Challenges of Database Testing

Automated testing has many facets to it — everything from functional/non-functional to regression testing. All of which need to be done to ensure proper, clean product deliveries. There is a possibility that a few requirements are at a high level, so there is a need to breakdown those requirements into the smaller parts. Testing a database is a complex task and the testers face many challenges while performing this testing.

To end this, we need to discuss the below two questions:

1. What Is Database Testing and What Issues Does It Face?

A database is a digital library where information is categorized and stored in various tables, which a program pulls its queries from. The forms of data stored depends on the actions and needs of each various program, while the type of data could be anything from simple numbers and characters to images and encrypted high volume data. The database is considered as a heart of any application. Furthermore, with complex applications and scenarios, we need to have a robust and secure database expansion. Hence, performing database automation testing more accurately is equally essential for testing an application’s performance and functions. When an end user interacts with the program, anything from alterations to simply pulling the data can occur and almost every database must handle multiple concurrent queries.

The challenges this faces in testing is straightforward: verification of the data mapping and maintain ACID (Atomicity, Consistency, Isolation, Durability) properties, with a massive quantity of data that often is in a state of constant alteration.

Data mapping is simple; it's just making sure that the data stores properly and in the appropriate locations, and that when queried, the changes/requests for data occur to the correct entry. The issue comes from the sheer volume of data that must be tested since any issues here can be easily missed until the queried during functional testing and flags there. This wastes time having to go back and check to see if the wrong query was made or the log in the database was wrong. Testing to make sure the database upholds ACID properties is an issue itself due to what it consists of.

• Atomicity is often referred to as the “all or nothing rule,” meaning that when the database is queried with a request, the entirety of the query passes back properly. In short, if you request all kinds of cats in an animal database, you get back a list of all the cats; no dogs or kinds of cats missing from the list. Issues here mean there is a functionality problem in the database.

• Consistency is that each query pulls back consistent results and only valid data is stored in the database; two identical searches should have identical results and no dogs in a database about cats.

• Isolation is straightforward in that all queries should remain isolated from each other; databases have a multitude of queries from different users going at a time and these can’t affect each other or the system won’t work.

• Durability is just as it sounds, making sure that stored data can’t be manipulated by any external factors once a query has occurred. It would be really bad if your server housing the database had a power outage and all the data vanished.

While Trigger conditions and Schema are important to database testing, the challenges here aren’t a major issue; they mostly consist of not having a proper test procedure in place or user error. Generally, as long as it's not overlooked during Consistency and Atomicity validation, these aren’t issues. When you change something in the existing database or application that runs on the database to refactor it or add new functionality, you need to ensure that you have not broken anything. This requires you to perform database regression testing to either fix the errors or roll back the changes made in the database.

2. Why Is It Important to Complete Automated Testing and What Do We Get Out of It?

After explaining what a database is, it should be rather obvious why this needs to be tested properly, but there is one more factor most of them may not be aware of: the value of the database.

A company’s databases are often their most valuable asset; the tremendous volumes of stored data have tremendous worth, not even counting the cost it took to acquire all of the stored data. Even if a project ends, its database is kept, migrated to a server for storage, and carefully preserved and maintained. Depending on the industry and type of data in the database, this value can rise to astronomical levels; this is NOT an area to cut corners on ensuring security.

 The major reason to automate the whole database testing process is simple: cost in time and resources. It’s just faster, simpler, and overall more efficient, ensuring reliability and stability for products and services, all of which improves the reputation of the business. 

This seems simple, but think of having to do this manually; the time and resource cost alone for testing that massive amount of data, in the end, is just far too much information to test manually.

Whether from a cost or time perspective, it’s just not feasible, and having to check every time data is changed, migrated, or copied to another server, it would be an insurmountable task to take on — not to mention the implication of missing a single test case from user error if implemented manually.