Programming Languages & Core Development Topics
Programming languages, development fundamentals, coding concepts, and core data structures. Includes syntax, algorithms, memory management at a programming level, asynchronous patterns, and concurrency primitives. Also covers core data manipulation concepts like hashing, collections, error handling, and DOM manipulation for web development. Excludes tool-specific proficiency (see 'Tools, Frameworks & Implementation Proficiency').
Maintainability and Legacy Code
Covers strategies and principles for evolving codebases safely and keeping them easy to understand and change over time. Topics include design principles such as Single Responsibility, Open Closed, Liskov Substitution, Interface Segregation, and Dependency Inversion, removing duplication, establishing appropriate abstraction boundaries, separation of concerns, identifying and remediating code smells, incremental refactoring approaches, regression risk mitigation via tests and feature toggles, backward compatibility and migration strategies, and prioritizing technical debt reduction. Interviewers assess the candidate ability to plan pragmatic refactors, minimize risk during change, and improve long term health of a codebase.
Clean Code and Best Practices
Covers the principles and hands on practices that produce readable, maintainable, and reliable code. Core elements include intent revealing and consistent naming, small focused functions and classes that follow single responsibility, avoiding duplication through refactoring and appropriate abstractions, clear structure and separation of concerns, following language specific idioms and style guides, consistent formatting, concise comments that explain nonobvious intent, defensive programming and robust error handling, edge case handling and input validation, use of linters and static analysis, incremental refactoring techniques, and pragmatic trade offs between ideal design and delivery constraints. Interviewers will also probe involvement in code reviews, version control hygiene, code metrics, and how candidates advocate for and teach coding standards to peers.
Api and Data Structure Design
Focuses on designing efficient data models and public interfaces that back real world backend features, and selecting or inventing data structures to meet functional and non functional requirements. Candidates should be able to design data structures and classes to support use cases such as rate limiters, leaderboards, session managers, cache layers, analytics counters, and queueing or aggregation services. Topics include mapping operations to data structure choices for latency and throughput goals, persistence and eviction strategies for cached state, concurrency control and atomic operations, synchronization or lock free designs, partitioning and sharding implications, and tradeoffs between in memory, persisted, and distributed storage. Also cover API design considerations such as endpoint and payload design, versioning, pagination, idempotency, error handling, security and authentication, monitoring and observability, and how API shape influences internal data models and query patterns. Interviewers may ask candidates to produce class or interface sketches, data schemas, and rationale for chosen approaches and complexity characteristics.