This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Implement paginated, sortable dynamic table component states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
##### Question
Design and implement a React table component with pagination and sorting. Requirements: clear component decomposition, reasonable state design, support dynamic columns. Follow-up: discuss extensibility and how to support a mobile-responsive layout.
Quick Answer: This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Implement paginated, sortable dynamic table component states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
You are building a reusable React table component for a web application. The component must handle typical data-grid needs while remaining simple, performant, and extensible.
Requirements
Design a clear component decomposition (how you split the UI and logic into components/hooks).
Propose a reasonable state model (what state lives where: local vs. controlled via props).
Support dynamic columns (columns are provided via configuration, not hard-coded).
Implement client-side sorting and pagination.
Provide a minimal usage example showing how a consumer passes data and column definitions.
Follow-up
Discuss extensibility: filtering, server-side mode, row selection, virtualization, theming, etc.
Explain how to make the table mobile-responsive.
Constraints
Use React (hooks are preferred). You may use TypeScript or JavaScript.
Avoid external table libraries; small utility packages are fine but not required.
Accessibility should be considered (keyboard and screen-reader friendly).
Constraints & Assumptions
Preserve the scope, facts, inputs, and requested outputs from the prompt above.
If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.
Clarifying Questions to Ask Guidance
Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.
State explicit assumptions before making sizing or architecture decisions.
Prioritize the functional path first, then address reliability, security, observability, and rollout.
What a Strong Answer Covers Guidance
A scoped requirements summary with concrete non-goals and success metrics.
API, data model, architecture, consistency, capacity, and operations.
Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.
A validation, monitoring, migration, and launch plan appropriate for the risk level.
Follow-up Questions Guidance
What breaks first at 10x traffic or data volume?
How would you degrade gracefully during dependency failures?
What metrics and alerts would prove the design is healthy after launch?