When you create too many indexes on a database table, it can lead to decreased performance. While indexes can improve query performance by speeding up data retrieval, they also come with overhead in terms of storage space and maintenance. Having too many indexes can result in slower data modification operations, such as inserts, updates, and deletes, as the database engine needs to maintain all the indexes whenever data changes. Additionally, excessive indexes can lead to increased disk I/O and memory usage, which can degrade overall system performance. Therefore, it's important to strike a balance between the benefits of indexing and the overhead it introduces, and only create indexes that are necessary for optimizing query performance.

Stress testing evaluates how the system behaves under extreme conditions, such as high traffic loads or resource shortages. It simulates heavy concurrent user activity to assess the system's robustness and ability to handle stress. Unlike load testing, which focuses on expected peak loads, stress testing pushes the system beyond its limits to identify potential failure points.

The immediate action to mitigate SQL injection vulnerabilities is to sanitize input data. This involves validating and cleaning user inputs before using them in SQL queries. Sanitization prevents attackers from injecting malicious SQL code into the application, thus protecting it from SQL injection attacks.

Duplicates

Test data generation tools play a crucial role in populating databases with relevant data for comprehensive testing. Relevant data closely resembles real-world scenarios and helps in uncovering potential issues that might not be apparent with random or synthetic data.

Profiling in database monitoring refers to the process of monitoring and analyzing database query performance. It involves examining various aspects such as query execution time, resource usage, and query optimization to identify bottlenecks and optimize query performance. By profiling queries, database administrators can gain insights into how queries are executed and identify opportunities for improving database performance.

This suggests a data integrity issue. Data integrity ensures the accuracy, reliability, and consistency of data throughout its lifecycle. In this scenario, the presence of duplicate records in the target database that were not in the source data indicates a failure in maintaining the integrity of the data during the ETL process.

Access control testing involves assessing the methods used to authenticate users and enforce authorization policies. Therefore, the correct option is "Authorization," as it pertains to defining and enforcing access rights. Authentication verifies the identity of users, encryption secures data during transmission or storage, and firewalls protect networks from unauthorized access but are not directly related to access control testing.

Manually deleting affected rows is not a recommended approach as it might lead to data inconsistency. Restarting the SQL Server service is a drastic measure and may disrupt other ongoing operations. Executing a new COMMIT TRANSACTION statement would finalize the changes, which is contrary to the goal of rolling back. The correct step is to use the ROLLBACK TRANSACTION statement to undo the changes made so far and maintain data integrity.

Test scripts in database testing are usually written using SQL (Structured Query Language) due to its capability to interact with databases effectively. SQL allows testers to perform various operations such as querying data, modifying database structure, and managing transactions, making it an essential tool for database testing.

Monitoring and profiling tools are primarily used in database testing to detect and analyze database performance issues. These tools help testers to monitor database activities, identify performance bottlenecks, and profile database behavior under different loads. By using monitoring and profiling tools, testers can gain insights into database performance metrics such as query execution time, resource utilization, and transaction throughput, which are crucial for ensuring the optimal performance of the database system.

Indexes improve query performance by allowing the database system to quickly locate records in large datasets. By creating indexes on columns frequently used in search conditions, the database can efficiently retrieve relevant data without scanning the entire table, resulting in faster query execution.