Understanding Database Testing
Database Testing is a critical aspect of software testing that involves verifying the structure, integrity, and performance of a database. This includes checking the schema, tables, triggers, and more. Additionally, it ensures that data integrity and consistency are maintained. The process may require executing complex queries to stress test the database and evaluate its responsiveness.
Why is Database Testing Essential?
Database Testing plays a crucial role in software testing because it validates the accuracy and reliability of the data stored and retrieved from the database. It helps prevent data loss, ensures that transaction data is not lost or aborted, and protects against unauthorized access. Given the database’s significance in any software application, testers must possess a strong understanding of SQL for effective database testing.
The Importance of Database Testing Beyond the GUI
In most software projects, the GUI (Graphical User Interface) often receives the most attention from testers and developers, as it is the most visible aspect of the application. However, validating the underlying data—the core of the application, known as the database—is equally important.
Database Testing in Practice: A Banking Application Example
Consider a banking application where users conduct transactions. From a database testing perspective, the following elements are crucial:
- The application must accurately store transaction information in the database and display it correctly to the user.
- No information should be lost during processing.
- The application should not retain data from partially performed or aborted operations.
- Unauthorized individuals must be prevented from accessing user information.
To achieve these objectives, rigorous data validation, or database testing, is essential.
Understanding the Distinctions Between User Interface Testing and Data Testing
| User-Interface testing | Database or Data testing |
|---|---|
| This type of testing is also known as Graphical User Interface testing or Front-end Testing. | This type of testing is also known as Backend Testing or data testing. |
| This type of testing chiefly deals with all the testable items that are open to the user for viewership and interaction like Forms, Presentation, Graphs, Menus, and Reports, etc. (created through VB, VB.net, VC++, Delphi – Front-end Tools) | This type of testing chiefly deals with all the testable items that are generally hidden from the user for viewership. These include internal processes and storage like Assembly, DBMS like Oracle, SQL Server, MYSQL, etc. |
This type of testing includes validating the
| This type of testing involves validating:
|
| The tester must be thoroughly knowledgeable about the business requirements as well as the usage of the development tools and the usage of automation frameworks and tools. | To be able to perform backend testing, must the tester have a strong background in the database server and Structured Query Language concepts. |
Types of Database Testing
The 3 types of Database Testing are
Structural Testing
Functional Testing
Non-functional Testing
Comprehensive Overview of Structural Database Testing
Understanding Structural Database Testing
Structural Database Testing is a specialized approach to database testing that focuses on validating all elements within the data repository. These elements are primarily used for data storage and are typically not accessible for direct manipulation by end-users. This testing process also involves validating database servers, ensuring they function correctly. Mastery of SQL queries is essential for successfully conducting structural database testing.
Schema Testing: Ensuring Database Consistency
Schema Testing, a crucial component of database testing, ensures that various schema formats within the database are validated. It checks whether the mapping formats of tables, views, and columns are consistent with the user interface’s mapping formats. The primary goal of schema testing is to ensure alignment between the front-end and back-end schema mappings, which is why it is often referred to as mapping testing.
Key checkpoints for effective schema testing include:
- Schema Format Validation: Ensuring that the schema formats associated with the database are accurate and compatible with the application’s user interface.
- Unmapped Elements: Verifying the presence and correctness of unmapped tables, views, and columns.
- Heterogeneous Databases: Ensuring consistency across different databases within the application environment.
Tools for Schema Validation
Several tools can assist in validating database schemas during testing:
- DBUnit (Integrated with Ant): Ideal for mapping testing.
- SQL Server: Enables testers to query and check database schemas with simple SQL queries, rather than relying on complex code.
For example, when developers make structural changes to a table, testers need to ensure that all associated stored procedures and views remain compatible. Similarly, schema changes between two databases can be compared using straightforward queries.
Database Table and Column Testing
When testing databases, it is essential to validate the tables and columns thoroughly:
- Mapping Validation: Ensuring that database fields and columns in the back-end align with those in the front-end.
- Field and Column Validation: Checking that the lengths and naming conventions of database fields and columns meet the specified requirements.
- Unused Elements: Identifying any unused or unmapped database tables or columns.
- Data Type Compatibility: Ensuring that data types and field lengths in the back-end match those in the front-end.
Additionally, it’s crucial to verify that the database fields allow user inputs as defined by business requirements.
Keys and Indexes Testing
Key points to consider when testing keys and indexes include:
- Primary and Foreign Keys: Verifying that the required constraints are established on the necessary tables.
- Key References: Ensuring that foreign key references are valid and that the data types of primary and foreign keys match.
- Naming Conventions: Checking that appropriate naming conventions are followed for all keys and indexes.
- Index Creation: Ensuring that both clustered and non-clustered indexes are created as specified by the business requirements.
Stored Procedures Testing
When testing stored procedures, the following aspects are critical:
- Coding Standards: Ensuring that the development team adheres to coding standards, error handling, and exception management.
- Condition Coverage: Verifying that all conditions and loops are adequately covered by the input data used in testing.
- Data Handling: Ensuring that TRIM operations are applied correctly when fetching data from database tables.
- Manual Execution: Testing stored procedures manually to confirm they produce the desired results and update table fields as expected.
- Trigger Invocation: Verifying that stored procedure execution correctly triggers the necessary actions.
Trigger Testing
When testing triggers, the following factors should be validated:
- Coding Conventions: Ensuring that the required coding standards are followed during trigger development.
- DML Transaction Execution: Verifying that triggers fulfill their intended purpose when executed during data manipulation operations.
- Data Update Accuracy: Ensuring that triggers update the database accurately once executed.
- Trigger Functionality: Validating the functionality of update, insert, and delete triggers within the context of the application under test.
By following these guidelines and using the appropriate tools, you can ensure comprehensive and effective database testing, leading to more robust and reliable database systems.
Comprehensive Database Validation and Testing
Server Configuration Validation
- Ensure that the database server configurations align with business requirements.
- Verify that users have appropriate authorization to perform only the actions required by the application.
- Confirm that the database server can handle the maximum number of user transactions specified in the business requirements.
Functional Database Testing
Functional Database Testing validates the database’s functionality from the end-user’s perspective. The goal is to ensure that all transactions and operations performed by users function as expected. Key checks include:
- Confirming whether fields are mandatory when allowing NULL values.
- Ensuring that field lengths are adequate.
- Verifying consistency in field names across tables.
- Checking for the presence of computed fields in the database.
This process involves validating field mappings from the end-user’s viewpoint. It’s crucial to perform operations at both the database level and the user interface level to ensure proper field validation.
Data Integrity and Consistency Checks
Data integrity and consistency are critical. The following aspects should be evaluated:
- Organization and logical structure of the data.
- Accuracy of stored data in relation to business requirements.
- Identification and removal of unnecessary data.
- Verification that data updates from the user interface are reflected accurately in the database.
- Validation that TRIM operations are performed before data insertion.
- Ensuring correct transaction execution and data commitment or rollback based on success or failure.
Login and User Security Validation
Login and user security are paramount. Key checks include:
- Preventing further application access with invalid credentials.
- Ensuring users can only perform operations specified by business requirements.
- Protecting data from unauthorized access.
- Creating user roles with appropriate permissions.
- Encrypting sensitive data, such as passwords and credit card numbers, to prevent storage in plain text.
- Ensuring complex passwords for all accounts to enhance security.
Non-Functional Database Testing
Non-functional testing encompasses various areas, including load testing, stress testing, security testing, usability testing, and compatibility testing. Specifically:
- Load Testing: Identify system response times under different load levels to assess risk and optimize system performance.
- Stress Testing: Determine the system’s breakdown point under heavy load, providing insight into its limitations.
Load Testing Considerations
Load testing is crucial for ensuring optimal performance. Key considerations include:
- Evaluating frequently used transactions for potential performance impacts.
- Including non-editing and editing transactions to differentiate performance characteristics.
- Focusing on transactions critical to the system’s core objectives to assess their performance under load.
- Measuring response times and record-fetching efficiency under high user loads.
Database Stress Testing
Database Stress Testing, also known as torturous or fatigue testing, is used to push the database system to its limits. This method identifies the system’s failure point under extreme loads and requires careful planning to avoid resource overuse.
Effective load testing tools include LoadRunner Professional, WinRunner, and JMeter.
Most common occurring issues during database testing
A significant amount of overhead could be involved to determine the state of the database transactions
Solution: The overall process planning and timing should be organized so that no time and cost based issues appear.
Myths or Misconceptions related to Database Testing
Database Testing requires plenty of expertise and it is a very tedious job
Reality: Effective and efficient Database Testing in Software Testing provides long-term functional stability to the overall application thus it is necessary to put in hard work behind it.
Essential Practices for Comprehensive Data Validation
Data and Metadata Verification: Ensure that all data, including metadata and functional data, aligns with the mapping outlined in the requirement specification documents.
Test Data Verification: Validate test data created with or consulted by the development team to ensure accuracy and reliability.
Output Data Validation: Use both manual and automated methods to verify the correctness of output data.
Advanced Testing Techniques: Employ techniques such as cause-effect graphing, equivalence partitioning, and boundary-value analysis to generate effective test data conditions.
Referential Integrity Rules: Validate the referential integrity rules for necessary database tables to maintain data consistency.
Database Default Values: Ensure that default table values are correctly selected and validated for database consistency.
Log Event Verification: Confirm that log events are successfully recorded in the database for all required login activities.
Scheduled Job Execution: Verify that scheduled jobs are executed promptly and as planned.
Timely Database Backups: Perform regular backups of the database to safeguard data.
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