CT-PT ISTQB Certified Tester - Performance Testing Questions and 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.

One of the mostcritical test acceptance criteriain performance testing is toensure that the hardware in the test environment is comparable to production. Differences inCPU, memory, disk I/O, or network infrastructurecandistort performance results.

Option A (Convincing stakeholders to set goals)is a planning activity, not an acceptance criterion.

Option B (Describing the system under test)is important but does not directly affect test acceptance.

Option D (Comparing baselined metrics)is useful, butwithout a comparable test environment, baseline metrics may be misleading.

Business stakeholders aremost concerned with risks that affect deployment and production stability. The primary risk in performance testing is that thetest environment may differ from production, leading to misleading test results.

Option A (HTTP response goals)is too technical for abusiness stakeholder audience.

Option B (Hardware specifications)is relevant for technical teams, not business stakeholders.

Option C (Support staff details)is alogistical aspect, not a key performance testing risk for business decision-makers.

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.

Crowd-based load generationinvolves using distributed users (e.g., cloud-based testers or real users). The mainchallengeis thatthe load generation can be difficult to reproduce consistentlydue to variations innetwork conditions, device types, and user behavior.

Option B is incorrectbecause load generation methods should adapt to system changes.

Option C is incorrectsince mainframe applications typically do not rely on crowd-based testing.

Option D is incorrectbecause crowd-sourced load testing is generallyless precisethan scripted load testing.

When system resources (e.g.,CPU, RAM, I/O) are oversaturated, the system becomes overloaded, leading toincreased response timesandpoor application performance.

Option A (Gradual improvement of response time)is incorrect becauseperformance degrades under heavy load.

Option C (Error logging decreases)is unlikely; in most cases, errorsincreasewhen systems reach their limits.

Option D (Database size decreases)is unrelated to performance saturation.

During performance testing, it is crucial to definefailure handling proceduresto ensure thatfailures do not introduce additional errorsinto the test execution process. This helpsmaintain test accuracyandavoid misleading results.

Option A (Meeting stakeholder expectations)is important but not the primary reason for defining failure handling.

Option C (Capturing all defects)is ageneral testing principle, not specific to failure handling in performance tests.

Option D (Minimizing distractions)is not a valid reason for defining failure handling.

One of thebiggest contributors to unreliable performance projectionsisdifferences between the test and production environments. If test environments do not matchCPU, memory, network configurations, and database setupsin production, the results may not berepresentative of real-world performance.

Option A (Redundancy between test and production environments)isnot a problem; it's actually beneficial for reliability.

Option B (Disagreement between stakeholders)can affect planning but does not cause unreliable projections.

Option D (Unrealistic stakeholder goals)affects expectations butnot the accuracy of projections.

Acloud-based environmentis themost cost-effectivesolution for performance testing. It offersscalability, pay-per-use models, and flexibility, allowing testers to simulate large workloadswithout expensive infrastructure investments.

Option A (Isolated lab environment)is costly due tohardware maintenance and infrastructure costs.

Option C (Mainframe environment)isexpensive and impracticalfor performance testing.

Option D (No environment)is not a viable option.