Here’s Section 1: QA Methodology & Linux & Docker for the demo interview. This section is designed for ~1 hour with 12 questions (theory + practical + scenario-based). Each question includes detailed sample answers.

✅ Section 1: QA Methodology & Linux & Docker

Topic Goals

• Assess understanding of QA principles, test planning, and defect lifecycle.
• Evaluate Linux command-line proficiency.
• Check Docker fundamentals and containerization concepts.

Q1. Explain the difference between Verification and Validation in QA.

Sample Answer:

• Verification ensures the product is built according to specifications (e.g., reviews, static analysis).
• Validation ensures the product meets user needs (e.g., functional testing, UAT).
• Example:
  • Verification: Checking design documents against requirements.
  • Validation: Running end-to-end tests to confirm expected behavior.

Q2. What is a Test Plan? What are its key components?

Sample Answer: A Test Plan is a document outlining the testing strategy, scope, objectives, resources, schedule, and deliverables. Key components:

• Scope & Objectives
• Test Items
• Test Environment
• Test Approach (manual/automation)
• Entry & Exit Criteria
• Risk & Mitigation
• Deliverables

Q3. How do you prioritize test cases?

Sample Answer:

• Based on Risk & Impact:
  • High-risk features → test first.
• Business Criticality:
  • Core workflows > optional features.
• Frequency of Use:
  • Common user paths > rare scenarios.
• Defect History:
  • Areas with past issues get higher priority.

Q4. Describe the Bug Lifecycle.

Sample Answer:

• New → Assigned → Open → Fixed → Retest → Verified → Closed
• Possible states: Rejected, Deferred, Duplicate, Cannot Reproduce.
• Tools: JIRA, Bugzilla, etc.

Q5. How do you ensure test coverage for a complex system?

Sample Answer:

• Use Requirement Traceability Matrix (RTM) to map requirements → test cases.
• Apply code coverage tools (e.g., gcov, coverage.py).
• Perform boundary value analysis, equivalence partitioning, and negative testing.

Q6. Linux: How do you check CPU and memory usage in real time?

Sample Answer:

• top or htop → real-time CPU/memory usage.
• free -m → memory usage summary.
• vmstat → system performance.
• ps aux | grep <process> → process-specific usage.

Q7. Linux: How do you find which process is using a specific port?

Sample Answer:

• lsof -i :<port>
• netstat -tulnp | grep <port>
• ss -ltnp | grep <port> (modern alternative).

Q8. Docker: Explain the difference between an Image and a Container.

Sample Answer:

• Image: A read-only template with instructions to create a container (e.g., OS + app).
• Container: A running instance of an image with its own filesystem, processes, and network.
• Analogy: Image = Class, Container = Object.

Q9. How do you persist data in Docker containers?

Sample Answer:

• Use Volumes:
  • docker volume create mydata
  • docker run -v mydata:/app/data myimage
• Or Bind Mounts:
  • docker run -v /host/path:/container/path myimage.

Q10. How do you troubleshoot a failing Docker container?

Sample Answer:

• docker ps -a → check container status.
• docker logs <container> → view logs.
• docker exec -it <container> /bin/bash → enter container.
• Check resource limits: docker inspect <container>.

Q11. Scenario: Your automated tests fail intermittently on a Linux CI server. How do you debug?

Sample Answer:

• Check logs for patterns.
• Verify resource usage (CPU/memory).
• Check network stability if tests depend on external services.
• Add retry logic for flaky tests.
• Use Dockerized environment for consistency.

Q12. Scenario: You need to run tests in an isolated environment without installing dependencies on the host. What’s your approach?

Sample Answer:

• Use Docker to containerize the test environment.

• Create a Dockerfile with all dependencies.

• Run tests inside the container:

  docker build -t test-env .
  docker run --rm test-env pytest

✅ Time Allocation:

• Theory (Q1–Q5): ~20 mins
• Linux (Q6–Q7): ~10 mins
• Docker (Q8–Q10): ~15 mins
• Scenarios (Q11–Q12): ~15 mins

👉 Do you want me to move on to Section 2: Gen AI & AI Tools now? Or should I also include a quick difficulty rating and expected answers for senior-level performance for Section 1?