CT-PT Sample Questions Answers

Akey risk in distributed systemsisunreliable remote servers, which can lead tolatency, timeouts, and failuresin performance testing.

Option A (Hard disk de-fragmentation)is not a significant risk in distributed systems.

Option B (Excess memory)is apositive factor, not a risk.

Option D (Bluetooth connectivity)is unrelated todistributed system performance.

Aload generatoris responsible forsimulating virtual usersand applyingworkloads to a systemas defined by an operational profile. This allows testers to analyze how the system behaves under different load conditions.

Option A (Background load)is incorrect becauseload generators create simulated user interactions, not just background noise.

Option C (Record and analyze behavior)is the role ofmonitoring tools, not a load generator.

Option D (Support root cause analysis)is incorrect becauseroot cause analysis is done after the load test, using monitoring tools.

Performance monitoring toolscollectreal-time and historicalperformance data, particularly fromserver logs, application metrics, and infrastructure monitoring. This allows testers to analyze performance trends efficiently.

Option A is incorrectbecause monitoring toolsdo not preventmalicious behavior but may detect it.

Option C is incorrectsinceidentifying multi-threading issuesis typically done throughprofiling toolsrather than performance monitors.

Option D is incorrectasDoS attack detectionfalls undersecurity testing.

One of the keyperformance risks in mainframe architecturesisslow hard disk speed, which canimpact transaction processing, batch jobs, and database access times.

Option A (Inconsistent loads via APIs)is more relevant todistributed or cloud architecturesrather than mainframes.

Option C (Misconfigured host machine)is aconfiguration issue, not a typical performance risk.

Option D (Lack of RAM)is less common in mainframes, which typically useoptimized memory management.

Crowd-based load generationrelies on real users from different locations, makingtest conditions highly variable. This makes itdifficult to reproduce the same test scenario multiple timesunder identical conditions.

Option B (Less sensitive to changes)is incorrect becausecrowd-based load is highly sensitive to external conditions(network, device types, etc.).

Option C (Suitable for mainframe applications)is incorrect becausecrowd-based load testing is typically used for web and cloud applications, not mainframes.

Option D (More precise than other methods)is incorrect becausecrowd-based load testing lacks precision due to real-world inconsistencies.

Astatic performance testis anon-execution-based reviewthat analyzes system architecture, network configurations, and other elements thataffect system performance before execution.

Option A (Usability test)is not a static performance test but rather a functional or UX evaluation.

Option B (Evaluation of testers' skills)is unrelated to performance testing.

Option D (Formal signature approval)is an administrative task and not a static test.

Spike testingis a type of performance testing that evaluates how a systemresponds to sudden, extreme increases or decreases in load. It is designed to simulateunexpected surges in user activity or workload, such as flash sales, viral events, or cyberattacks.

Option A (Gradual load increase testing)describesload testing, not spike testing.

Option B (Handling expected peak load)describesstress testing, which pushes the system to or beyond its limits but does not focus on sudden changes.

Option C (Meeting future efficiency requirements)relates tocapacity planningrather than spike testing.

Spike testing helps toidentify system bottlenecks, resource allocation issues, and performance degradationwhen traffic surges unexpectedly.

Performance testing istime-sensitiveand must be designed tofit within the constraintsof the project timeline. If performance tests take too long to execute, they may not be feasible within a given sprint or development cycle. The results should be reproducible, meaning the same test on an unchanged system should yield the same results (making option C incorrect). While stakeholder expectations are important, performance tests should be objective and based on defined benchmarks rather than subjective expectations (making option D incorrect).

One of thebest practices in performance test scriptingis tovalidate that correct data is recorded in the databaseafter execution. This ensures thatperformance issues do not impact data integrity.

Option A (Increasing the number of scripts)may providemore coverage but does not verify accuracy.

Option C (Adding transaction timers)is useful for performance monitoring but does not ensurecorrect data entry.

Option D (Holding the development team accountable)is amanagement responsibility, not a scripting best practice.