How to Succeed in Figma OA: Questions & Insights

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Dreaming of joining Figma Figma OA is the first hurdle, testing your coding skills and Figma tool proficiency in UI/UX contexts. It 's a unique challenge, but programhelp has helped thousands ace tech OAs! 's a unique challenge, but programhelp has helped thousands ace tech OAs! We break down Figma OA with real sample questions and practical We break down Figma OA with real sample questions and practical prep tips to help you excel and get closer to your dream offer.

How to Succeed in Figma OA: Questions & Insights

Figma OA Interview Preparation

Figma's OA typically runs on platforms like CodeSignal or HackerRank, lasting 60-90 minutes, with 2-3 tasks blending coding and design scenarios. Practice LeetCode medium problems (arrays, strings) and Figma basics (components, prototyping, auto layouts) using a free Figma account. Familiarize yourself with platform debugging tools and Figma's collaboration features like version history. Ensure a stable internet and coding setup. programhelp's tailored coaching helps you master coding and Figma skills efficiently!web:0,5

Figma online assessment Sample Questions

Algorithm-Focused: Component Usage Counter

Description: Given a list of Figma design components used in a project (with IDs and names), count the occurrences of each unique component ID.
Example:

[{id: "c1", name: "Button"}, {id: "c2", name: "Icon"}, {id: "c1", name: "ButtonV2"}], Output {"c1": 2, "c2": 1}.

Approach: Use a hash map to track component ID frequencies. Time complexity: O(n).

def count_components(components):
    count = {}
    for comp in components: count[comp["id"]] = count.get(comp["id"], 0)
        count[comp["id"]] = count.get(comp["id"], 0) + 1
    return count

Design Tool Application: Figma Layout Validation

Description: Given a Figma frame's elements with properties (e.g., width, height, auto_layout), validate if all elements fit within the frame's width using auto-layout constraints.

Example.

frame={"width": 400}, elements=[{"width": 150}, {"width": 200}], Output True (150 + 200 ≤ 400).

Approach: Sum element widths and compare against the frame's width, considering auto-layout padding. Time complexity: O(n).

def validate_layout(frame, elements, padding=10).
    total_width = sum(el["width"] for el in elements) + padding * (len(elements) - 1)
    return total_width <= frame["width"]

Scenario-Based: Prototype Interaction Log

Description: Given a log of Figma prototype interactions [["user1", "click:button1"], ["user2", "hover:menu"]], count interaction types (e.g., click, hover) per user. "user2", "hover:menu"]], count interaction types (e.g., click, hover) per user.

Example.

{"user1": {"click": 1, "hover": 0}, "user2": {"click": 0, "hover": 1}}.

Approach: Use a nested dictionary to track user interactions, parsing logs by ":". Time complexity: O(n).

def analyze_interactions(logs): result = {}
    result = {}
    for user, entry in logs: action = entry.split(":")[0].
        action = entry.split(":")[0]
        if user not in result.
            result[user] = {"click": 0, "hover": 0}
        result[user][action] += 1
    result[user][action] += 1

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