Testing, Quality & Reliability Topics
Quality assurance, testing methodologies, test automation, and reliability engineering. Includes QA frameworks, accessibility testing, quality metrics, and incident response from a reliability/engineering perspective. Covers testing strategies, risk-based testing, test case development, UAT, and quality transformations. Excludes operational incident management at scale (see 'Enterprise Operations & Incident Management').
Testing and Test Execution
Writing and running tests to validate behavior and prevent regressions. Candidates should be able to design unit and integration tests that cover the golden path and edge cases, use mocks or dependency injection for isolation, run tests locally and in continuous integration environments, interpret test failures, and iterate on fixes. Interview tasks may ask you to write test cases for a function or to diagnose and fix failing tests.
Testing and Code Quality
Knowledge and practice of testing strategies and code quality processes that help ensure reliable, maintainable mobile applications. Candidates should be able to describe unit, integration, and end to end testing approaches; how to design testable code through separation of concerns, interface boundaries, and dependency injection; and practical usage of testing frameworks such as XCTest, JUnit, or Jest. They should explain techniques for mocking or stubbing network and persistence layers, structuring fast and deterministic test suites, and reducing flakiness. Discuss also code review standards, static analysis and linting practices, continuous integration pipelines for automated testing, and trade offs between test coverage and development velocity.
Code Quality and Debugging Practices
Focuses on writing maintainable, readable, and robust code together with practical debugging approaches. Candidates should demonstrate principles of clean code such as meaningful naming, clear function and module boundaries, avoidance of magic numbers, single responsibility and separation of concerns, and sensible organization and commenting. Include practices for catching and preventing bugs: mental and unit testing of edge cases, assertions and input validation, structured error handling, logging for observability, and use of static analysis and linters. Describe debugging workflows for finding and fixing defects in your own code including reproducing failures, minimizing test cases, bisecting changes, using tests and instrumentation, and collaborating with peers through code reviews and pair debugging. Emphasize refactoring, test driven development, and continuous improvements that reduce defect surface and make future debugging easier.
Comprehensive Testing Strategy (Unit, Integration, UI, E2E)
Comprehensive testing strategy for production mobile apps. Unit testing: testing business logic in isolation, mocking dependencies. Integration testing: testing interactions between layers and components. UI testing: testing user-facing features with appropriate frameworks. E2E testing: full user flow testing. Tools: XCTest (iOS), JUnit/Espresso (Android), Detox for cross-platform. Test coverage goals and test pyramid principles. Avoiding flaky tests, managing test data, CI/CD integration. Different testing strategies for different components.
Your QA Background and Experience Summary
Craft a clear, concise summary (2-3 minutes) of your QA experience covering: types of applications you've tested (web, mobile, etc.), testing methodologies you've used (manual, some automation), key tools you're familiar with (test management tools, bug tracking systems), and one notable achievement (e.g., 'I identified a critical data loss bug during regression testing that prevented a production outage').
Debugging and Recovery Under Pressure
Covers systematic approaches to finding and fixing bugs during time pressured situations such as interviews, plus techniques for verifying correctness and recovering gracefully when an initial approach fails. Topics include reproducing the failure, isolating the minimal failing case, stepping through logic mentally or with print statements, and using binary search or divide and conquer to narrow the fault. Emphasize careful assumption checking, invariant validation, and common error classes such as off by one, null or boundary conditions, integer overflow, and index errors. Verification practices include creating and running representative test cases: normal inputs, edge cases, empty and single element inputs, duplicates, boundary values, large inputs, and randomized or stress tests when feasible. Time management and recovery strategies are covered: prioritize the smallest fix that restores correctness, preserve working state, revert to a simpler correct solution if necessary, communicate reasoning aloud, avoid blind or random edits, and demonstrate calm, structured troubleshooting rather than panic. The goal is to show rigorous debugging methodology, build trust in the final solution through targeted verification, and display resilience and recovery strategy under interview pressure.
Production Readiness and Professional Standards
Addresses the engineering expectations and practices that make software safe and reliable in production and reflect professional craftsmanship. Topics include writing production suitable code with robust error handling and graceful degradation, attention to performance and resource usage, secure and defensive coding practices, observability and logging strategies, release and rollback procedures, designing modular and testable components, selecting appropriate design patterns, ensuring maintainability and ease of review, deployment safety and automation, and mentoring others by modeling professional standards. At senior levels this also includes advocating for long term quality, reviewing designs, and establishing practices for low risk change in production.
Automation Testing and Debugging
Focuses on methods and tooling for testing and debugging automated scripts and applications across environments and layers. Includes diagnosing flaky tests, analyzing test failures, reading and interpreting logs, setting breakpoints, using browser developer tools, capturing screenshots and video recordings, and using remote debugging approaches. Covers systematic root cause analysis to determine whether failures stem from test code, application code, environment or infrastructure, and strategies for isolating problems such as component level testing and reproducible minimal examples. Addresses cross layer troubleshooting across frontend, application programming interface, database and network components as well as platform specific testing considerations such as emulator versus real device behavior and mobile device operating system differences. Also includes best practices for test design, logging and monitoring, making test failures actionable for developers, and troubleshooting automation within continuous integration and continuous delivery pipelines and shared environments.
Technical Debt Management and Refactoring
Covers the full lifecycle of identifying, classifying, measuring, prioritizing, communicating, and remediating technical debt while balancing ongoing feature delivery. Topics include how technical debt accumulates and its impacts on product velocity, quality, operational risk, customer experience, and team morale. Includes practical frameworks for categorizing debt by severity and type, methods to quantify impact using metrics such as developer velocity, bug rates, test coverage, code complexity, build and deploy times, and incident frequency, and techniques for tracking code and architecture health over time. Describes prioritization approaches and trade off analysis for when to accept debt versus pay it down, how to estimate effort and risk for refactors or rewrites, and how to schedule capacity through budgeting sprint capacity, dedicated refactor cycles, or mixing debt work with feature work. Covers tactical practices such as incremental refactors, targeted rewrites, automated tests, dependency updates, infrastructure remediation, platform consolidation, and continuous integration and deployment practices that prevent new debt. Explains how to build a business case and measure return on investment for infrastructure and quality work, obtain stakeholder buy in from product and leadership, and communicate technical health and trade offs clearly. Also addresses processes and tooling for tracking debt, code quality standards, code review practices, and post remediation measurement to demonstrate outcomes.