How does the use of database locks impact transaction concurrency and performance?
- Deadlocks
- Improved scalability
- Increased concurrency
- Reduced contention
While database locks ensure data integrity by preventing concurrent access to shared resources, they can also lead to deadlocks, where two or more transactions are waiting for each other to release locks, causing a stalemate. This reduces concurrency and can degrade performance. To mitigate deadlocks, databases employ strategies such as deadlock detection and resolution, lock timeouts, and lock escalation.
What are some limitations of code coverage analysis?
- Code coverage analysis does not guarantee the absence of bugs.
- Code coverage can provide a false sense of security.
- Code coverage does not measure the quality of test cases.
- Code coverage metrics may vary depending on testing scenarios.
While code coverage analysis is valuable, it has limitations. It does not guarantee the absence of bugs, as it only measures the extent to which the code has been executed by tests. Additionally, achieving high code coverage can provide a false sense of security, as it does not necessarily indicate thorough testing or the absence of defects. Developers should be aware of these limitations and supplement code coverage analysis with other testing techniques to ensure robust software quality.
Which of the following elements is used to create a hyperlink in HTML?
In a large-scale e-commerce platform, multiple users are trying to purchase the same limited-stock item simultaneously. How would you handle concurrent transactions to ensure fair access and prevent overselling?
- Implementing a Reservation System
- Optimistic Locking
- Rate Limiting Purchases
- Using a Queue for Order Processing
To address concurrent purchases of limited-stock items, implementing a reservation system is effective. This involves temporarily reserving stock for a user during the checkout process, ensuring fair access and preventing overselling by managing stock availability in real-time.
What is benchmarking used for in Go?
- Code optimization
- Debugging
- Performance analysis
- Syntax checking
Benchmarking in Go is primarily used for performance analysis. It helps developers identify bottlenecks and inefficiencies in their code by measuring the execution time of specific functions or code blocks. This is crucial for optimizing the performance of Go programs.
In Go, methods are primarily used for what purpose?
- Code organization
- Data encapsulation
- Error handling
- Function reusability
Methods in Go are primarily used for code organization, allowing related functionality to be grouped together.
In database migration, the 'down' method is responsible for _______ the database schema.
- Creating
- Deleting
- Reverting
- Updating
Reverting
_______ is a popular assertion library used in Go for testing.
- assert
- assert.go
- check
- testify
testify is a popular assertion library in Go used for writing tests. It provides various assertion functions that make it easier to write expressive and readable test cases. Using testify simplifies the process of writing and maintaining test code in Go.
JavaScript _______ are objects that store collections of key-value pairs.
- Arrays
- Maps
- Objects
- Sets
JavaScript Maps are objects that store collections of key-value pairs. Unlike Objects, they allow any data type as a key and provide methods for easy manipulation.
What is the difference between client-side caching and server-side caching?
- Both client-side and server-side caching are the same.
- Client-side caching stores data on the server to improve performance. Server-side caching stores data in the user's browser cache.
- Client-side caching stores data on the user's device, reducing server requests. Server-side caching stores data on the server, reducing database or application server load.
- Neither client-side nor server-side caching exists.
Client-side caching occurs on the user's device, reducing the need for repeated server requests. Server-side caching, on the other hand, involves storing data on the server, alleviating load and enhancing overall system performance.