You are tasked with developing a logging system for an Express.js application to log every incoming request. How would you implement middleware to log the details of every request made to the application?
- Create a middleware function that logs request details and use app.use to apply it globally to all routes.
- Include logging code within each route handler to log request details individually.
- Use a third-party logging library like Morgan and configure it within your Express.js application.
- Use JavaScript's built-in console.log within each route to log request details.
To log details of every incoming request in an Express.js application efficiently, you should create a dedicated middleware function that logs request details and use app.use to apply it globally to all routes. This centralizes logging and avoids duplicating code in each route handler. The other options are either less efficient or not recommended for production applications.
You are configuring a Node.js project and want to ensure that a certain command runs before your tests run each time. How would you configure this using the package.json file?
- Use the "pretest" script in the "scripts" section of the package.json file to specify the command that should run before tests.
- Include the command in the "description" field of the package.json file.
- Create a separate pretest.json configuration file.
- Use a comment in the test file to specify the pretest command.
To ensure a certain command runs before tests each time, you should use the "pretest" script in the "scripts" section of the package.json file. This script will be executed automatically before running tests when the npm test command is invoked. The other options are not standard ways to configure pretest actions.
You are developing a suite of unit tests for a service that interacts with an external API. How would you employ mocking and stubbing to ensure the tests are isolated and reliable?
- Mock the external API calls to simulate responses
- Stub all internal functions used in the service
- Avoid mocking and use real external API calls
- Mock only the database interactions
In unit testing, it's crucial to isolate the code being tested. To ensure tests are isolated and reliable when dealing with an external API, you should mock the external API calls. This allows you to control the responses and not rely on external services during tests. Stubbing internal functions is not the primary approach for isolating external API calls. Avoiding mocking by using real API calls can lead to unreliable and slow tests. Mocking the database, in this case, is unnecessary.
The fs.watch method is used to watch for changes in a file or a directory but may not be consistent across platforms due to its reliance on ______.
- inotify
- polling
- event-driven
- file system events
The fs.watch method relies on polling on some platforms to detect file and directory changes. This polling approach may not be consistent across platforms and can have performance implications.
In a complex CORS scenario, how can you selectively allow certain types of requests while denying others?
- Create custom middleware
- Set Access-Control-Allow-Origin to *
- Use the OPTIONS method
- Configure server-side routing
In complex CORS scenarios, you can selectively allow or deny requests by creating custom middleware on your server. This middleware can inspect the request headers, methods, or other criteria to determine whether to allow or deny a request. The other options are components of CORS but do not provide fine-grained control over request types.
________ is a security practice that involves encoding information so that only authorized parties can access it.
- Encryption
- Hashing
- Salting
- Obfuscation
Encryption is a security practice that involves encoding information in a way that only authorized parties with the decryption key can access it. This is commonly used to protect sensitive data during transmission and storage.
In a system following eventual consistency, what implications does it have on Read operations after a Write operation?
- Strong consistency
- Read operations may return stale data
- Write operations are blocked until consistency is achieved
- Write operations are delayed
In a system with eventual consistency, Read operations may return stale or outdated data for a period of time after a Write operation. This is because eventual consistency prioritizes availability and performance over strict consistency. Strong consistency (Option 1) ensures that all reads return the most recent write but may lead to higher latency. Options 3 and 4 are not characteristic of eventual consistency.
How can you define optional route parameters in Express.js?
- Enclose parameters in square brackets [param]
- Use the optional keyword before the parameter
- Use the ? symbol after the parameter
- Wrap parameters in parentheses (param)
In Express.js, you can define optional route parameters by using the ? symbol after the parameter name, like /route/:param?. This makes the parameter optional, allowing it to match both routes with and without that parameter. The other options do not represent the correct way to define optional route parameters in Express.js.
What happens when an error is thrown inside an async function and it is not caught within the function?
- The error will be caught by the global error handler and potentially crash the application.
- The error is automatically logged to the console, but the function continues executing.
- The error is ignored, and the function continues executing.
- The error is caught by the JavaScript runtime and handled silently.
If an error is thrown inside an async function and is not caught within the function, it will propagate to the global error handler, which can potentially crash the application. Proper error handling is crucial in async code.
You are tasked with improving the performance of a database that experiences heavy read and write operations. How would you balance the use of indexing to improve read performance while minimizing the impact on write performance?
- Add Indexes to All Columns for Faster Reads
- Use Covering Indexes for Frequently Queried Columns
- Implement Partitioned Tables to Isolate Write-Intensive Data
- Regularly Rebuild All Indexes for Maximum Performance
To balance the use of indexing in a database with heavy read and write operations, it's crucial to use Covering Indexes for frequently queried columns. These indexes include all the necessary data for the query, reducing the need to access the main table. Implementing Partitioned Tables can isolate write-intensive data from read-intensive data, improving write performance. Adding indexes to all columns and regularly rebuilding all indexes can lead to unnecessary overhead and hinder write performance.