Method and System for Generating Simulation Data Based on a Data Dictionary

Abstract

The present invention provides a method and system for generating simulation data based on a data dictionary, including: forming construction rules according to the content of the data dictionary; wherein, the construction rules include algorithm functions for generating simulation data; obtaining fields according to the table structure of a database, or for fields added by a user in a document, generating data under the fields through the construction rules. The present invention achieves the purpose of generating simulation data through various data generation functions extended by an enterprise-level data dictionary. By adopting enterprise-level data dictionary parsing and extended construction rules, data standardization and controllability are realized.

Description

Technical Field

[0001] The present invention relates to the field of data generation technology, and specifically, to a method and system for generating simulation data based on a data dictionary. Background Art

[0002] In the current practical application of data generation, instead of summarizing data generation rules, they are solidified in some SQL statements. The rules are not unified, the simulation degree is not high, and it is difficult to reuse. For example, when generating names, it is Zhang Yi, Zhang Er, etc.; when generating ID cards, it is 00...1, 00...2, etc. For another person, it may be 442..., 442..., etc., with inconsistent rules. Moreover, the checksum and the meaning of each code are not carefully studied. Even if they are studied, due to the limitations of the characteristics of conventional SQL code (each time the entire paragraph has to be written, and the SQL syntax of different databases is different and not compatible. For example, MySQL is not compatible with Oracle, nor with Informix, nor with PostgreSQL), it is very difficult to reuse. The code written this time must be rewritten when needed next time, or a large amount of time and effort is required to deeply adapt to the database SQL when changing a database. Writing code using SQL is a high-level content for any database, resulting in very limited significance of the previously sorted rules. After all, each time it has to be written again, or when it needs to be changed according to the situation, it is time-consuming and laborious to rewrite the code written by others. Moreover, due to different people's understandings of the rules, the rules of the data written are also different and not unified, and there is no way to constrain at the implementation level.

[0003] Taking the SQL data generation method as an example, for each data generation in SQL, the entire SQL code has to be written, and the code cannot be reused for different types of data. The versatility is poor, and it is only applicable to the current database. For example, the SQL data generation script for MySQL is not suitable for the Oracle database. Summary of the Invention

[0004] Aiming at the defects in the prior art, the purpose of the present invention is to provide a method and system for generating simulation data based on a data dictionary.

[0005] According to a method for generating simulation data based on a data dictionary provided by the present invention, it includes a construction rule creation step, and also includes a database data generation step and / or a document data generation step;

[0006] The construction rule creation step: forming construction rules according to the content of the data dictionary; wherein, the construction rules include algorithm functions for generating simulation data;

[0007] The database data generation step: obtaining fields according to the table structure of the database, specifying construction rules for the fields according to the user's instructions, or automatically matching construction rules, and generating data under the fields through the construction rules;

[0008] Document data generation steps: For the fields added by the user in the document, construct rules are specified for the fields according to the user's instructions, or construct rules are automatically matched, and data is generated under the fields through the construct rules.

[0009] Preferably, the construct rule creation steps include:

[0010] Step of forming major construct rules: The content in the data dictionary is split by theme to obtain each small unit of content, and each small unit of content is respectively parsed to form major construct rules corresponding to the theme;

[0011] Step of forming minor construct rules: The code values of the small unit content under the theme corresponding to the major construct rules are parsed and processed to form minor construct rules under the major construct rules. Among them, the code values and the algorithms corresponding to the small unit content are written and aggregated for code algorithms to generate minor construct rules;

[0012] Step of forming construct rules: Based on the code algorithms in one or more minor construct rules, an algorithm function for generating simulation data is formed.

[0013] Preferably, specifying construct rules for fields according to the user's instructions includes: automatically reading the database table structure, fields, and field contents corresponding to the data to be generated, and allowing the user to freely edit and select construct rules from the construct rule library for each field to determine the simulation data generated for each field;

[0014] The automatic matching of construct rules includes: automatically reading the database table structure, fields, and field contents corresponding to the data to be generated, and then automatically matching construct rules and fields according to relevant algorithms; the relevant algorithms include: performing the first construct rule matching through the comment or description of each field obtained from the database table result, and then reading the field type and field length to perform parameter authentication on the construct rules matched for the first time or changing them to construct rules that simultaneously meet the field description, type, and length; if there are multiple construct rules, recommendations for construct rules are comprehensively made according to the usage frequency of the construct rules; if the user leaves the comment or description of the field blank, the field type and field length are preferentially matched.

[0015] Preferably, the constraint information of the fields includes primary key, foreign key, and unique value; for the primary key and unique value: automatically identify the field type and length, and automatically match construct rules that meet the conditions; for the foreign key, through the foreign key matching algorithm, automatically read the associated field contents of the associated table, screen the contents, and automatically inject them into the foreign key field after processing.

[0016] A data generation system for simulation data based on a data dictionary provided by the present invention includes a construction rule creation module, and further includes a database data generation module and / or a document data generation module;

[0017] The construction rule creation module: forms construction rules according to the content of the data dictionary; wherein, the construction rules include algorithm functions for generating simulation data;

[0018] The database data generation module: obtains fields according to the table structure of the database, specifies construction rules for the fields according to the user's instructions, or automatically matches construction rules, and generates data under the fields through the construction rules;

[0019] The document data generation module: for the fields added by the user in the document, specifies construction rules for the fields according to the user's instructions, or automatically matches construction rules, and generates data under the fields through the construction rules.

[0020] Preferably, the construction rule creation module includes:

[0021] The construction rule major category formation module: splits the content in the data dictionary according to the theme, obtains each small unit content, and respectively analyzes each small unit content to form construction rule major categories corresponding to the theme;

[0022] The construction rule minor category formation module: analyzes and processes the code values of the small unit content under the theme corresponding to the construction rule major category to form construction rule minor categories under the construction rule major category. Among them, the code values and the algorithms corresponding to the small unit content are used for code algorithm writing and aggregation to generate construction rule minor categories;

[0023] The construction rule formation module: forms an algorithm function for generating simulation data based on the code algorithms in one or more construction rule minor categories.

[0024] Preferably, the specifying of construction rules for fields according to the user's instructions includes: automatically reading the corresponding database table structure, fields, and field contents to be generated with data, and allowing the user to freely edit and select construction rules in the construction rule library for each field to determine the simulation data generated for each field;

[0025] The automatic matching construction rules include: automatically reading the database table structure, fields, and field contents corresponding to the data to be generated, and then automatically matching the construction rules and fields according to relevant algorithms; the relevant algorithms include: performing the first construction rule matching through the comment or description of each field obtained from the database table result, and then reading the field type and field length to perform parameter authentication on the first-matched construction rule or changing it to a construction rule that simultaneously meets the field description, type, and length; if there are multiple construction rules, the construction rules are recommended comprehensively according to the usage scenario frequency of the construction rules; if the user sets the comment or description of the field to null, the field type and field length are preferentially matched.

[0026] Preferably, the constraint information of the field includes the primary key, foreign key, and unique value; for the primary key and unique value: automatically identify the field type and length, and automatically match the eligible construction rules; for the foreign key, through the foreign key matching algorithm, automatically read the associated field contents of the associated table, screen the contents, and automatically inject the foreign key field after processing.

[0027] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the method for generating simulation data based on a data dictionary are implemented.

[0028] According to an electronic device provided by the present invention, including a memory, a processor, and a computer program stored on the memory and executable on the processor, when the computer program is executed by the processor, the steps of the method for generating simulation data based on a data dictionary are implemented.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. By parsing and splitting the data dictionary (such as a standardized enterprise-level data dictionary), the present invention recombines it into new construction rules that meet the unified standard for data generation, forms a construction rule library, and allows custom supplementation of new construction rules.

[0031] 2. Through the standardized construction rules, the present invention can perform data generation for multiple databases and document generation.

[0032] 3. In the database data generation of the present invention, there is no intermediate redundant product, directly reaching the database table; and the simulation degree is refined to the field, and the construction rules can be automatically matched with one key to achieve automation, and the constraint fields are automatically processed, and multiple single tables can also be generated in parallel without queuing.

[0033] 4. The document generation in the present invention generates text data, adapts to most database import functions on the market, and expands the applicable range.

[0034] 5. When users use the functions provided by the present invention, they do not need a code foundation and the operation is simple, which is suitable for different groups of people from those with no code foundation to professional code personnel. Description of the Drawings

[0035] By reading the following detailed description of the non-limiting embodiments with reference to the accompanying drawings, other features, objects, and advantages of the present invention will become more apparent:

[0036] Figure 1 It is a schematic flow chart of the data creation method of the present invention. Detailed Embodiments

[0037] The present invention will be described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several changes and improvements can still be made. These all belong to the protection scope of the present invention.

[0038] The present invention achieves the purpose of creating simulation data through various data creation functions extended by the enterprise-level data dictionary. By adopting the parsing and extension construction rules of the enterprise-level data dictionary, the standardization and controllability of data are realized. The present invention can actually be compatible with multiple databases and multiple data sample forms, such as text, json, etc., solves the problem of non-compatibility of multi-database sql, saves a lot of time and energy, and there is no need to delve into the high-order sql code of each database, or the problem of the standardization of different types of data, as well as the problem of the reuse of construction rule assets. Even if others use it, the construction rules are still the same, and it will not be affected by different codes, different understandings, and different rules used by different people.

[0039] A data creation method for simulation data based on a data dictionary according to the present invention includes:

[0040] Step S1: Split and parse the content of the data dictionary to form a construction rule library for simulation data creation, where the construction rule library includes construction rules. The data dictionary can be, for example, an enterprise-level data dictionary. The content of the data dictionary is split and parsed to form construction rules for standardized data creation and form a construction rule library. The step S1 includes:

[0041] Step S1.1: According to different themes of the content of the data dictionary, split, parse, and create different major categories of construction rules; specifically, the split content is recorded as small unit content, and the small unit content is parsed.

[0042] Step S1.2: According to the Chinese or English name corresponding to the theme, split and create the names of different sub - categories of construction rules under the major category of construction rules to which the theme belongs. Analyze and process the corresponding various code values according to the names to form the content of different sub - categories of construction rules, and generate different usage methods. The processing includes: writing and aggregating code algorithms for the code values and the algorithmic ideas corresponding to the small - unit content parsed in the previous step to generate sub - categories of construction rules.

[0043] Among them, the construction rule library for standardized data generation supports functions such as adding, deleting, modifying, and querying in a timely manner. It can also add various types of data dictionaries, expand the library content, and at the same time, it can re - sort the construction rules to generate new data dictionaries. At the same time, the construction rules can be adapted to all data - generation methods.

[0044] The construction rules are based on multi - function codes, that is, the content of the construction rules includes multi - function codes. The multi - function codes of the same construction rule can be split to obtain individual function codes, and the individual function codes can be combined to form new construction rules. For example, one individual function code of construction rule A can be combined with another individual function code of construction rule B to form a new construction rule C. The name of the construction rule is the name of the background algorithm function. For example, the name of the construction rule corresponding to the ID card simulation data is ssn. The content of the construction rule ssn includes the algorithm for generating ID card simulation data, packaged as a function, and the function name is ssn. This function name is the name of the construction rule, and the algorithm code can be quickly called through the corresponding function name to generate the corresponding simulation data. Each construction rule corresponds to an algorithm in the background. It is also possible to adjust parameters through some function reserved entrances to generate different data for the same construction rule. For example, if only ssn is selected, random ID cards will be generated, and if the parameter ssn(20,30) is added, ID cards of people between 20 and 30 years old will be generated.

[0045] The major category of construction rules includes one or more sub - categories of construction rules, and the sub - categories of construction rules correspond to construction rules. For example, the major category of construction rules with the theme of "person" can be split into sub - categories of construction rules with names such as ID card, name, address, etc. For another example, the major category of construction rules with the theme of "network" can be split into sub - categories of construction rules with names such as ipv4, ipv6, md5, etc. The names of the sub - categories of construction rules can use Chinese names or common English names for the convenience of users to understand. It is also possible to customize the names of the sub - categories of construction rules. In the preferred example, each sub - category of construction rules corresponds to a construction rule, and one construction rule can correspond to multiple sub - categories of construction rules.

[0046] Step S2: Database data generation step. It supports multiple common database engines and can be refined to fields. Specifically, it obtains field and constraint information according to the table structure of the database, specifies construction rules for fields according to the user's instructions, or uses intelligent analysis to automatically match appropriate construction rules, and generates data through the construction rules. Matching means that for example, field A matches the ID card construction rule, which means that the data to be generated for this field A is simulated ID card data. After matching the fields of the database with the construction rules, input the number of simulated data to be generated, and then start generating data to obtain the number of simulated data.

[0047] In the data generation process, select and adopt one of the two methods according to the selected or matched construction rules for standardized data generation:

[0048] Method A: Specify construction rule step. First, automatically read the database table structure, fields, and field contents corresponding to the data to be generated. The user can freely edit and select construction rules from the standard construction rule library for each field to determine what data each field generates.

[0049] Method B: Automatically match construction rule step. First, automatically read the common database table structure, fields, and field contents. Then the user uses the automatic matching function to automatically match construction rules and fields according to relevant algorithms without having to select construction rules again. The algorithm can be to perform the first construction rule matching through the comment or description of each field obtained from the database table structure, and then read the field type and field length to authenticate the parameters of the first-matched construction rule or change it to a construction rule that simultaneously meets the field description, type, and length. If there are multiple construction rules, a more suitable construction rule can be recommended by comprehensively considering the usage frequency of the construction rules. If the user sets the comment or description of the field to null, the field type and field length are preferentially matched.

[0050] Both Method A and Method B directly insert data into the database without redundant intermediate products, and the construction rules are easy to understand. The code of the specific algorithm corresponding to each construction rule is packaged into a single function for the user. An open reference channel is provided for the single function that is not easy to understand, and the reference name is in Chinese or common English. For example, "Name" is a construction rule name, and "ID card" is also a construction rule name. In addition to quickly understanding the content through simple Chinese names, easy-to-understand explanations and usage examples are also provided. It is easy to get started, has a wide range of applications, the data generation efficiency and speed are significantly higher than the manual level, and the construction rules used for each data generation can be archived for standardized management and auditing.

[0051] Among them, the construction rules come from the construction rule library created in step S1. For special constraint information, such as indexes, primary keys, foreign keys, unique values, increments, etc., intelligent processing is performed without user operation, reducing cumbersome steps and error conflicts. It can be operated unitarily or in batches. For example, for primary keys and unique values. The characteristic of a primary key is that it cannot be repeated, and as a field, it must conform to the field length and field type. The present invention automatically identifies the field type and length, and automatically matches relevant construction rules that meet the conditions without user operation. Another example is for foreign keys. A foreign key is used to associate with another table and is a field used to determine the records of another table, which is used to maintain data consistency. For users, operating foreign keys is more difficult because they need to know the data content of the corresponding associated fields in another table. The present invention performs automated processing. Through the foreign key matching algorithm, the algorithm automatically reads the content of the associated fields in the associated table, filters the content, and automatically injects the content into the foreign key field after processing.

[0052] Step S3: Document data generation step. Database data generation is to directly generate simulation data into the database, while document data generation is to generate simulation data into a document. Document data generation does not require database configuration and is not associated with the database. It uses a more flexible data generation product and performs data generation according to standardized construction rules. Users can add fields according to their needs and select construction rules for the newly added blank fields, and then start data generation by entering the quantity.

[0053] The generated document data in document data generation can be used. If necessary, users can also import it into other databases or for other purposes. The databases supported by database data generation are mainly common general types. However, for some databases on the market, due to security considerations, one-to-one key configuration is required, or the closed intranet cannot be directly connected to use database data generation. In this case, the document data generated by document data generation can be placed in the intranet and then imported into the database. Step S2 corresponding to document data generation and step S3 corresponding to database data generation can be executed alternatively or both. When both are executed, there is no relationship of step sequence. The process of database data generation is: connect to the database, automatically read the database, and the user matches construction rules according to needs to generate database data. The process of document data generation is: the user adds fields and selects rules according to needs to generate document data. For document data generation, the simulation data obtained by the present invention is text data as the product, and the text data is txt or csv file data. The file and the database are completely different systems and are independent of the database, so it is not restricted by the database type. At the same time, most databases on the market also support the import of document data, which also means compatibility with most databases in another aspect. At the same time, it also expands the data usage, not limited to R & D and testing personnel, and non-technical personnel such as business can also use it.

[0054] The present invention also provides a data generation system for simulation data based on a data dictionary. The data generation system for simulation data based on a data dictionary can be implemented by executing the process steps of the data generation method for simulation data based on a data dictionary. That is, the data generation method for simulation data based on a data dictionary can be understood as a preferred implementation manner of the data generation system for simulation data based on a data dictionary. Specifically, according to a data generation system for simulation data based on a data dictionary provided by the present invention, it includes a construction rule creation module, and also includes a database data generation module and / or a document data generation module;

[0055] The construction rule creation module: forms construction rules according to the content of the data dictionary; wherein, the construction rules include algorithm functions for generating simulation data;

[0056] The database data generation module: obtains fields according to the table structure of the database, specifies construction rules for the fields according to the user's instructions, or automatically matches construction rules, and generates data under the fields through the construction rules;

[0057] The document data generation module: for the fields added by the user in the document, specifies construction rules for the fields according to the user's instructions, or automatically matches construction rules, and generates data under the fields through the construction rules.

[0058] The construction rule creation module includes:

[0059] The construction rule major category formation module: splits the content in the data dictionary according to the theme, obtains each small unit content, and respectively analyzes each small unit content to form construction rule major categories corresponding to the theme;

[0060] The construction rule minor category formation module: analyzes and processes the code values of the small unit content under the theme corresponding to the construction rule major category to form construction rule minor categories under the construction rule major category. Among them, the code values and the algorithms corresponding to the small unit content are used for code algorithm writing and aggregation to generate construction rule minor categories;

[0061] The construction rule formation module: forms an algorithm function for generating simulation data based on the code algorithms in one or more construction rule minor categories.

[0062] The specifying construction rules for fields according to the user's instructions includes: automatically reading the corresponding database table structure, fields, and field contents to be used for data generation, and allowing the user to freely edit and select construction rules in the construction rule library for each field to determine the simulation data generated for each field;

[0063] The automatic matching construction rules include: automatically reading the database table structure, fields, and field contents corresponding to the data to be generated, and then automatically matching the construction rules and fields according to relevant algorithms; the relevant algorithms include: performing the first construction rule matching through the comment or description of each field obtained from the database table result, and then reading the field type and field length to perform parameter authentication on the construction rules matched for the first time or changing them to construction rules that simultaneously meet the field description, type, and length; if there are multiple construction rules, recommend the construction rules comprehensively according to the usage frequency of the construction rules; if the user empties the comment or description of the field, give priority to matching the field type and field length.

[0064] The constraint information of the field includes the primary key, foreign key, and unique value; for the primary key and unique value: automatically identify the field type and length, and automatically match the eligible construction rules; for the foreign key, through the foreign key matching algorithm, automatically read the associated field content of the associated table, screen the content, and automatically inject it into the foreign key field after processing.

[0065] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the method for generating simulation data based on a data dictionary are implemented.

[0066] According to an electronic device provided by the present invention, including a memory, a processor, and a computer program stored on the memory and executable on the processor, when the computer program is executed by the processor, the steps of the method for generating simulation data based on a data dictionary are implemented.

[0067] Those skilled in the art know that in addition to implementing the systems, devices, and their respective modules provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the systems, devices, and their respective modules provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc. to achieve the same program. Therefore, the systems, devices, and their respective modules provided by the present invention can be regarded as a kind of hardware component, and the modules included therein for implementing various programs can also be regarded as the structure within the hardware component; the modules for implementing various functions can also be regarded as both software programs for implementing the method and the structure within the hardware component.

[0068] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for generating simulation data based on a data dictionary, characterized in that, It includes a construction rule creation step, and also includes a database data generation step and / or a document data generation step; Construction rule creation step: Form construction rules according to the content of the data dictionary; wherein, the construction rules include algorithm functions for generating simulation data; Database data generation step: Obtain fields according to the table structure of the database, specify construction rules for the fields according to the user's instructions, or automatically match construction rules, and generate data under the fields through the construction rules; Document data generation step: For the fields added by the user in the document, specify construction rules for the fields according to the user's instructions, or automatically match construction rules, and generate data under the fields through the construction rules; The construction rule creation step includes: Construction rule major category formation step: Split the content in the data dictionary according to the theme to obtain each small unit content, and respectively parse each small unit content to form construction rule major categories corresponding to the theme; Construction rule minor category formation step: Parse and process the code values of the small unit content under the theme corresponding to the construction rule major category to form construction rule minor categories under the construction rule major category. Among them, write and aggregate the code algorithm of the code value and the algorithm corresponding to the small unit content to generate construction rule minor categories; Construction rule formation step: Based on the code algorithms in one or more construction rule minor categories, form an algorithm function for generating simulation data; Specifying construction rules for fields according to the user's instructions includes: Automatically reading the corresponding database table structure, fields, and field contents to be generated with data, and allowing the user to freely edit and select construction rules in the construction rule library for each field to determine the simulation data generated by each field; Automatically matching construction rules includes: Automatically reading the corresponding database table structure, fields, and field contents to be generated with data, and then automatically matching construction rules and fields according to relevant algorithms; the relevant algorithms include: Conducting the first construction rule matching through the comment or description of each field obtained from the database table result, and then reading the field type and field length to authenticate the parameters of the first-matched construction rule or change it to a construction rule that simultaneously meets the field description, type, and length; if there are multiple construction rules, recommend construction rules comprehensively according to the usage frequency of the construction rules; if the user sets the comment or description of the field to be empty, give priority to matching the field type and field length.

2. The method for generating simulation data based on a data dictionary according to claim 1, wherein The constraint information of the fields includes primary keys, foreign keys, and unique values; for primary keys and unique values: Automatically identify the field type and length and automatically match eligible construction rules; for foreign keys, through the foreign key matching algorithm, automatically read the associated field content of the associated table, screen the content, and automatically inject it into the foreign key field after processing.

3. A data generation system for simulation data based on a data dictionary, characterized in that, It includes a construction rule creation module, and also includes a database data generation module and / or a document data generation module; Construction rule creation module: Form construction rules according to the content of the data dictionary; wherein, the construction rules include algorithm functions for generating simulation data; Database data generation module: Obtain fields according to the table structure of the database, specify construction rules for the fields according to the user's instructions, or automatically match construction rules, and generate data under the fields through the construction rules; Document data generation module: For the fields added by the user in the document, specify construction rules for the fields according to the user's instructions, or automatically match construction rules, and generate data under the fields through the construction rules; The construction rule creation module includes: Construction rule major category formation module: Split the content in the data dictionary according to the theme to obtain each small unit content, and respectively analyze each small unit content to form construction rule major categories corresponding to the theme; Construction rule minor category formation module: Analyze and process the code values of the small unit content under the theme corresponding to the construction rule major category to form construction rule minor categories under the construction rule major category. Among them, write and aggregate the code algorithm corresponding to the code value and the small unit content to generate construction rule minor categories; Construction rule formation module: Based on the code algorithms in one or more construction rule minor categories, form an algorithm function for generating simulation data; Specifying construction rules for fields according to the user's instructions includes: Automatically reading the database table structure, fields, and field contents corresponding to the data to be generated, and allowing the user to freely edit and select construction rules in the construction rule library for each field to determine the simulation data generated for each field; Automatically matching construction rules includes: Automatically reading the database table structure, fields, and field contents corresponding to the data to be generated, and then automatically matching construction rules and fields according to relevant algorithms; The relevant algorithms include: Perform the first construction rule matching through the comment or description of each field obtained from the database table result, and then read the field type and field length to authenticate the parameters of the first-matched construction rule or change it to a construction rule that simultaneously meets the field description, type, and length; If there are multiple construction rules, recommend construction rules comprehensively according to the usage frequency of the construction rules; If the user sets the comment or description of the field to null, give priority to matching the field type and field length.

4. The data generation system for simulation data based on a data dictionary according to claim 3, wherein The constraint information of the field includes primary key, foreign key, and unique value; For the primary key and unique value: Automatically identify the field type and length and automatically match eligible construction rules; For the foreign key, through the foreign key matching algorithm, automatically read the associated field content of the associated table, screen the content, and automatically inject the foreign key field after processing.

5. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method for generating simulation data based on a data dictionary according to claim 1 or 2.

6. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the computer program is executed by a processor, it implements the steps of the method for generating simulation data based on a data dictionary according to claim 1 or 2.

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