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 Communication
Skills and practices for producing readable, maintainable, and idiomatic code while clearly communicating intent. Candidates should demonstrate clear naming, logical structure, proper error handling, and writing code that other engineers can easily review and extend. This topic also covers narrating your thought process while coding, explaining trade offs between readability and optimization, identifying next optimization steps, and knowing when to avoid premature optimization. Interviewers will assess both the code you produce and your ability to explain design choices and sequencing of improvements.
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.
Frontend Performance and Optimization
Evaluate the ability to identify, measure, and remediate performance bottlenecks across components and at application scale. Candidates should discuss how to measure performance with browser tooling, avoid unnecessary reflows and repaints, prevent memory leaks, and reduce wasted work through memoization and controlled rendering. They should be able to explain code splitting and lazy loading strategies, image and asset optimization, caching policies and use of content distribution networks, trade offs between infinite scroll and pagination, and perceived performance techniques such as skeleton screens and progressive loading. Decision making should include cost, maintainability, and user experience trade offs.
Performance Optimization and Code Quality
Evaluate the candidates ability to identify performance bottlenecks propose pragmatic optimizations and maintain code quality. Topics include reducing unnecessary re renders rendering optimizations lazy loading code splitting bundle size reduction virtual scrolling pagination and choosing efficient data structures and algorithms. Candidates should explain profiling approaches using browser developer tools and telemetry to measure impact and present trade off analysis that balances performance gains with maintainability and development speed. The topic also covers writing modular testable code preventing memory leaks and following practices that improve long term code health.
Developer Experience and Code Quality
Practices and systems that make engineers productive and ensure a healthy codebase. Topics include type system strategies and TypeScript adoption, linting and formatting, static analysis, meaningful code review flow, design documents and contribution guidelines, developer tooling and local environment optimization, continuous integration and continuous delivery processes, automated checks, testing culture and test harnesses, documentation and onboarding, and measurable indicators of maintainability and velocity. Candidates should be able to reason about trade offs that improve developer throughput and long term code quality.
JavaScript Coding Patterns
Common and modern JavaScript coding patterns used to build maintainable, testable, and performant front end code. Topics include modern language features such as arrow functions, the spread operator, and destructuring, patterns for asynchronous code using promises and async await, functional programming idioms like immutability and composition, module and factory patterns, and robust error handling practices. Candidates should also discuss when to apply these patterns and trade offs between clarity and micro optimization.
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.