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Software Engineering Practices Topics

Covers industry-standard practices for building maintainable, high-quality software, including code quality, maintainability, documentation, and effective technical communication within engineering teams.

Code Quality and Technical Debt Management

Covers practices for writing readable, maintainable, and correct code and for managing long term code health. Topics include error handling, automated and manual testing, code review practices, refactoring and optimization, style and readability, continuous improvement, identification and quantification of technical debt, prioritization of pay down activities versus feature delivery, and measuring the impact of remediation efforts. Candidates should be able to explain decision criteria for when refactoring is worth the investment and how to institutionalize improvements.

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Scaling Developer Productivity and Experience

Approaches to increase team velocity and reduce friction as organization and codebases grow. Topics include improving feedback loop times, build and test performance, creating internal tooling and scaffolding, documenting conventions, automating repetitive tasks, improving developer onboarding, creating shared libraries and templates, and measuring productivity improvements. Candidates should propose concrete initiatives, discuss trade offs, and explain how to measure impact.

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Problem Clarification and Requirements

Best practices for clarifying a problem statement before designing or coding a solution. This includes restating the problem in your own words, enumerating inputs outputs and constraints, asking about expected ranges and performance targets, listing edge cases and invariants, and defining acceptance criteria. Strong answers make ambiguity explicit, prioritize clarifying questions, and present a short checklist to guide development and testing.

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Extensibility and Refactoring

Approaches for extending existing systems with new functionality and safely refactoring to improve maintainability. Candidates should discuss identifying extension points, designing stable interfaces, minimizing breaking changes, writing and updating tests, applying appropriate abstractions and design patterns, and performing incremental refactors to reduce risk. Evaluate trade offs between short term fixes and long term architectural work, as well as communication strategies to align the team during refactors.

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Code Navigation and Understanding Existing Codebases

Ability to read and understand unfamiliar or partially implemented repositories, identify where functionality lives, trace execution paths, and safely extend code. Candidates should demonstrate tactics for onboarding into a codebase such as locating entry points and core modules, reading tests and documentation, using debugger and logging to observe runtime behavior, understanding build and dependency systems, and making incremental, test backed changes. Interview prompts often present snippets or partial implementations and ask candidates to explain behavior, find bugs, or design small extensions consistent with the existing architecture.

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Working With Existing Codebases

Skills and practices for quickly understanding, navigating, and safely modifying an existing mobile codebase. Topics include reading architecture and module boundaries, using version history and code search to find ownership and intent, following and enforcing conventions, writing and running unit and integration tests, adding instrumentation, making incremental refactors, managing dependencies and build configuration, using feature flags and CI, and communicating changes through code reviews and documentation. Interviewers assess a candidate's ability to make low risk changes, reduce technical debt, and deliver features while preserving stability and clarity in a legacy or large codebase.

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Mobile Feature Implementation and Delivery

Translate feature requirements into a delivered mobile feature end to end. Skills include clarifying requirements with product and design, designing the user interface and interactions, defining data models and application programming interface contracts, selecting local storage and caching strategies, implementing state management and error handling, and creating a testing strategy that spans unit, integration, and user interface tests. Also include deployment planning, versioning, feature gating, performance trade offs, and cross team coordination with backend and quality teams. Demonstrate trade off analysis, backward compatibility planning, and instrumentation of metrics to measure adoption and health in production.

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Modular and Component Based Design

Principles and practices for breaking large mobile applications into modular reusable components and feature modules. Topics include module boundaries and public interfaces dependency management build time and packaging considerations dynamic feature delivery approaches for Android and analogous techniques for iOS strategies to enforce encapsulation and interface stability testing and continuous integration for modules and team ownership models. Candidates should be able to propose a modularization plan for a legacy app discuss migration approaches and explain trade offs between reuse and complexity.

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Debugging and Troubleshooting

Practical ability to systematically diagnose, reproduce, and resolve defects and runtime issues in mobile applications across platforms. Candidates should demonstrate proficiency with platform native tooling such as Xcode and Android Studio to inspect logs, set breakpoints, step through code, and collect stack traces. They should explain root cause analysis techniques, hypothesis driven debugging, and isolation strategies to reduce problem scope. Include approaches for reproducing intermittent issues and race conditions, use of network proxies and mock servers to simulate network faults, and how to leverage crash reporting and monitoring systems to triage production problems. Candidates should also describe when to add targeted tests or instrumentation to validate fixes and how to reason about asynchronous behavior, lifecycle transitions, threading, and memory interactions when troubleshooting.

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