Implementation method and system for simulation data generation

Abstract

The invention discloses an implementation method and system for analog data generation. The implementation method comprises the steps that an analog data information configuration table is defined; analyzing rules in the simulation data information configuration table into various generation rules according to types; inputting a plurality of types of data according to a plurality of generation rules to generate a large model, and generating simulation data; generating a corresponding verification rule according to the rule in the simulation data information configuration table; and verifying the generated data, if the verification is passed, generating a result, and if the verification is failed, inputting a failure reason and the data into the data generation large model until the verification is passed. According to the method and the device, the simulation data can be generated and verified in a mode that only configuration does not need codes, manpower resources consumed in the simulation data generation and verification process are reduced, the quality of automatically generated simulation data is improved, and the efficiency in the development and test process is improved.

Description

Technical Field

[0001] The present invention relates to the field of simulation data, and in particular to a method and system for realizing simulation data generation. Background Art

[0002] Simulating data is an inevitable part of the software development and testing process in the financial sector. As a data-intensive industry, the financial industry has highly complex, real-time, and sensitive data. Financial data not only involves a large amount of transaction records and customer information, but also contains data from multiple key business links such as risk assessment and fraud detection. These data are crucial for decision-making and risk management of financial institutions. Due to the particularity of financial data, obtaining high-quality and diverse test data has become a very challenging task.

[0003] At present, most of the tools used by developers and testers to generate test simulation data are irregular data generation methods. Such data has no actual business meaning and often cannot meet the actual business usage needs. If you want to improve the generation quality, you need to use hard coding or manual Excel generation to achieve it. This method not only requires specialized personnel to adapt. In addition, the logic of this method is usually not reusable and very difficult to expand. That is, it cannot be deployed quickly, is costly, inefficient, and of poor quality, and it is difficult to meet the needs of financial institutions for test simulation data.

[0004] In the prior art, the method for generating simulation data has the following problems:

[0005] 1) The simulation data generation method based on the existing technology cannot support data generation with business logic rules, and the quality of the generated simulation data is poor;

[0006] 2) Based on the existing simulation data generation method, different program codes need to be developed for different data generation logic requirements, which has poor scalability and low production efficiency;

[0007] 3) Complex logic requires manual data generation, which is not only costly but also difficult to determine the quality when generating large amounts of data, making it difficult to meet the requirements for high-quality data during the development and testing process. Summary of the invention

[0008] In view of the above problems, the present invention is proposed to provide a method and system for realizing simulation data generation that overcomes the above problems or at least partially solves the above problems.

[0009] According to one aspect of the present invention, a method for generating simulation data is provided, the method comprising:

[0010] Define the simulation data information configuration table;

[0011] Parsing the rules in the simulation data information configuration table into multiple generation rules according to type;

[0012] Generate large models based on multiple generation rules input to multiple types of data to generate simulation data;

[0013] Generate corresponding verification rules according to the rules in the simulation data information configuration table;

[0014] The generated data is verified. If it passes, the result is generated. If it fails, the failure reason and data are input into the data generation model until the verification passes.

[0015] Optionally, the definition of the simulation data information configuration table specifically includes:

[0016] Create a simulation data information configuration table, including the name of the data table to be generated, field attributes, reference data information, and data generation rules.

[0017] Optionally, the data generation rules specifically include: field type, field length, field unique constraint, generation relationship of different fields, association relationship of different tables, data meaning description, field dictionary range, number of data items, and data distribution rules.

[0018] Optionally, the multiple types specifically include: date type, character type, long text type, integer type and decimal type.

[0019] Optionally, the verification rules specifically include: field type restriction, maximum length restriction, field unique constraint restriction, field association relationship restriction, dictionary range restriction and data meaning restriction.

[0020] The present invention further provides a system for realizing simulation data generation, which uses a method for realizing simulation data generation according to any one of claims 1 to 5, characterized in that the system comprises:

[0021] Information configuration module, used to define the simulation data information configuration table;

[0022] A rule parsing and building module, used for parsing the rules in the simulation data information configuration table into multiple generation rules according to type;

[0023] A data generation module is used to generate a large model based on multiple types of data input according to multiple generation rules to generate simulation data;

[0024] The data quality assessment module is used to generate corresponding verification rules according to the rules in the simulation data information configuration table; the generated data is verified, and if it passes, the result is generated; if it fails, the failure reason and data are input into the data generation model until the verification passes.

[0025] The present invention provides a method and system for realizing simulation data generation, the method comprising: defining a simulation data information configuration table; parsing the rules in the simulation data information configuration table into multiple generation rules by type; inputting multiple types of data generation models according to the multiple generation rules to generate simulation data; generating corresponding verification rules according to the rules in the simulation data information configuration table; verifying the generated data, if it passes, generating results, if it fails, inputting the failure reasons and data into the data generation model until the verification passes. It can support the generation and verification of simulation data in a configuration-only, code-free manner, reduce the human resources required for the simulation data generation and verification process, improve the quality of automatically generated simulation data, and improve the efficiency of the development and testing process.

[0026] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0028] Figure 1 A flowchart of a method for generating simulation data provided by an embodiment of the present invention;

[0029] Figure 2 A block diagram of a system for implementing simulation data generation provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0031] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0033] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0034] like Figure 1 As shown, a method for realizing simulation data generation includes the following steps:

[0035] Create a simulation data information configuration table, which includes the name of the data table to be generated, field attributes, reference data information, and data generation rules;

[0036] Get the data generation information contained in the simulation data information configuration table, splice the table fields with associated relationships, find the table unique identifier according to the table association relationship, and split it into different logical rules for generating data according to the data types of different fields;

[0037] According to the information contained in the simulation data information configuration table, all data generation rules are parsed to obtain corresponding verification rules;

[0038] According to the split data generation logic, it is put into the data generation model under the corresponding data type to generate the corresponding data;

[0039] Traverse the generated data, execute the methods corresponding to different verification rules in turn according to the generated verification rules, and record the corresponding verification results;

[0040] If all validation rules are passed, the generated data will be returned. If not, after all validation rules are executed, the erroneous data and the reasons will be submitted to the data generation model for regeneration until all validations are passed.

[0041] Data generation rules include: field type, field length, field unique constraint, generation relationship of different fields, association relationship of different tables, data meaning description, field dictionary range, number of data items, and data distribution rules (average generation, extreme generation, progressive generation, and intensive generation).

[0042] The data types of different fields include: date type, character type, long text type, integer type, and decimal type.

[0043] The validation rules derived based on the data generation rules include: field type restrictions, maximum length restrictions, field unique constraint restrictions, field association relationship restrictions, dictionary range restrictions, and data meaning restrictions.

[0044] like Figure 2 As shown, a simulation data generation implementation system includes: an information configuration module, a rule parsing and building module, a data generation module, and a data quality assessment module;

[0045] An information configuration module is used to configure the generation rules of the data to be generated according to the preset template;

[0046] A rule parsing and building module is used to parse the input data generation rules to form input conditions for the data generation module and the data verification module;

[0047] A data generation module, used to generate simulation data according to the rules generated by the analysis;

[0048] The data quality assessment module is used to verify the quality of data generation and filter out erroneous data.

[0049] The preset template includes the table name, field name, field type, field length, field constraints, the relationship between different fields, data generation range, distribution rules, number of data items, reference data information, etc.

[0050] Based on the simulation data generation method, in actual use, you only need to configure the information configuration module to directly generate simulation data that meets actual needs, without the need for complex logic writing and logic verification. This meets the needs of simulation data generation in different scenarios and improves efficiency and the quality of generated data.

[0051] Beneficial effect: The purpose of the present invention is to propose a method for generating simulation data, which can support the generation and verification of simulation data in a way that only configuration is required without the need for code, reduce the human resources required for the simulation data generation and verification process, improve the quality of automatically generated simulation data, and improve the efficiency of the development and testing process.

[0052] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for generating simulation data, characterized in that: The implementation method includes: Define the simulation data information configuration table; Parsing the rules in the simulation data information configuration table into multiple generation rules according to type; Generate large models based on multiple generation rules input to multiple types of data to generate simulation data; Generate corresponding verification rules according to the rules in the simulation data information configuration table; The generated data is verified. If it passes, the result is generated. If it fails, the failure reason and data are input into the data generation model until the verification passes.

2. The method for realizing simulation data generation according to claim 1, characterized in that: The definition of the simulation data information configuration table specifically includes: Create a simulation data information configuration table, including the name of the data table to be generated, field attributes, reference data information, and data generation rules.

3. The method for realizing simulation data generation according to claim 2, characterized in that: The data generation rules specifically include: field type, field length, field unique constraint, generation relationship of different fields, association relationship of different tables, data meaning description, field dictionary range, number of data items, and data distribution rules.

4. The method for realizing simulation data generation according to claim 1, characterized in that: The multiple types specifically include: date type, character type, long text type, integer type and decimal type.

5. The method for realizing simulation data generation according to claim 1, characterized in that: The verification rules specifically include: field type restriction, maximum length restriction, field unique constraint restriction, field association relationship restriction, dictionary range restriction and data meaning restriction.

6. A system for realizing simulation data generation, applying a method for realizing simulation data generation according to any one of claims 1 to 5, characterized in that: The implementation system comprises: Information configuration module, used to define the simulation data information configuration table; A rule parsing and building module, used for parsing the rules in the simulation data information configuration table into multiple generation rules according to type; A data generation module is used to generate a large model based on multiple types of data input according to multiple generation rules to generate simulation data; The data quality assessment module is used to generate corresponding verification rules according to the rules in the simulation data information configuration table; the generated data is verified, and if it passes, the result is generated; if it fails, the failure reason and data are input into the data generation model until the verification passes.

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