Machine Coding Interview Questions for Freshers (2026 Guide)

If you are a fresher preparing for a frontend or full-stack machine coding round, the good news is that the questions at your level are narrower than they look. For frontend-focused fresher roles, machine coding rounds commonly involve building a small, self-contained UI component or application, such as a todo list, a set of tabs, or a star rating widget, in roughly 45 to 90 minutes, using plain HTML, CSS, and JavaScript or a lightweight React scaffold. This is different from the OOP/LLD-style machine coding rounds used in some general software engineering interviews, where questions may involve systems such as parking lots, expense splitting, or rate limiters.

That is a different test from OOP or low-level-design-style machine coding rounds, where the focus shifts toward object modeling, extensibility, changing requirements, and sometimes design patterns. The exact format depends more on the role and company than on experience level alone. For frontend-focused fresher roles, over-preparing only for OOP/LLD problems can still be a poor use of time if the actual round is centered on building UI. This guide covers what is commonly asked at the fresher level, what interviewers are checking for, and a practical way to work through the problem in the time you have.

Fresher UI machine coding vs OOP/LLD-style machine coding

The confusion between levels is common enough that it is worth putting side by side before anything else.

 If you are unsure which round you are walking into, ask your recruiter directly what the round covers. It is a normal question to ask, and the answer changes how you should spend your prep time this week.

What a fresher machine coding round actually tests 

At this level, interviewers are less interested in a perfect abstraction and more interested in seeing a working core path. The signal they are looking for is whether you can turn a small, ambiguous prompt into a working interface: clean component breakdown, local state, event handling, and code that is readable enough to extend later. A candidate who spends the full session on the happy path and never gets it running is a weaker signal than one who ships something simpler but complete.

This matters more than it sounds. A fresher who spends 40 minutes designing a beautiful component hierarchy on paper and only has 10 minutes left to type code will usually score worse than one who has something clickable on screen after 20 minutes, even if that first version is rough. Interviewers at this level are calibrating for "can this person ship," not "can this person architect." 

The core UI questions asked most often

These are the problems that repeatedly show up as entry-level starting points, based on the Front End Interview Handbook's practice sets, frontend interview roundups, and common fresher-round reports.

• Todo list app. Add, edit, delete, and toggle complete or incomplete, with optional filters for all, active, or completed items. Tests CRUD logic, local state, list rendering, and basic forms. This is one of the most common foundational UI coding problems and one of the best problems to practice first because many other questions reduce to the same underlying shape: an array of items and operations that add, remove, update, or filter them.
• Tabs. Multiple content panels with a single controlled active tab. Tests conditional rendering and simple state. The trap here is state that gets out of sync with what is actually rendered, keep a single source of truth for which tab is active rather than tracking each panel's visibility separately.
• Accordion or collapsible sections. Expand and collapse panels, single or multi-open. Tests per-item state and, optionally, basic accessibility. Clarify early whether multiple panels can be open at once, it changes whether you need one active index or a set of open indices.
• Star rating. Interactive stars with hover and click to set a rating, sometimes with a half-star or read-only variant. Tests event handling and visual state, specifically the difference between a hover-preview value and the committed value.
• Modal or dialog. Open and close behavior, an overlay, Escape-key handling, and basic focus management. Tests interaction state and accessibility fundamentals. Clicking the backdrop to close may also be requested, but treat that as a product requirement rather than a universal dialog behavior.
• Progress bar. Animated or stepped progress with a controllable value. Tests CSS combined with state updates.
• Image carousel or slider. Next and previous controls, indicator dots, and boundary handling (what happens at the first or last slide, does it wrap around or stop).
• Counter. Increment, decrement, and reset with min and max bounds. A minimal state exercise, sometimes used as a warm-up question before a larger prompt.
• Calculator. Basic arithmetic with edge cases like divide-by-zero and chained operations. Tests input handling and display logic, and is a good test of whether you handle the edge cases an interviewer will actually try (typing an operator twice in a row, pressing equals with no second number entered).

A step up in scope, but still appropriate for entry level: a digital clock or stopwatch, a simple form with real-time validation, basic or truncated pagination, and tic-tac-toe (game logic plus win detection).

A minimal state shape, using the todo list as the example 

Because the todo list is the most common starting point, it is worth seeing what a clean, minimal version of its state actually looks like. This is not the only correct shape, but it demonstrates the pattern interviewers want to see: one array holding the data, and handler functions that update it immutably.

For a basic add, delete, toggle, and filter implementation, the shared state only needs two pieces: a todos array (each item an object with an id, text, and completed flag), and a filter value tracking which of all, active, or completed is currently selected. If inline editing is required, you will usually also need a transient edit state, such as an editingId and draft text, or keep that state locally inside the todo item being edited. Adding an item appends a new object to the array. Toggling an item maps over the array and flips the completed flag on the one whose id matches, leaving every other item untouched. Neither handler mutates the existing array directly; both build a new one, preserving React's state snapshots and ensuring updates are represented by new state values rather than mutations.

Notice what is absent from this shape: no global store, no separate "isEditing" boolean scattered across components, no derived data being stored in state (the filtered list itself is computed at render time from todos and filter, not kept in its own state variable). That last point is worth remembering across every problem in this list. If a value can be calculated from an existing state, calculate it during render instead of storing it separately, storing it invites the two copies to drift out of sync.

What you are actually expected to demonstrate 

Interviewers at this level are checking for a specific, fairly consistent set of things:

• A clean component breakdown, or clearly organized modules if you are writing plain JavaScript.
• Local state management (useState or equivalent), without reaching for a global store you do not need.
• Event handlers, sensible form and input state management, and correct list keys.
• Basic CSS: layout that works and gives visual feedback.
• The obvious edge cases: an empty list, the first or last item, invalid input, a user clicking rapidly.
• Naming and structure clear enough that another engineer could extend the code.
• The ability to talk through your approach before you start typing, and to demo the working core feature at the end. 

Jumping straight into code without spending 5 to 10 minutes on a plan is a common red flag interviewers report, even for junior candidates. It is worth saying explicitly why this matters at fresher level specifically: an interviewer cannot tell from silence whether you understood the requirement or you are guessing, narrating your plan for 30 seconds before typing removes that ambiguity for free.

What is out of scope at this level 

This is worth being explicit about, because the fresher and experienced versions of "machine coding" get confused constantly, including by candidates who over-prepare for the wrong round. 

Not expected of a fresher: multi-floor parking-lot systems, elevator dispatch, full expense-splitting graphs (the kind of problem behind a Splitwise clone), concurrent rate limiters, or anything built around Strategy, State, or Factory design patterns as the primary focus. Also out of scope: heavy concurrency handling, production-grade persistence, data tables with server-side sort and filter plus virtualization, infinite scroll with race-condition handling, autocomplete with debounce and cancelable requests, or nested comment trees with real-time updates.

Those belong to intermediate and product-company SDE-1-plus rounds. If you want to see what that tier of question actually looks like, GreatFrontEnd's frontend LLD guide covers it directly, it is a useful preview of where your prep goes next, not something to study now.

A practical, time-boxed approach

For the problems above, a simple five-step approach covers almost all of them:

1. Clarify, 3 to 5 minutes. Restate the must-haves versus the nice-to-haves. Ask about input format, whether invalid input needs handling, and what interactions the interviewer plans to test. For a todo list, that might mean asking whether items persist after a refresh, or whether that is out of scope for this round.
2. Quick plan, 5 to 10 minutes. List the components and state pieces before writing code. For a todo app, that means deciding the shape of your data (a todos array, a filter value, handler functions) before touching the editor.
3. Core implementation. Get the happy path working and demoable first: add an item, list it, toggle it. Prefer simple, correct code over a clever abstraction you might not finish.
4. Edges and polish. Handle empty states, bounds, and basic validation. Add just enough CSS that the result looks intentional.
5. Demo and discuss. Walk through what you built, and mention one or two ways it could be extended, local storage persistence or filters, for example, if time allows.

Practicing a smaller set of problems deeply, a todo list, tabs, an accordion, a modal, a carousel, and one form, tends to cover more real interview ground than skimming a long list superficially. Most of the problems in this guide share the same underlying pattern once you strip away the surface differences: an array or object in state, a handful of pure functions that update it, and a render function that reflects it. Once that pattern feels automatic for one problem, the next one takes noticeably less time.

Common mistakes interviewers flag

• Starting to type before clarifying the requirements or sketching a plan.
• Loose prop bags or state shapes that allow logically impossible combinations, such as mutually exclusive isLoading, isSuccess, and isError flags accidentally being true at the same time.
• Spending disproportionate time on visual polish before the core interaction works.
• Not handling the obvious edge cases the prompt implies, even without being asked directly.
• Storing a value in state that could instead be computed from existing state at render time, this is one of the most common sources of subtle bugs even in small components. 

Where the data is thinner

Public, attributed transcripts specifically labeled "fresher machine coding round" are less common than for mid-level product-company rounds. Most of what is documented is practice-oriented, aggregated lists rather than single verified interview reports. Company-specific fresher accounts more often mention todo-style or basic component builds than full low-level-design systems; backend-heavy machine coding problems (a parking lot or vending machine system, for instance) are more frequently reported for SDE-1 roles at product companies, and those candidates usually already have some prior experience or strong object-oriented practice. Pure campus freshers more commonly report algorithmic and basic UI or JavaScript coding rounds instead. Where a claim above rests on a practice list rather than a single confirmed transcript, that is the case throughout this section, not a one-off exception.

Frequently asked questions

Do I need to know React for a fresher machine coding round? Frontend UI coding rounds may use vanilla JavaScript or the framework relevant to the role. If you are targeting React positions, practicing these questions in React is a sensible default because the underlying skills, state management, events, component structure, and DOM behavior, transfer across most of these problems.

How long should I spend practicing before I feel ready? There is no single verified number for this, but the pattern in the research above is consistent: a small set of problems practiced deeply (todo list, tabs, accordion, modal, one form) covers more of what actually gets asked than a long list attempted once each.

What if I finish early? Use remaining time on the edge cases and polish steps in the practical approach above, empty states, invalid input, and a short walkthrough of what you would add next. Finishing the happy path with time to spare and stopping there is a missed opportunity to show more of what you know.

Is it a problem if my solution does not look polished? Not on its own. The research above repeatedly points to working core behavior as the primary signal at this level, with visual polish and edge cases as secondary. A working, slightly plain todo list beats a beautifully styled one that cannot add an item.

Practice these questions on GreatFrontEnd

The fastest way to get comfortable with this round is to build the exact components above under a timer. GreatFrontEnd's UI coding practice questions cover todo lists, tabs, accordions, modals, and the rest of this list, each with a reference solution and tests written by ex-FAANG engineers, so you can check your approach against a working answer instead of guessing whether you got it right. That is the difference between reading a list of machine coding interview questions for freshers and actually being ready to walk into one.