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Question 1. Which term best describes a quantitative measure that directly reflects business performance against a strategic objective? A) Indicator B) Metric C) KPI D) Benchmark Answer: C Explanation: KPIs (Key Performance Indicators) are quantitative metrics linked to strategic goals, used to gauge performance. Question 2. In the GQM approach, what does the “Q” stand for? A) Quality B) Question C) Quantify D) Query Answer: B Explanation: GQM = Goal‑Question‑Metric; the “Q” denotes the specific question that translates a goal into measurable terms. Question 3. Which of the following is a characteristic of a “good” metric according to the SMART criteria? A) Ambiguous B) Time‑bound C) Generic D) Unverifiable
Answer: B Explanation: SMART metrics are Specific, Measurable, Achievable, Relevant, and Time‑bound; “time‑bound” ensures a deadline for evaluation. Question 4. A metric that tracks the number of defects per 1,000 lines of code is an example of: A) Process metric B) Product metric C) Project metric D) Financial metric Answer: B Explanation: Defect density measures product quality, relating defects to the size of the software artifact. Question 5. Which data type is considered qualitative? A) Average response time in milliseconds B) Number of tickets closed per week C) Customer sentiment expressed in free‑text comments D) CPU utilization percentage Answer: C Explanation: Qualitative data captures non‑numeric attributes such as sentiment or opinions. Question 6. The primary purpose of “monitoring” a metric is to: A) Predict future revenue
Question 9. Which method is most suitable for validating data accuracy in an automated logging system? A) Peer review of code B) Cross‑checking with manual logs C) Random sampling of log entries D) Surveying end users Answer: C Explanation: Random sampling allows verification that logged data matches actual events without exhaustive manual comparison. Question 10. Return on Investment (ROI) is calculated as: A) (Net profit ÷ Total cost) × 100% B) (Total revenue ÷ Net profit) × 100% C) (Total cost ÷ Net profit) × 100% D) (Net profit ÷ Total revenue) × 100% Answer: A Explanation: ROI measures the efficiency of an investment by dividing net profit by total cost and expressing it as a percentage. Question 11. Cost of Quality (COQ) includes which two main categories? A) Prevention and appraisal B) Development and maintenance C) Marketing and sales D) Licensing and support
Answer: A Explanation: COQ separates costs of conformance (prevention + appraisal) from costs of non‑conformance (failures). Question 12. Throughput in a production process is best defined as: A) Time taken to complete a single unit B) Number of units produced per time period C) Total inventory on hand D) Average waiting time before processing Answer: B Explanation: Throughput measures the rate at which the system delivers finished units. Question 13. Which metric directly measures customer willingness to recommend a product? A) CSAT B) CES C) NPS D) churn rate Answer: C Explanation: Net Promoter Score (NPS) asks customers how likely they are to recommend the product. Question 14. A high churn rate most likely indicates: A) Strong product adoption B) Poor customer retention
Question 17. An OKR consists of an Objective and: A) Key Results B) Operational Risks C) Knowledge Resources D) Organizational Roles Answer: A Explanation: OKR = Objective + Key Results; the key results are measurable outcomes that indicate progress. Question 18. Resource utilization is best expressed as: A) Number of projects completed per quarter B) Percentage of available capacity that is actively used C) Total headcount in the department D) Ratio of budget spent to budget allocated Answer: B Explanation: Utilization measures how much of the allocated resource capacity is being used. Question 19. Defect density is typically expressed as: A) Defects per person‑hour B) Defects per thousand lines of code (KLOC) C) Defects per test case D) Defects per sprint
Answer: B Explanation: Defect density normalizes defects to code size, commonly per KLOC. Question 20. Defect Removal Efficiency (DRE) is calculated as: A) (Defects found before release ÷ Total defects) × 100% B) (Total defects ÷ Defects found after release) × 100% C) (Defects found after release ÷ Total defects) × 100% D) (Total defects ÷ Defects found before release) × 100% Answer: A Explanation: DRE measures the proportion of all defects that were detected and removed prior to release. Question 21. A defect that escapes to production is known as: A) Defect leakage B) Defect re‑open C) Defect churn D) Defect regression Answer: A Explanation: Defect leakage refers to defects not caught during testing and discovered by end users. Question 22. Mean Time To Repair (MTTR) primarily reflects: A) Time from defect detection to its resolution B) Average time between successive failures C) Total development effort per sprint
B) Condition coverage C) Branch coverage D) Path coverage Answer: C Explanation: Branch coverage verifies that each decision outcome has been taken during testing. Question 26. Automation ROI is highest when: A) Test scripts are written in a proprietary language B) The same tests are executed repeatedly across releases C) Manual testing takes less than an hour per test D) The application changes rarely Answer: B Explanation: Reusing automated tests over many cycles maximizes return on automation investment. Question 27. Cyclomatic Complexity is used to assess: A) Number of defects per module B) Number of independent paths through code C) Frequency of code commits D) Average response time Answer: B Explanation: Cyclomatic Complexity counts linearly independent paths, indicating code complexity.
Question 28. Mean Time Between Failures (MTBF) is most appropriate for measuring: A) Development productivity B) System reliability over time C) Test case execution speed D) Customer satisfaction Answer: B Explanation: MTBF quantifies the average interval between successive system failures. Question 29. In observability, logs are best described as: A) Continuous numeric measurements over time B) Immutable records of discrete events C) End‑to‑end request traces D) Real‑time alerts Answer: B Explanation: Logs capture timestamped, immutable event records. Question 30. Which pillar of observability provides time‑series data such as CPU utilization? A) Metrics B) Logs C) Traces D) Alerts
D) Throughput Answer: B Explanation: Availability measures uptime as a percentage of total scheduled time. Question 34. The 95th percentile (P95) latency metric means: A) 95% of requests are faster than this value B) Average latency across all requests C) Maximum latency observed D) Minimum latency observed Answer: A Explanation: P95 latency indicates that 95% of requests complete faster than the reported value. Question 35. Saturation in a system is best interpreted as: A) Number of users logged in B) Degree to which resources are utilized relative to capacity C) Total number of microservices deployed D) Frequency of code deployments Answer: B Explanation: Saturation reflects how close a resource (CPU, queue) is to its maximum capacity. Question 36. In DORA metrics, a high Change Failure Rate suggests: A) Frequent successful deployments
B) Poor quality of code or testing processes C) Short lead times for changes D) Low deployment frequency Answer: B Explanation: Change Failure Rate = % of changes causing incidents; a high rate signals quality or process issues. Question 37. Lead Time for Changes measures: A) Time from incident detection to resolution B) Duration between code commit and production deployment C) Number of sprints required to complete a feature D) Time spent in code review Answer: B Explanation: Lead time captures the end‑to‑end time from commit to live service. Question 38. Which statistical method helps identify outliers in metric data? A) Linear regression B) Moving average C) Z‑score calculation D) Pareto analysis Answer: C Explanation: Z‑scores quantify how many standard deviations a value lies from the mean, flagging outliers.
Question 31. Which metric is most appropriate for measuring the reliability of a microservice over time? A) Mean Time To Repair (MTTR) B) Mean Time Between Failures (MTBF) C) Defect Density D) Cycle Time Answer: B Explanation: MTBF captures the average interval between successive failures, indicating reliability. Question 32. In the context of observability, a “trace” is best described as: A) A time‑series of CPU usage values B) A log entry containing an error message C) A record of the end‑to‑end path of a single request across services D) A histogram of request latencies Answer: C Explanation: Traces follow one request through all components, showing the flow and timing. Question 33. Which Service Level Indicator (SLI) would you use to evaluate API availability? A) 99.9% uptime per month B) Average request latency (ms) C) Error budget consumption D) Number of deployments per week Answer: A
Explanation: Availability (percentage of time the API responds successfully) is a classic SLI. Question 34. An error budget of 0.1% corresponds to an SLO of: A) 99.9% B) 99.0% C) 100% D) 0.1% Answer: A Explanation: Error budget = 1 – SLO; 0.1% error budget → SLO = 99.9%. Question 35. Which of the following best defines “saturation” in performance metrics? A) Number of concurrent users B) Ratio of current load to maximum capacity C) Total CPU time used D) Average response time Answer: B Explanation: Saturation measures how much of a resource’s capacity is being utilized. Question 36. The DORA metric “Change Failure Rate” is calculated as: A) (Failed deployments ÷ Total deployments) × 100% B) (Incidents ÷ Total changes) × 100% C) (Mean time to recovery ÷ Lead time) × 100% D) (Successful deployments ÷ Total changes) × 100%
