Targeted data generation for application testing on databases

Applications that process large datasets are a widely used type of software. Particularly, these applications address data integration problems in the field of enterprise application integration. These problems are solved using special tool environments supporting the development, implementation, and monitoring of applications that implement the Extract, Transform, and Load (ETL) model. The specific feature of functional testing of such applications is that there are many possible combinations of input data. The approaches implemented in the data generation tools for functional testing of applications on databases, in the best case, are based on database and SQL-query schemes that are used in applications to be tested. These approaches ensure the coverage of functionality of an application under testing only by conducting an exhaustive search of possible combinations of input data. The approach to data generation proposed in this paper makes it possible to find a coverage of application functionality with a nearly optimal amount of data (one dataset for one functional branch of the application).