What is a race condition, and how does it relate to synchronization?
- Concurrency
- Data inconsistency
- Parallelism
- Thread safety
A race condition occurs in concurrent systems when the outcome of operations depends on the timing or interleaving of multiple threads. It leads to data inconsistency and unpredictable results. Synchronization mechanisms like mutexes and semaphores are used to prevent race conditions by ensuring that only one thread can access a shared resource at a time, thereby maintaining data integrity and thread safety.
What is a segmentation fault, and what can cause it in memory management?
- Accessing an invalid memory address
- Buffer overflow
- Incorrectly configured hardware
- Insufficient memory space
A segmentation fault occurs when a program attempts to access a memory address that is not within its allocated memory space. This can happen due to bugs in the program's code, such as accessing an uninitialized pointer or trying to write to read-only memory. Insufficient memory space or buffer overflows can indirectly lead to segmentation faults by causing memory corruption.
How does the Shortest Job First (SJF) scheduling algorithm minimize average waiting time?
- SJF executes processes based on their arrival time, ensuring timely completion and minimizing waiting times.
- SJF minimizes average waiting time by executing longer jobs before shorter ones, ensuring fair allocation of CPU time.
- SJF prioritizes shorter jobs over longer ones, allowing quick tasks to complete first, thus reducing the average waiting time for all processes.
- SJF selects processes randomly, leading to a balanced distribution of CPU time and reducing waiting times.
Shortest Job First (SJF) scheduling minimizes average waiting time by prioritizing shorter jobs, which reduces the overall waiting time for processes in the ready queue. This approach is effective in scenarios where smaller tasks can be completed quickly, leading to better system responsiveness and improved resource utilization. However, SJF may face challenges in predicting job lengths accurately, especially in dynamic workloads, requiring adaptations like Shortest Remaining Time First (SRTF) to handle varying job durations effectively.
The _________ layer of the OSI Model handles logical addressing and routing of data packets.
- Application
- Presentation
- Network
- Transport
The correct option is Network. The Network layer of the OSI Model is responsible for logical addressing and routing of data packets. It establishes paths for data to travel through the network based on logical addresses (like IP addresses) and determines the best route for data transmission. This layer also manages congestion control and error handling. The Application layer deals with user interfaces and application-level protocols, Presentation layer handles data formatting and encryption, and Transport layer ensures reliable data delivery.
The _________ time is the time taken for the scheduler to switch from one process to another.
- Context
- Execution
- Response
- Turnaround
Context Switch time is crucial in multitasking environments as it directly impacts system efficiency. It includes saving the state of the current process, loading the state of the next process, and updating necessary data structures.
The SQL ___________ statement is used to modify data in a database.
- UPDATE
- SELECT
- INSERT
- DELETE
The correct option is "UPDATE." The UPDATE statement is used to modify existing data in a database table. It allows you to change the values of one or more columns in one or more rows based on specified conditions.
Which mechanism is used to prevent multiple threads from accessing shared resources simultaneously?
- Encapsulation
- Inheritance
- Mutex
- Polymorphism
The mutex (mutual exclusion) mechanism is employed to prevent multiple threads from simultaneously accessing shared resources, ensuring that only one thread can access the resource at a time, thus avoiding conflicts and data corruption.
Imagine you're designing a web application that requires real-time communication between the client and server. Which protocol(s) would be suitable for implementing this feature, and how would you ensure efficient data transfer?
- HTTP Long Polling
- MQTT (Message Queuing Telemetry Transport)
- WebSocket
- XMPP (Extensible Messaging and Presence Protocol)
WebSocket is suitable for real-time communication between the client and server because it establishes a persistent connection that allows bidirectional data flow with low latency. This eliminates the overhead of establishing new connections for each exchange, making it efficient for real-time applications such as chat, gaming, or collaborative editing. HTTP Long Polling involves repeated client-server requests, leading to higher latency and increased server load, making it less efficient for real-time scenarios. MQTT and XMPP are messaging protocols often used for IoT and instant messaging, respectively, but they are not optimized for real-time web applications like WebSocket.
A company's website is experiencing frequent SQL injection attacks. How would you advise the development team to mitigate this security risk?
- Implement input validation and sanitization
- Regularly update and patch the web server and database management system (DBMS)
- Use parameterized queries
- Utilize a web application firewall (WAF)
Input validation and sanitization ensure that user input is validated and sanitized to prevent SQL injection attacks. Parameterized queries separate SQL code from user input, reducing the risk of SQL injection. Regularly updating and patching the web server and DBMS closes known vulnerabilities that attackers exploit. A WAF can detect and block SQL injection attacks, but it's not as effective as input validation and sanitization.
In a real-world scenario of a customer relationship management (CRM) system, discuss how normalization principles can be applied to handle customer data effectively while minimizing redundancy.
- Break customer data into multiple tables based on entities like contacts, orders, and products
- Create separate databases for different customer data
- Store all customer data in a single table
- Use non-relational databases
Normalization in a CRM system involves breaking down customer data into multiple tables such as contacts, orders, and products, linked by foreign keys. This reduces redundancy, ensures data consistency, and allows for efficient data retrieval and updates. Storing all customer data in one table would lead to redundancy and inefficiency, while separate databases or non-relational databases would not adhere to normalization principles.