Find Interview Questions for Neudesic

Right Answer:
HTTP status codes are three-digit numbers returned by a server to indicate the result of a client's request. Common codes include:

- **200**: OK - The request was successful.
- **201**: Created - The request was successful, and a resource was created.
- **400**: Bad Request - The server could not understand the request due to invalid syntax.
- **401**: Unauthorized - Authentication is required and has failed or not been provided.
- **404**: Not Found - The requested resource could not be found on the server.
- **500**: Internal Server Error - The server encountered an unexpected condition that prevented it from fulfilling the request.

Right Answer:
Rate limiting is a technique used to control the number of requests a client can make to a server within a specified time period. To apply it to REST APIs, you can implement mechanisms such as token buckets, leaky buckets, or fixed windows to track and restrict the number of API calls from a user or IP address, returning an error response when the limit is exceeded.

Right Answer:
Authentication in RESTful APIs can be implemented using methods like Basic Auth, OAuth 2.0, or JSON Web Tokens (JWT). Authorization is typically handled by checking user roles or permissions against the requested resource. For example, after authenticating a user, the server can issue a token (like a JWT) that the client includes in subsequent requests to access protected resources, where the server verifies the token and checks the user's permissions.

Right Answer:
To handle errors and exceptions in a RESTful API, use standard HTTP status codes to indicate the type of error (e.g., 400 for bad requests, 404 for not found, 500 for server errors). Include a consistent error response format in the body, providing details such as an error code, message, and any relevant information to help the client understand the issue. Log errors for internal tracking and debugging.

Right Answer:
Some criteria for a Microsoft Access database include:

1. **Data Types**: Determines the kind of data that can be stored (e.g., text, number, date). Incorrect data types can lead to errors and data integrity issues.

2. **Primary Keys**: Uniquely identifies each record. Missing primary keys can result in duplicate records and difficulty in data retrieval.

3. **Normalization**: Organizing data to reduce redundancy. Poor normalization can lead to data anomalies and inefficient queries.

4. **Relationships**: Defines how tables relate to each other. Incorrect relationships can cause data inconsistency and complicate data retrieval.

5. **Indexes**: Improves query performance. Too many indexes can slow down data modification operations.

6. **Validation Rules**: Ensures data integrity by enforcing specific conditions. Poorly defined rules can lead to invalid data entries.

Right Answer:
I would first take a moment to assess the task and gather my thoughts. Then, I would communicate with my senior manager to clarify the requirements and express my concerns. I would also explore possible solutions or alternatives to make the task more manageable.