Extensible plug-in batch generation test data method, system, equipment and media

Abstract

The invention discloses a method, system, equipment and medium for generating test data in batches in an extensible plug-in. Extensible plug-in batch generation of test data methods, including: formulating data generation interface specifications and data type enumeration, processing form variables, generating data and packaging results, reading function lists and rendering function forms, and comparing database fields with Function mapping, get the data generation model; install the plug-in, make the main application load the plug-in, load the data generation model; read the input parameters of the data generation model, generate data in batches, convert the batch-generated data into SQL statements, and execute SQL in batches . Extensible plug-in batch generation test data system, including: data model generation module; plug-in loading module; data generation module. The invention also provides an expandable plug-in batch generation test data device and medium.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a method, system, device and medium for generating test data in batches through extensible plug-in. Background technique [0002] In the era of mobile Internet, the requirements for product iteration speed are getting higher and higher. In the traditional development mode, a large number of defects are found in the testing stage, resulting in a long testing cycle and delaying the timing of product launch. As a result, many test management tools and automated testing tools have appeared on the market to assist the leftward shift of testing work, and data preparation before the execution of test scripts is required before automated testing. [0003] There are many types of automated testing, such as interface testing, UI testing, and performance testing. Different test types have different requirements for test data. If you do interface testing, you usually need to prepa...

AI Technical Summary

Problems solved by technology

The former method is time-consuming, laborious and inefficient, especially when constructing data with complex structures and is very error-prone; the latter method has very high requirements for data cleaning and desensitization tools, and a slight negligence may cause Serious Consequences of Data Leakage

[0007] 2. It is completely unrealistic to rely on manual work to generate millions of data. Even using some random data generation tools has efficiency problems, and the resulting time cost is very high.

Images