Since a database is such an important component of any programme, its accuracy and reliability must be controlled and generated in accordance with the application. Database testing is an important phase in the software development process that should not be overlooked. 

Let’s take a closer look at this process to better understand its significance, value, functions, types, and techniques.

1. What is Database Testing?

Database testing is a form of software testing that examines the database’s schema, tables, and triggers, among other things. It also verifies data accuracy and credibility. It could entail writing large datasets to load/stress check the database and ensure that it is responsive. Since the database is the heartbeat of every software programme, it is important to ensure that it is in good working order. Database monitoring is the method of ensuring that the database is in good working order. This is carried out in a supervised research environment. The method is also referred to as back-end testing or data testing.

Database testing is a multi-tiered process because it typically covers multiple areas. You must test the user interface layer, the business layer, the data access layer, and the database itself when performing a full database test.

Each of these layers contributes to a total and highly functional application.

2. Importance of Database Testing

Database testing is crucial in software testing because it guarantees that the data values and information obtained and saved in the database are correct. Database testing prevents loss of data, protects data from failed transactions, and prevents unauthorized access to data. Since databases are critical to any software application, database researchers must have a strong understanding of SQL. 

An app cannot be used properly unless it has a completely functional database. All data is stored in the database, which serves as the software’s vital back-end stage. To maintain and build information, as well as react to requests, applications depend on a perfectly functioning database. Data testing is primarily concerned with ensuring that the values and data contained in the database are correct.

When performing a database test, the tester must have a thorough knowledge of the programme. They must then make a list of all possible programme queries. This is something that the production team can help with. The database test will then determine if each query performs as expected in terms of its requirements. An application can have hidden flaws if database testing isn’t done properly. This could result in data being lost, not being generated, or being processed incorrectly while using the programme. This may have a significant impact on the app’s overall experience and functionality. Database testing also results in the reduction of the difficulty of backend requests. It also operates to ensure that no unsafe or inaccurate information is secured in the application’s backend. 

Since the Graphical User Interface has been the most accessible aspect of the application, the GUI is normally given far more attention by the test and development teams. After all, reinforcing the knowledge that is at the core of the application, referred to as the DATABASE, is also important. 

Let’s have a look at a banking app where a user can make transactions. Things to consider from a Database Testing or DB Testing perspective are as follows:

• The application saves user information in the application database and shows it to the user accurately.
•  In the meantime, no data is missing.
• The application does not save any details about half completed or interrupted operations.
• The details of the user cannot be accessed by someone other than the user.

To achieve all of the aforementioned goals, we must use data validation or data testing.

3. Types of Database Testing

The 3 types of Database Testing are

1. Structural Testing
2. Functional Testing
3. Non-functional Testing

Now we’ll take a look at each type and its subtypes one at a time.

3.1 Structural Database Testing

Structural Database Testing is a database testing methodology that verifies all elements within a data repository that are primarily used for information storage and cannot be specifically exploited by end-users. In structural database research, database server validation is also a significant factor. Mastery of SQL queries is needed to complete this testing successfully.

3.1.1 Schema Testing

In database testing, schema testing validates different schema formats connected with the database and confirms whether table/view/column mapping specifications are compliant with user interface mapping formats. Schema testing’s main goal is to ensure that the front-end and back-end schema mappings are identical. As a result, it’s also known as mapping testing.

Let’s go through the most significant schema verification checkpoints.

1. Validation of the various schema formats connected with the databases. Frequently, the table’s mapping format is incompatible with the mapping format used in the application’s user interface.
2. In the case of unmapped tables/views/columns, verification is needed.
3. It’s also essential to check if an environment’s diverse databases are compatible with the overall application mapping.

Let’s take a glance at some pleasant Database Testing methods for verifying database schemas.

1. For mapping testing, DBUnit, which is integrated with Ant, is ideal.
2. SQL Server enables testers to verify and query the database schema by writing basic queries rather than writing code.

For example, if developers wish to modify the layout of a table or remove it entirely, the tester must ensure that all Data Types and Viewpoints that rely on that table are consistent with the new structure. Another example is that if the testers want to compare the schemas of two databases, they can do so with simple queries.

3.1.2 Database Table, Column Testing

Let’s take a glance at some database and column testing reviews.

• Is the mapping of the database fields and columns in the backend consistent with the front-end mappings?
• Validation of the database fields and columns for the duration and naming convention as defined by the specifications.
• The existence of any unused/unmapped database tables/columns is confirmed.
• Validation of the system’s compatibility of data type and field length, compares the columns in the back-end database with those in the application’s front-end.
• Whether the database areas enable the user to enter desired user inputs as specified in the business requirement specification documentation.

3.1.3 Keys and Indexes Testing

Checks for keys and indexes that are essential –

• Verify that the necessary Primary Key Foreign Key constraints on the required tables have been established.
• Verify that the references to foreign keys are right.
• In both tables, make sure the primary key and the corresponding foreign keys have the same data type.
• Examine all of the keys and indexes to see if the proper naming conventions have been followed.
• Make sure the appropriate fields and indexes are the right size and length.
• According to the business requirements, to check whether clustered and non-clustered indexes have been generated on the appropriate tables.

3.1.4 Trigger Testing

Triggers are nothing but an action or set of actions performed on Tables or Views when Insert / Delete / Update or Truncate queries are executed. To test Trigger, we need to execute the SQL query embedded in the trigger independently first and record the result. Then execute the trigger as a whole and compare the results.

• Whether or not the appropriate coding conventions were observed during the Triggers’ coding phase?
• Examine whether the triggers that were performed for the respective DML transfers met the appropriate criteria.
• If the trigger correctly updates the data after it has been performed?
• In the context of the application under evaluation, verification of the requisite Update/Insert/Delete activates usability.

3.1.5 Database Server Validations

1. Examine the database server settings according to the company’s needs.
2. Check that the appropriate user has permission to perform only those types of behaviour that the application requires.
3. Check that the database server can handle the total number of user-transactions required by the business requirements.

3.2 Functional Testing

Functional database testing is a form of database testing that validates a database’s functional specifications from the viewpoint of the end-user. The primary objective of operational database testing is to determine whether or not database transactions and activities undertaken by end-users operate as planned. 

The following are typical requirements for database validations to be met.

• Is it possible to make a field compulsory while still enabling NULL values?
• Is the range of each field is of proper size?
• Is it true that all related fields in different tables have the same titles?
• Is it possible to find some measured fields in the database?

The verification of field mappings from the user’s end-perspective is the aim of this process. In this case, the tester will conduct a database operation before navigating to the appropriate user interface object to determine and check whether or not the correct field verifications had been performed. The converse scenario, in which the tester performs the very first procedure at the user interface and then justifies it from the back end, should also be implemented.

3.2.1 Validating the accuracy and continuity of data

It is critical to perform the following tests:

• Is the information logically organised?
• Is the data in the tables right and meets the requirements of the business?
• Is there any excessive data in the framework that is being tested?
• Is it true that data that has been modified through the user interface has been processed in accordance with the requirements?
• Is it true that TRIM operations were performed on the data once it was inserted into the test database?
• Whether or not the transactions were completed in accordance with the business requirement criteria, and whether or not the results were correct?
• If the transaction is completed effectively, has the data been properly engaged?
• If the transfer was not successfully completed by the end-user, if the data was effectively rolled back?
• Is it true that all of the transactions were completed using the design methodology prescribed by the program’s business requirements?

3.2.2 User Security and Login

The following factors must be taken into account when reinforcing login and user protection credentials.

• If the application prevents the user from progressing further in the application if 

The username is incorrect but the password is correct.

The username is right, but the password is incorrect.

The Username and password are also incorrect.

• Is the consumer only permitted to carry out the operations that are defined by the business requirements?
• Is the information safe from unauthorised access?
• Is it possible to build different user positions with different permissions?
• Is it true that all users have the necessary levels of access to the defined Database, as per the business requirements?
• Test that confidential data in the database, such as passwords and credit card numbers, is encoded and not kept in clear text. It’s a good way to make sure that all of your accounts have passwords that are both complicated and difficult to remember.

3.3 Non-Functional Testing

In the scope of database testing, non-functional testing can be divided into many groups based on the business criteria. Load testing and stress testing are examples of these. When it comes to the task of non-functional testing, load testing and stress testing, which can be combined under the banner of Performance Testing represent two distinct objectives and that is: 

3.3.1 Risk Quantification: 

Risk quantification aids investors in determining the various device reaction time requirements under different load levels. Any function involving quality assurance was created with this goal in mind. We must keep in mind that although load testing does not explicitly reduce risk, it does provide mitigation opportunities and an incentive for risk mitigation through the methods of risk detection and risk quantification.

3.3.2 Minimum system tools needed: 

The bare minimum system configuration required to meet shareholders’ formally defined performance standards. So that unnecessary hardware, software, and related cost of ownership may be reduced. This particular requirement can be classified as a requirement for overall market efficiency.

3.3.3 Load Testing

Load Testing is a non-functional software testing process in which the performance of a software application is tested under a specific expected load. The goal of Load Testing is to improve performance bottlenecks and to ensure stability and smooth functioning of the software application before deployment. Any load test should have a well-defined and documented purpose. Load testing necessitates the use of the following configurations.

• If the most commonly used user transactions are inefficient, they have the ability to affect the efficiency of all other transactions.
• In the final test suite, at least one non-editing user transaction should be included, so that the output of such transactions can be distinguished from that of other more difficult transactions.
• The more critical transactions that support the program’s core goals should have been included, as error under a load of these transactions has the biggest effect by definition.
• At least one editable transaction should be included in order to distinguish the output of these transactions from that of other transactions.
• Optimal response time for all potential requirements when dealing with a large number of virtual users.
• Timeframes for retrieving various records that are efficient.

 

Load Runner, Win runner, and JMeter are all useful load checking tools.

3.3.4 Database Stress Testing

Database Stress Testing is a form of testing that is used to put a database system through its paces under a huge workload before it fails. This aids in locating the database system’s failure point. To prevent overuse of resources, careful planning and efforts are needed. Torture testing or exhaustive testing are other terms for data stress testing.

Load Runner and JMeter are two important stress testing methods.

4. How to conduct Database Testing?

Database testing can be done using a variety of techniques and methods. These changes based on the programme, the questions involved, and the software developers’ expectations. However, the basic goal of testing is still the same. 

One methodology is transaction checking. This procedure ensures that each of the ACID properties functions correctly.

Schema testing ensures that all of the objects in the scheme work properly. This is accomplished by thoroughly inspecting each item. Here are some of the things that have been put to the test:

• Tools and databases
• Names of databases
• Configure the database
• Registration, records, and reset of the device
• a set of tables
• The amount of space available for each database
• Testing the indexes and keys

Basic database functions and processes are often subjected to stress and efficiency testing to ensure that they operate appropriately. The tester generates specific queries and performs them through the process to see how the programme reacts during stress and performance testing.

Whatever protocol and testing methods are used, the tester would need a good understanding of both SQL (Structured Query Language) and DML (Data Manipulation Language).

5. How can Testing Data be configured and prepared for Database Testing?

Preparing the testing data is one of the most critical stages of database testing, since consistent test data collection is crucial in this phase. So now is the time to talk about certain test data preparation techniques. In fact, there are only two of them. 

5.1 Test data preparation techniques

5.1.1 Adding new information

You must first clean the database before inserting any of the information as directed in your test cases. After you’ve entered all of the necessary information, you can begin running the test cases and filling in the “Pass/Fail” columns after comparing the planned and actual results. It will appear to be easy, but it is not. There are a few important considerations to follow:

• It’s possible that an empty database instance isn’t open.
• It’s possible that the test data you’ve inserted is inadequate for testing some cases like load testing and results.
• Due to database table dependencies, data insertion can become a difficult task.
• When you insert small test data, it can obscure certain problems, however a large data set will reveal them.
• Complex procedures and queries can be needed when adding data.

The above-mentioned concerns are the most critical when it comes to data preparation for research. However, there are some advantages of using this method:

• The execution of test cases becomes more effective.
• Bug isolation takes no time since the database is only loaded with data listed in the test cases.
• Testing and comparing outcomes takes less time.
• The testing procedure is uncomplicated.

5.1.2 A subgroup of sample data is selected from the real DB data.

This method is more useful and real for preparing test data. This method, however, is not for the faint of heart. You must have solid technical skills as well as understanding of SQL and DB Schema. So, in this case, you must copy and then use production data, substituting some parameter value with dummy values. Because it represents production data, this is probably the most consistent data subset for your test data. However, due to data privacy and security issues, this method is not always viable.

6. The most specific issues that arise during database testing and their solutions

Issue 1: To assess the origin of the database transactions, a huge proportion of overhead may be implicated.

Solution: The overall process preparation and scheduling should be coordinated so that there are no time or cost and expense problems.

Issue 2: New test data must be designed following the cleanup of old test data.

Solution: A pre-planned strategy and methods for generating test data should be available.

Issue 3: To ensure that SQL queries are capable of managing the necessary database test cases, a SQL generator is intended to convert SQL validators.

Solution: The continuous updating and maintenance of SQL queries is an essential part of the overall testing phase that should be included in the overall test strategy.

Issue 4: Because of the above requirements, the database testing procedure’s setup could be both expensive and time-consuming.

Solution: There should be a delicate balance struck between project efficiency and timeliness.

7. Myths or misunderstandings around database testing and their reality

 

Myth 1: Database testing necessitates a high level of experience and is a time-consuming task.

Reality: Proper and effective Database Testing in Software Testing ensures the entire application’s long-term functional reliability, so it’s essential to put in the effort.

 

Myth 2: Database checking creates an additional job bottleneck.

Reality: Database testing, on the other hand, brings more value to the entire research by uncovering secret problems and thereby effectively assisting in the improvement of the overall application.

 

Myth 3: The overall production phase is slowed by database testing.

Solution: A massive proportion of database testing contributes to the overall enhancement of the database application’s consistency.

 

Myth 4: Database testing may be prohibitively expensive.

Solution: Any spending in database testing is a long-term investment that ensures the application’s long-term reliability and robustness. As a result, database testing or SQL testing is needed.

8. Practices for Database 

1. Every data, including metadata and functional data, must be verified in accordance with the mapping provided by the requirement specification documents.
2. Validation of the test data that was generated by or in collaboration with the development team is needed.
3. The performance data is validated using both manual and automated processes.
4. For the creation of necessary test data conditions, various techniques such as cause-and-effect graphing, equivalence partitioning, and boundary-value analysis are used.
5. A crucial principle is the choosing of default table values for database reliability verification. If all appropriate login events’ log events have been effectively added to the database.
6. Is it true that scheduled jobs run on time?
7. Backup the database on a regular basis.

Conclusion

Database testing can be done in a variety of ways using the various resources available. However, the overall findings must remain consistent. With several different functions, variables, and procedures that go into a database, testers must grasp the fundamental concepts. When designing some type of programme, you should always make sure to thoroughly test the database.

Testdel also Extract , transformed , load and modeled your data from production data to  create identical scrambled data which is key for success for using your test environments.

Click here to find out more about TestDel test-environment management including database testing .