1. What is the primary purpose of load testing in real-time systems?
(A) To replace the operating system
(B) To evaluate system behavior under expected or peak task loads
(C) To store historical data without analysis
(D) To execute batch-only operations
2. Load testing helps in identifying:
(A) Memory-only problems
(B) CPU idle exclusively
(C) Disk batch-only issues
(D) Performance bottlenecks, missed deadlines, and resource contention
3. During load testing, the system is typically subjected to:
(A) Disk batch-only workloads
(B) CPU idle exclusively
(C) Gradually increasing task loads up to or beyond expected limits
(D) Memory-only tasks
4. Metrics commonly measured during load testing include:
(A) Disk batch-only measurements
(B) CPU idle exclusively
(C) Response time, throughput, latency, and resource utilization
(D) Memory-only metrics
5. One objective of load testing in hard real-time systems is:
(A) CPU idle exclusively
(B) Ensuring all deadlines are met under peak load conditions
(C) Disk batch-only performance
(D) Memory-only constraints
6. Load testing can help in detecting:
(A) Task starvation and priority inversion issues
(B) CPU idle exclusively
(C) Disk batch-only bottlenecks
(D) Memory-only conflicts
7. Synthetic workload generation in load testing involves:
(A) Disk batch-only simulations
(B) CPU idle exclusively
(C) Creating artificial tasks and events to simulate expected load conditions
(D) Memory-only task generation
8. Trace-driven load testing uses:
(A) Memory-only events
(B) CPU idle exclusively
(C) Disk batch-only traces
(D) Actual execution traces from real systems to replicate realistic workloads
9. Load testing helps in tuning:
(A) Scheduling policies, resource allocation, and task priorities
(B) CPU idle exclusively
(C) Disk batch-only settings
(D) Memory-only configurations
10. In distributed real-time systems, load testing evaluates:
(A) Memory-only metrics
(B) CPU idle exclusively
(C) Disk batch-only traffic
(D) Network latency, message throughput, and inter-node coordination under load
11. A major benefit of load testing is:
(A) CPU idle exclusively
(B) Identifying system limitations before deployment
(C) Disk batch-only verification
(D) Memory-only analysis
12. Stress testing differs from load testing in that:
(A) Disk batch-only stress
(B) CPU idle exclusively
(C) Stress testing evaluates extreme or abnormal conditions beyond normal load
(D) Memory-only stress
13. Load testing can help prevent:
(A) System crashes, deadline misses, and unexpected failures under peak conditions
(B) CPU idle exclusively
(C) Disk batch-only errors
(D) Memory-only faults
14. Tools used for load testing in real-time systems often provide:
(A) Memory-only analysis
(B) CPU idle exclusively
(C) Disk batch-only monitoring
(D) Metrics visualization, logging, and alerts
15. Effective load testing requires:
(A) Disk batch-only simulations
(B) CPU idle exclusively
(C) Realistic workload models, accurate system representation, and repeatable conditions
(D) Memory-only setups
16. Load testing can improve system design by:
(A) Highlighting areas needing optimization or redesign before deployment
(B) CPU idle exclusively
(C) Disk batch-only improvements
(D) Memory-only fixes
17. Resource contention observed during load testing indicates:
(A) Disk batch-only contention
(B) CPU idle exclusively
(C) Multiple tasks competing for the same CPU, memory, or I/O resources
(D) Memory-only conflicts
18. Task deadline monitoring during load testing ensures:
(A) Memory-only timing
(B) CPU idle exclusively
(C) Disk batch-only deadlines
(D) Critical tasks complete within their time constraints even under high load
19. Load testing results can guide:
(A) System tuning, resource allocation, and task prioritization strategies
(B) CPU idle exclusively
(C) Disk batch-only adjustments
(D) Memory-only optimizations
20. The main advantage of load testing in real-time systems is:
(A) CPU idle exclusively
(B) Ensuring reliable, predictable, and efficient performance under expected and peak conditions
(C) Disk batch-only validation
(D) Memory-only evaluation