Database testing is a form of software testing that focuses on validating the data stored in a database. This includes ensuring that the structure and content of the data itself, as well as the relationships between individual elements of the data, are correct. The term “database testing” may also include performance testing, where performance problems that occur when running queries against the database are detected.
Database Testing Means
Database testing is an approach to software development that provides a systematic way of ensuring the quality of the data within, as well as the programs that interact with it. The goal of such tests is to identify errors in data access code and ensure that data cannot be corrupted by any application using it.
The process ensures that all required changes are made to the data and routines of a database system. This makes sure that any new code functions as expected, and doesn’t corrupt or delete existing data. Database testing involves two major steps:
Database testing is also performed to ensure that external systems work with the database successfully. If new programs are developed to interface with an existing database, they are tested to ensure that they have no adverse effects on the existing data.
Database testing takes place after unit, integration, and system tests to find out any errors in code or structuring of the database itself. It involves checking both logical and physical levels of the database for problems, including inter-record relationships and foreign key constraints. Most systems contain multiple databases; in such cases, each database is validated.
What are the benefits of Database Testing?
Like any part of the development process, database testing has its pitfalls and benefits. The drawbacks mainly relate to the time it takes to do the testing, as well as refactoring existing code and data. However, there are several reasons why you should perform database tests on your application:
- Database testing has the potential to improve the quality of your application significantly. It can be done at any point in a mature, stable project and will help you avoid problems in new code. In such cases, database tests should be performed as part of the unit test process before integration with other modules and databases.
- Database testing is not limited to checking for structural errors; it can also be used to ensure that existing data is formatted correctly. This saves time as the majority of bugs will be caught at this stage, and allows you to find and correct them before they progress further into the development cycle.
- Using database testing techniques means you will have a higher degree of confidence in your application working properly upon launch. It also means that the time taken to check for bugs will be reduced, allowing you to release on schedule.
- Database testing also helps reduce the risk in making changes to an existing database structure or design. If you know your new code functions correctly with the old system, it is easier to make needed updates and alterations later on during development.
- Database testing does require a certain amount of effort and investment in time. However, if you want to have the best chance of creating a stable application that performs well under a range of conditions, database testing is an essential step to take.
- Database testing is useful when changes need to be introduced to existing code. If something is broken or a new set of rules needs to be created for the database, it can be done and tested before deployment. This reduces the likelihood that errors will occur when users start working with the new data.
Types of database testing:
The various types of testing that can be accomplished are listed below. This list is not exhaustive and your specific needs may require different test combinations. Each type of tester has its own strengths and weaknesses, so you need to pick the appropriate testing method for the job at hand.
Based on its function and structure, a database can be divided into three basic categories:
- Structural Testing
- Functional Testing
- Non-functional Testing
It is very important to make sure that your testing covers not just the front end of the application, but other parts of the schema like triggers and functions.
Structural testing is the most basic type of database testing. It involves checking how well the schema and design are implemented in the code. Structural tests can be performed directly on the database or using a Data-Driven Testing tool like SQL Test/Borland Database Toolkit
These tools provide protection against poorly designed databases by imposing a set of predefined structure-related rules on all database entities. The code is then run against the database, and checks are performed to verify whether or not it follows the defined structural rules.
Structural testing usually takes place during development rather than as part of the continuous integration process. This is because structural tests generally only detect errors in the design phase.
One of the main benefits of structural testing is that it significantly reduces the number of issues found during integration. Structural tests ensure that, with a high degree of probability, entities are designed correctly and meet product requirements. This helps reduce problems when implementing the schema in code; typically these errors are more difficult to diagnose and correct than structural flaws.
Using schema testing will help you to identify the quality of your database design. It can be done during development, or after the project has been completed and issues are being identified as part of a software testing process.
Schema tests involve checking whether or not all constraints (such as unique keys) have been properly implemented using triggers and/or stored procedures.
The most important aspect of database testing is to ensure that the design meets all product requirements and satisfies customer expectations. With schema testing, you can check that the right rules are being implemented in your code for each entity. You can also see if these rules have been properly coded to handle all outputs correctly using various combinations of input values. This will help you to understand whether the system is going to work in real life, and it will give you a better overall understanding of how the product works.
Database/column testing is a part of structural testing and involves checking whether or not all the table columns (or database entities) that are required by your application exist in the schema.
Column tests should be performed on all tables to verify their existence, size, nullability, and so forth. It’s also advisable to perform column tests on tables that have been modified from the original database schema because there is a significant risk associated with adding new columns.
Often, when adding new columns to existing tables in a database, the application’s users will be unable to perform certain actions unless granted access to these columns. Column testing is designed to identify such cases before they become real issues in production. It involves creating test data for all entity types in the application database and setting up user accounts with the appropriate permissions for each test scenario.
Once column tests are carried out, you should be able to identify any issues that could prevent users from running certain business functions – or accessing data – if a new column is added to the database schema. This also helps you to avoid errors in which columns may not have been set up correctly; a column can be added but for the default value not to be set, which might lead an application to throw errors simply because it doesn’t expect data in that particular field.
Any changes to a database schema introduce risk. One of the biggest risks associated with changing a database is the fact that triggers and stored procedures may suddenly start throwing errors.
Trigger testing helps to detect errors in trigger logic early in the SDLC and reduce problems when implementing changes into existing systems. It involves creating test data for all entity types in the application database. A set of test scenarios are then created, typically based on the most common user interactions with the application. Finally, a set of triggers is created to handle these events and persistent data correctly.
These tests should be run against all codebase builds before releasing them into production. This helps prevent problems due to trigger changes breaking existing applications in production.
Stored Procedure and View testing
When changing stored procedures and views inside your database, there is the risk that you might inadvertently introduce bugs into code that is used by other databases too. This can lead to issues such as hard-to-diagnose data loss errors when data from different systems end up being combined in a single table.
Stored procedure and view testing help to identify any issues with the code that can result from changes to stored procedures and views. It should be carried out before any code goes into production, as it will help you to avoid scenarios in which, for example, a trigger written against one view might cause mistakes when run against another.
This testing involves creating test data for all entity types in the application database and setting up user accounts with the appropriate permissions for each test scenario.
Once the stored procedure and view tests have been carried out, you should be able to identify any issues that could prevent users from running certain business functions – or accessing data – if a new stored procedure or view is added to the database schema.
Database Server Validations
Database server validations may seem like a redundant activity, given that database changes are usually validated before going into production. However, it is important to remember that database changes are carried out overtime – daily, weekly, and monthly – by multiple teams. Therefore, there is always a chance of mistakes being made when implementing or modifying stored procedures and triggers without appropriate validation.
Database server validations help to ensure that these coding errors are caught sooner rather than later and don’t go unnoticed into production, potentially causing major issues with the database integrity or performance. It involves creating test data for all entity types in the application database. A set of test scenarios – based on the most common user interactions – is then created, using the stored procedures and triggers that have been modified.
Database server validations should take place before releasing any changes into production. This helps ensure that database integrity is not compromised by incorrectly coded databases, or errors caused by other teams not following best practices when implementing SQL Server stored procedures and views for their features.
Keys and Indexes Testing
Database schema changes have the potential to introduce risk due to the possibility of keys and indexes being invalidated. Changing or adding a key or an index on one table may cause issues if there is another table that relies on it; i.e.: If the primary key stored in one table uses a column from another, then changing this column across all affected rows could break foreign key validation rules.
Database keys and indexes testing helps to uncover any issues that might result from the introduction of a new key or index. It involves creating test data for all entity types in the application database and setting up user accounts with the appropriate permissions for each test scenario. Once this has been carried out, we can then run a set of test scenarios based on the most common user interactions, to ensure that no issues are encountered in production due to keys and indexes.
Then, once we’ve confirmed that our changes do not impact any other tables’ keys or indexes, we can be confident that there will be no adverse effects when they are deployed into production. Database Keys and Indexes Testing must take place before releasing any changes into production.
Functional Testing helps you to ensure that the application’s business functionality is working as expected. It involves creating test data for all entity types in the application database and setting up user accounts with the appropriate permissions for each test scenario.
Then, once we’ve confirmed that our changes do not impact any other tables’ keys or indexes, we can be confident that there will be no adverse effects when they are deployed into production.
Black Box Testing
Black box testing involves creating test data for all entity types in the application database and setting up user accounts with the appropriate permissions for each test scenario. Then, once we’ve confirmed that our changes do not impact any other tables’ keys or indexes, we can be confident that there will be no adverse effects when they are deployed into production.
Testing the application in a virtual environment provides an extra layer of security so that you can be sure it will function as expected when it is deployed into production.
Non-functional testing, also known as functional catching means that they are checking the capacity of a database software through numerous virtual users performing load, stress, and warning checks.
Load testing, also known as functional capacity testing ensures the performance data of all application modules do not exceed their specified thresholds under a given workload. Load or stress tests can be accomplished using dedicated tools that operate in real-time and generate manageable loads for client-tier systems, or they can be scripted from within the database.
Stress testing helps to ensure database server and application performance is within acceptable limits. Stress tests can be accomplished using dedicated tools that operate in real-time and generate manageable loads for client-tier systems, or they can be scripted from within the database.
Which tools are used for database testing?
There are a few tools you can use to test your database:
- DTM Data Generator
- MS SQL Servanter
- SQL Test
- Oracle SQL Developer
What are the advantages of database testing
Here I have listed some of the advantages of database testing:
- Database testing helps to minimize bugs: Testing can be utilized to expose flaws in the database design or development process. Data Quality Testing and other types of testing can be used to catch database inconsistencies, missing or poor-quality data.
Testing can also reveal potential performance problems and help you to understand how effectively database transactions are being processed.
- Database testing enhances the quality of the product: After database testing, you can release the updates with minimum issues. Database testing can be used to verify and confirm your database applications are operating correctly.
- Database testing helps to correct the defects: It can be used to identify and fix bugs. Database testing helps you to get rid of errors in database design, development, or maintenance.
- Database testing improves the performance of database applications: Through database testing, you can find potential performance issues and understand how effectively database transactions are being processed.
- Database testing increases confidence and security: Database testing helps you to avoid failures in the production environment, ensures that the fix is working as expected.
- Database testing increases productivity: Database testing can help you to get rid of errors in database design, development, or maintenance.
- Database testing provides better oversight: Database testing helps you to identify and fix the bugs in the production database.
- Database testing helps to track the progress: Database testing is helpful to document and describe specific test cases that were used to verify your database applications.
- Database testing provides a verification: You can use database testing to verify and confirm your database applications are operating correctly.
- Database testing ensures that the fix works as expected: Database Testing focuses on finding errors and providing solutions. It also helps to ensure fixes work.
- Database testing reduces the cost: Database Testing is an excellent way to improve your database applications and reduce their errors before they get released.
What are the disadvantages of database testing?
One disadvantage of database testing is that it requires specific expertise and tools, and the extent of testing depends on the size of your application. It may be difficult to test every possible issue and circumstance. If not conducted carefully, the tests can become a time-consuming distraction for developers that should be working on code instead.
Database testing is critical for ensuring your applications are functioning as expected between releases, and it adds value when used correctly to expose bugs or defects in components of the database. The most effective database testing is integrated with the other types of software testing, and conducted in parallel with related efforts such as integration testing, user acceptance testing, and performance testing.
Database-level tests are also helpful for quality assurance (QA) staff who must be sure that a release candidate meets its requirements before pushing it to users for QA or production use.
Database testing can be very time-consuming, and thus is sometimes ignored. Successfully addressing these problems requires a dedicated testing effort from database developers, testers, managers, and project sponsors.