Download ISTQB.CT-PT.VCEplus.2025-03-22.23q.tqb

Protocol-level scripts measure the actual response times of network requests, making them ideal for analyzing network latency, bandwidth issues, and server response times.Option A (GUI scripts) measure user interactions, not network timing.Option B (API scripts) measure API interactions but do not provide detailed network response time analysis.Option C (HTTP scripts) measure web requests but lack low-level network insights.

A load generator is responsible for simulating virtual users and applying workloads to a system as defined by an operational profile. This allows testers to analyze how the system behaves under different load conditions.Option A (Background load) is incorrect because load generators create simulated user interactions, not just background noise.Option C (Record and analyze behavior) is the role of monitoring tools, not a load generator.Option D (Support root cause analysis) is incorrect because root cause analysis is done after the load test, using monitoring tools.

To ensure an accurate operational profile, it is crucial to validate and adjust it with key stakeholders before executing tests. This step ensures that the workload realistically represents actual user behavior.Option A (Executing the test first and adjusting later) is incorrect because adjustments should be made before execution to avoid misleading results.Option C (Aggregating profiles into a single generic profile) removes important distinctions between different user types, reducing test accuracy.Option D (Creating separate profiles and using equal proportions) does not match the actual power purchaser behavior, which requires a realistic representation of their higher-volume transactions.

When system resources are oversaturated (e.g., CPU, RAM, or network bandwidth), response times will degrade because the system struggles to process requests efficiently. This is a key performance bottleneck indicator.Option A is incorrect because response times do not improve under heavy load; they typically worsen. Option C is incorrect because error logging may actually increase rather than decrease under stress.Option D is incorrect because database size is independent of system saturation unless records are actively purged.

For batch processing performance metrics, the two most important factors are:Throughput -- Measures the number of transactions processed over time.Wait times -- Evaluates delays in processing batches.Option B (Number of records deleted) is irrelevant unless batch processing specifically involves deletions.Option C (Network latency percentage) applies to real-time transaction processing, not batch jobs.Option D (Concurrent virtual users) applies more to load testing rather than batch performance.

Aggregating test results helps stakeholders understand performance trends by combining data points from multiple test runs. This makes it easier to draw conclusions about system behavior.Option A is incorrect because aggregation may reduce detailed visibility, not increase it.Option B is incorrect because aggregation does not expedite testing itself.Option D is incorrect because aggregated results do not indicate test completion.

Performance monitoring tools collect real-time and historical performance data, particularly from server logs, application metrics, and infrastructure monitoring. This allows testers to analyze performance trends efficiently.Option A is incorrect because monitoring tools do not prevent malicious behavior but may detect it.Option C is incorrect since identifying multi-threading issues is typically done through profiling tools rather than performance monitors.Option D is incorrect as DoS attack detection falls under security testing.

Performance tests primarily identify resource bottlenecks such as CPU saturation, memory leaks, network congestion, and database slowdowns.Option B (Suitability issues) is a functional requirement concern, not a performance issue.Option C (Learnability concerns) relates to usability testing, not performance.Option D (Accessibility requirements) falls under compliance and usability testing, not performance testing.

Mobile and browser-based applications often rely on APIs for data retrieval and processing. Unexpected API load can cause latency issues, bottlenecks, and system crashes.Option A (Hard disk speed) is not a major issue in cloud-based or mobile systems.Option B (Misconfigured host machine) affects on-premise systems, not mobile/browser-based applications.Option D (Internet connectivity issues) is a user-side issue, not a system performance risk.

One of the key performance risks in mainframe architectures is slow hard disk speed, which can impact transaction processing, batch jobs, and database access times.Option A (Inconsistent loads via APIs) is more relevant to distributed or cloud architectures rather than mainframes.Option C (Misconfigured host machine) is a configuration issue, not a typical performance risk.Option D (Lack of RAM) is less common in mainframes, which typically use optimized memory management.