AutocompleteMedium
Autocomplete / Typeahead
Build a search input that fetches suggestions as the user types, with debouncing, keyboard navigation, and loading/error states.
DebounceAsync fetchKeyboard UXAccessibility
Flipkart·Swiggy·Razorpay
Machine Coding Round
Build UI components under real interview conditions. AI evaluates your code on correctness, state management, edge cases, and component design — the same rubric used by senior engineers at Flipkart, Swiggy, and Razorpay.
No credit card required
Practice for machine coding rounds at
These component-building problems appear repeatedly across Indian tech company interviews. Each is graded on functionality, code quality, edge cases, and UX.
Build a search input that fetches suggestions as the user types, with debouncing, keyboard navigation, and loading/error states.
Implement a feed or product list that loads more items as the user scrolls to the bottom, with a loading indicator and error handling.
Build a multi-column task board where users can drag cards between columns. Manage state for card order and column membership.
Create a searchable multi-select dropdown with chip display, select-all, deselect, and keyboard accessibility.
Build a reusable star rating component with hover effects, click-to-rate, read-only mode, and half-star support.
Implement a file upload component with drag-and-drop support, upload progress bar, file type validation, and cancellation.
A clear mental framework turns a 90-minute pressure session into a familiar, repeatable flow.
Understand inputs, outputs, and edge cases before writing a single line. Clarify ambiguities with the interviewer.
Define props, state shape, and component hierarchy. A clear design prevents rewrites mid-session.
Get a basic version running in 20 minutes. A partially working solution beats a perfect-but-incomplete one.
Add loading states, error handling, empty states, and keyboard accessibility. These differentiate good from great.
Write and run code in a real browser environment with Sandpack. See your component render as you build — just like in a real interview.
Your solution is graded on correctness, state management, component design, edge case handling, and code quality — not just "does it work".
Problems are mapped to interview patterns at specific companies. Practice Flipkart-style e-commerce UIs, Swiggy-style real-time components, and more.
Community
Share your solutions, get feedback, and see how others approached the same problems. Dedicated channels for machine coding, component design, and company-specific prep.
No plan required
A machine coding round is a timed session (60–90 minutes) where you build a functional UI component or small application from scratch — for example, an autocomplete search, infinite scroll list, Kanban board, or star rating widget. The interviewer evaluates your code quality, component design, edge case handling, and how you approach the problem. It is common at Indian tech companies like Flipkart, Swiggy, Razorpay, Meesho, and CRED.
Common machine coding problems include: autocomplete/typeahead, infinite scroll, drag-and-drop list, file upload with progress, multi-select dropdown, modal/dialog, accordion/tabs, image carousel, star rating, kanban board, nested comments, pagination component, and real-time search filter. Companies like Flipkart focus on building scalable, reusable components with clean state management.
To prepare for machine coding rounds: (1) Practice building UI components from scratch without referencing docs; (2) Focus on clean state management, prop design, and edge cases; (3) Time yourself — aim to have a working solution in 45–60 minutes; (4) Practice with live preview so you can see your component rendering; (5) Study company-specific problem types — Flipkart focuses on e-commerce UIs, Swiggy on real-time updates, Razorpay on form flows.
Machine coding rounds are extremely common in Indian tech company interviews. Companies that conduct machine coding rounds include Flipkart, Swiggy, Razorpay, CRED, Meesho, Zepto, Groww, PhonePe, Juspay, Nykaa, and many more. Some FAANG companies also conduct machine coding-style rounds as part of their frontend interview process.
Build real UI components in a live IDE, get AI feedback on your code, and see exactly what you need to improve before your next interview.