Software Testing and Quality Control

Cyclomatic complexity V(G) is calculated as the number of decision statements (predicate nodes) plus one, or more formally E - N + 2P for a connected graph. It measures program control flow complexity and the minimum number of test paths needed.

A Test Incident Report documents any unusual event during testing that requires investigation - such as defects,环境 issues, or unexpected behaviors. A test log is a chronological record, test cycle is a testing iteration, and test item refers to the software component being tested.

Nonfunctional criteria (also called quality attributes) describe how a system behaves rather than what it does. Availability is a classic nonfunctional requirement specifying the percentage of time a system must be operational. Requirements (A), specifications (E), and failure modes (C) are functional or process-related, while defect density (B) is a quality metric rather than a requirement type.

Option D (Endurance Test) is correct because endurance testing specifically measures sustained performance over extended periods under continuous expected load - it tests for memory leaks, resource exhaustion, and performance degradation that accumulate over time. Load tests (A) measure capacity, stress tests (B) find breaking points, performance tests (C) measure responsiveness, and volume tests (E) test data volume handling - none focus specifically on sustainability.

Option B is correct because client-side data caching can dramatically improve performance for end users but will negatively skew test results by reducing server load during testing - the test won't accurately reflect actual server performance under load. Options A (load balancers), C (parameterization), and D (rendezvous points) are performance testing best practices that improve test accuracy, not skew results. Caching should be disabled or consistent during testing to get valid results.

Performance testing requires a test environment that closely mirrors production to yield meaningful results. With only 50% resources, the test server cannot accurately simulate production load patterns. Testing at reduced capacity or with reduced load will not reveal true performance characteristics.

All listed factors are common reasons why performance issues escape detection during testing. Unclear concurrent user definitions lead to inadequate load simulation. Insufficient test data fails to expose database performance issues. Environment differences mask production realities. Unsimulated network bandwidth hides latency problems.

Load testing measures system performance under anticipated production load to verify it meets performance requirements. Stress testing uses beyond-normal loads. Performance testing is broader. Endurance testing tests stability over long duration. Volume testing tests with large data volumes.

Performance testing measures response times and other metrics, often at lower loads to establish baselines or identify individual component performance. Load testing specifically targets expected production loads. The wording 'usually low load' distinguishes this as general performance measurement rather than load simulation.

Stress testing measures system behavior under unusually high or peak loads, often beyond normal capacity, to find breaking points. Load testing uses expected loads. Performance testing is broader. Endurance tests over time. Volume tests with large data. The phrase 'unusually high or peak loads' indicates stress testing.

A test scenario describes the sequence of events and conditions that occur during a testing session, including user actions, system responses, and environmental factors. Option A refers to a rendezvous point in load testing, B describes test script execution, and D refers to test creation. C correctly captures that a test scenario encompasses all events that happen during testing.

Even out-of-the-box implementations can have performance problems that only surface under load or specific conditions. These issues are often undocumented and may not be discovered until production use. Performance testing validates whether the OTB solution meets requirements, especially for critical transactions or peak loads. A is incorrect because OTB software can meet requirements; B and D are irrelevant to testing need.

Endurance testing specifically checks if the application can sustain expected load over an extended period, revealing memory leaks, resource exhaustion, or degradation that occurs over time. Load testing measures performance at expected load; stress testing finds breaking points; performance testing is the general category; volume testing uses large data volumes. D is the specific answer for sustained load testing.

Report Studio includes built-in validation features that allow report authors to check for errors such as missing data items, incorrect calculations, or layout issues before running the report. This validation capability is accessible directly within the Report Studio interface. The other options are incorrect - validation does not require external scripts or macros, and Query Studio does not provide comprehensive validation for complex reports.

Software testing typically accounts for 40-50% of total software development costs according to industry studies and research. This includes activities like test planning, test design, test execution, and maintenance of test artifacts. The 10-20% range underestimates testing effort, while 70-80% and 5-10% are outside realistic industry ranges.