting a total number of the test data from the generated demand; the product between the duty cycle of the test field and the total number of test data is determined as the total number of field values of the test field.
In one embodiment of the present disclosure, the metadata of the production field includes a field class of the production field; the acquisition module 501 is further configured to: if the field value of the production field accords with a target rule in a rule set, determining a field category corresponding to the target rule as the field category of the production field; or if the field value of the production field does not accord with each rule in the rule set, determining the setting category as the field category of the production field.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
In summary, the generating device of test data provided in the embodiment of the present disclosure obtains metadata of a plurality of production fields included in production data, obtains a generation requirement of the test data, extracts a plurality of test fields included in the test data from the generation requirement, determines a production field corresponding to the test field, obtains a generation rule of the test field based on the metadata of the production field corresponding to the test field, generates a plurality of field values of the test field according to the generation rule of the test field, and uses a plurality of field values of each test field as the test data. Therefore, the production field corresponding to the test field can be determined, the metadata of the production field corresponding to the test field is considered to obtain the generation rule of the test field so as to generate a plurality of field values of the test field, and the test field with higher similarity with the production field can be obtained, namely, the test data with higher similarity with the production data can be obtained.
Fig. 6 is a block diagram of an electronic device, according to an example embodiment.
As shown in fig. 6, the electronic device 600 includes:
a memory 610 and a processor 620, a bus 630 connecting the different components (including the memory 610 and the processor 620), the memory 610 storing a computer program which when executed by the processor 620 implements the test data generation method according to the embodiments of the present disclosure.
Bus 630 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Electronic device 600 typically includes a variety of electronic device readable media. Such media can be any available media that is accessible by electronic device 600 and includes both volatile and nonvolatile media, removable and non-removable media.
Memory 610 may also include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 640 and/or cache memory 650. The electronic device 600 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 660 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, commonly referred to as a "hard disk drive"). Although not shown in fig. 6, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 630 through one or more data medium interfaces. Memory 610 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the various embodiments of the disclosure.
A program/utility 680 having a set (at least one) of program modules 670 may be stored in, for example, memory 610, such program modules 670 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 670 generally perform the functions and/or methods in the embodiments described in this disclosure.
The electronic device 600 may also communicate with one or more external devices 690 (e.g., keyboard, pointing device, display 691, etc.), one or more devices that enable a user to interact with the electronic device 600, and/or any device (e.g., network card, modem, etc.) that enables the electronic device 600 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 692. Also, the electronic device 600 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through a network adapter 693. As shown in fig. 6, the network adapter 693 communicates with other modules of the electronic device 600 over the bus 630. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 600, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processor 620 executes various functional applications and data processing by running programs stored in the memory 610.
It should be noted that, the implementation process and the technical principle of the electronic device in this embodiment refer to the foregoing explanation of the method for generating test data in the embodiment of the disclosure, and are not repeated herein.
In summary, the electronic device provided in the embodiment of the present disclosure may perform the foregoing method for generating test data, obtain metadata of a plurality of production fields included in production data, obtain a generation requirement of the test data, extract a plurality of test fields included in the test data from the generation requirement, determine a production field corresponding to the test field, obtain a rule for generating the test field based on the metadata of the production field corresponding to the test field, generate a plurality of field values of the test field according to the rule for generating the test field, and use the plurality of field values of each test field as the test data. Therefore, the production field corresponding to the test field can be determined, the metadata of the production field corresponding to the test field is considered to obtain the generation rule of the test field so as to generate a plurality of field values of the test field, and the test field with higher similarity with the production field can be obtained, namely, the test data with higher similarity with the production data can be obtained.
To achieve the above embodiments, the present disclosure also proposes a computer-readable storage medium.
Wherein the instructions in the computer-readable storage medium, when executed by the processor of the electronic device, enable the electronic device to perform the method of generating test data as described above. Alternatively, the computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (16)
1. A method of generating test data, comprising:
acquiring metadata of a plurality of production fields included in the production data;
acquiring a generation requirement of test data, and extracting a plurality of test fields included in the test data from the generation requirement;
determining a production field corresponding to the test field, and obtaining a generation rule of the test field based on metadata of the production field corresponding to the test field;
generating a plurality of field values of the test field according to the generation rule of the test field, and taking the plurality of field values of each test field as the test data;
wherein the metadata of the production field includes a duty cycle of the production field, wherein the duty cycle of the production field is a ratio between a total number of field values of the production field and a total number of the production data;
the generating rule of the test field is obtained based on the metadata of the production field corresponding to the test field, and the generating rule comprises the following steps:
and determining the duty ratio of the production field corresponding to the test field as the duty ratio of the test field, wherein the duty ratio of the test field is the ratio of the total number of field values of the test field to the total number of test data.
2. The method of claim 1, wherein the determining the production field to which the test field corresponds comprises:
and extracting a production field corresponding to the test field from the generation requirement.
3. The method of claim 1, wherein the determining the production field to which the test field corresponds comprises:
identifying that a target field exists in a plurality of production fields, wherein the field name of the target field is the same as the field name of the test field, and/or the field class of the target field is the same as the field class of the test field;
and determining the target field as a production field corresponding to the test field.
4. The method of claim 1, wherein the metadata of the production field includes N valued intervals of a field value of the production field, where N is a positive integer;
the generating rule of the test field is obtained based on the metadata of the production field corresponding to the test field, and the generating rule comprises the following steps:
and determining N value intervals of the production field corresponding to the test field as the N value intervals of the test field.
5. The method of claim 4, wherein the metadata of the production field further comprises a duty cycle of an ith value interval of field values of the production field, wherein the duty cycle of the ith value interval is a ratio between a number of field values within the ith value interval and a total number of field values of the production field;
The generating rule of the test field is obtained based on the metadata of the production field corresponding to the test field, and the generating rule further comprises:
and determining the duty ratio of the ith value interval of the production field corresponding to the test field as the duty ratio of the jth value interval of the test field, wherein the ith value interval is the same as the jth value interval, the duty ratio of the jth value interval is the ratio of the number of field values in the jth value interval to the total number of field values of the test field, and both i and j are positive integers not greater than N.
6. The method of claim 1, wherein the obtaining the rule for generating the test field based on the metadata of the production field corresponding to the test field further comprises:
extracting a total number of the test data from the generated demand;
the product between the duty cycle of the test field and the total number of test data is determined as the total number of field values of the test field.
7. The method of any one of claims 1-6, wherein the metadata of the production field includes a field class of the production field;
The metadata of the plurality of production fields included in the acquired production data includes:
if the field value of the production field accords with a target rule in a rule set, determining a field category corresponding to the target rule as the field category of the production field; or,
and if the field value of the production field does not accord with each rule in the rule set, determining the set category as the field category of the production field.
8. A test data generating apparatus, comprising:
an acquisition module configured to acquire metadata of a plurality of production fields included in the production data;
the extraction module is configured to acquire the generation requirement of the test data and extract a plurality of test fields included in the test data from the generation requirement;
the determining module is configured to determine a production field corresponding to the test field and obtain a generation rule of the test field based on metadata of the production field corresponding to the test field;
the generating module is configured to generate a plurality of field values of the test field according to the generating rule of the test field, and takes the field values of each test field as the test data;
The metadata of the production field includes a duty cycle of the production field, wherein the duty cycle of the production field is a ratio between a total number of field values of the production field and a total number of the production data;
the determination module is further configured to:
and determining the duty ratio of the production field corresponding to the test field as the duty ratio of the test field, wherein the duty ratio of the test field is the ratio of the total number of field values of the test field to the total number of test data.
9. The apparatus of claim 8, wherein the determination module is further configured to:
and extracting a production field corresponding to the test field from the generation requirement.
10. The apparatus of claim 8, wherein the determination module is further configured to:
identifying that a target field exists in a plurality of production fields, wherein the field name of the target field is the same as the field name of the test field, and/or the field class of the target field is the same as the field class of the test field;
and determining the target field as a production field corresponding to the test field.
11. The apparatus of claim 8, wherein the metadata of the production field includes N valued intervals of a field value of the production field, wherein N is a positive integer;
the determination module is further configured to:
and determining N value intervals of the production field corresponding to the test field as the N value intervals of the test field.
12. The apparatus of claim 11, wherein the metadata of the production field further comprises a duty cycle of an ith value interval of field values of the production field, wherein the duty cycle of the ith value interval is a ratio between a number of field values within the ith value interval and a total number of field values of the production field;
the determination module is further configured to:
and determining the duty ratio of the ith value interval of the production field corresponding to the test field as the duty ratio of the jth value interval of the test field, wherein the ith value interval is the same as the jth value interval, the duty ratio of the jth value interval is the ratio of the number of field values in the jth value interval to the total number of field values of the test field, and both i and j are positive integers not greater than N.
13. The apparatus of claim 8, wherein the determination module is further configured to:
extracting a total number of the test data from the generated demand;
the product between the duty cycle of the test field and the total number of test data is determined as the total number of field values of the test field.
14. The apparatus according to any one of claims 8-13, wherein the metadata of the production field comprises a field class of the production field;
the acquisition module is further configured to:
if the field value of the production field accords with a target rule in a rule set, determining a field category corresponding to the target rule as the field category of the production field; or,
and if the field value of the production field does not accord with each rule in the rule set, determining the set category as the field category of the production field.
15. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the method of generating test data according to any of claims 1-7.
16. A computer readable storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform the method of generating test data according to any of claims 1-7.
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