Test data is a mandatory requirement for testing every software, because the data testing ensures smooth functioning of a software. In the past real-time data was used for quality assurance phase of every software, however, due to data protection regulations and privacy concerns genuine data cannot be used for testing. Therefore, software development companies keep trying to find new ways for synthetic data generation. This article discusses 5 popular methods of test data generation.
1. Manual Test Data Generation
It is the most simple and direct way of generating test data. It allows the testing team to generate data for all essential fields, test cases, and scenarios. The data is generated to test various scenarios, including null, valid, invalid, valid, data set for smooth performance.
Brightside: In this case, no additional resources are factored in, because the testing team uses their own skills and judgment to produce data.
Downside: This methods is not efficient because it requires too much of time. Moreover, it requires an expert resource having domain knowledge to create good data set. Yet, this method does not ensure error-free data generation.
2. Automated Test Data Generation
With the help of test data generation tools, a reliable synthetic data set is generated. This technique helps improve the process, and provides high volume of good data.
Brightside: The major benefit of using test data management tools is that the resulted data reliable and accurate. Moreover, it does not require resource allocation to produce data, and can function during non-working hours as well.
Downside: The biggest disadvantage of adopting this technique is its high cost. Moreover, this technique does not provide reliable required results if the system is too complex. In such case, the tool faces a difficulty to understand the system.
3. Back-end Data Injection
This technique utilizes back-end servers with a huge database. Since, the existing databases can be updated directly using the test data stored in the database, therefore, huge volume of data are available for use through SQL queries.
Brightside: Back-end data injection technique strikes off the need of front-end data entry; which requires optimum attention and cautiousness during data entry to avoid any error which might hamper the performance of database. Moreover the data can be injected into the system quickly. It does not demand highly expert persons to perform this process. With backend technique, you can create backdated entries as well which cannot be done using manual or automated test data generation techniques.
Downside: However, if it is not implemented correctly, backend data injection can cripple the whole system. Therefore, the personnel doing this must possess domain expertise so that he/she understands the data flow in the system, and also requirement of database tables.
4. Third-Party Tools
Third party tools allow efficient data generation and injection it into the system. Having a complete understanding about the back-end applications data, these tools can inject synthetic data into the system. The generated data is very similar to the real-time genuine data. Hence, you can have diverse data available in high volume efficiently.
Brightside: This method allows data accuracy because of the tools’ complete understanding of the system as well as the domain. Moreover, it allows backdated data entries as well which enable the testers to execute testing on historical data as well. Other than this, one does not need to have detailed domain knowledge and expertise to perform testing based on data generated by third-party tools.
Downside: the biggest disadvantage of this method is its huge cost. Not to mention, it offers limited use for a specific type of system only, which means that the data can only be used for specific users and applications.
5. Path wise Test Data Generators
Highly popular technique for data generation, path-wise method provides the user a defined approach instead of multiple paths. This eliminates the element of confusion, because the user has access to pertinent and good knowledge, and he can predict its coverage. All a user has to do is to enter the program to be tested, and the criteria of testing such as path coverage, statement coverage, etc.
There are various methods of generating synthetic test data. At GenRocket, our experienced team of professionals can assist you in picking the right method based on your requirements and program. Let’s join hands to make your business software smooth and error free by providing high-quality data testing.