Rippling Software Engineer Onsite Coding Questions
10+ questions from real Rippling Software Engineer Onsite Coding rounds, reported by candidates who interviewed there.
What does the Rippling Onsite Coding round test?
The Rippling onsite coding round is the core technical evaluation. Software Engineer candidates typically see 2-3 algorithm and data structure problems. Problems range from medium to hard difficulty, and interviewers evaluate both correctness and code quality.
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Rippling Software Engineer Onsite Coding Questions
Rippling Onsite Fullstack Interview (Frontend Focus) Experience
The interview centered on frontend development, specifically requiring the implementation of interactive buttons and the logic necessary to display and render various images.
LeetCode #23: Merge k Sorted Lists. Difficulty: Hard. Topics: Linked List, Divide and Conquer, Heap (Priority Queue), Merge Sort. Asked at Rippling in the last 6 months.
LeetCode #737: Sentence Similarity II. Difficulty: Medium. Topics: Array, Hash Table, String, Depth-First Search, Breadth-First Search, Union-Find. Asked at Rippling in the last 6 months.
#21 Merge Two Sorted Lists
LeetCode #21: Merge Two Sorted Lists. Difficulty: Easy. Topics: Linked List, Recursion. Asked at Rippling in the last 6 months.
#3 Longest Substring Without Repeating Characters
LeetCode #3: Longest Substring Without Repeating Characters. Difficulty: Medium. Topics: Hash Table, String, Sliding Window. Asked at Rippling in the last 6 months.
## Problem Derive the character ordering of an alien language from a sorted list of words using topological sort. ## Likely LeetCode equivalent LC 269 (Alien Dictionary) is the direct match. ## Tags graph, topological-sort, hash_table
## Problem Implement a canvas drawing system supporting shapes, fills, or flood-fill operations on a 2D grid. ## Likely LeetCode equivalent Related to LC 733 (Flood Fill). ## Tags matrix, DFS, simulation
## Problem Compute the block sum of a matrix where each cell holds the sum of neighboring cells within distance K. ## Likely LeetCode equivalent LC 1314 (Matrix Block Sum) is the direct match. ## Tags matrix, prefix-sum, arrays
Rippling SWE Onsite - Unique Occurrences
## Problem Verify that the number of occurrences of each value in an array is unique. ## Likely LeetCode equivalent LC 1207 (Unique Number of Occurrences) is the direct match. ## Tags hash_table, arrays
## Problem You are asked to design a REST API layer for a task management service. Implement the following endpoints (you may use any framework or pseudocode): ``` POST /tasks Create a task {title, description, due_date, assignee_id} GET /tasks/:id Get task by ID PATCH /tasks/:id Update fields (partial update) DELETE /tasks/:id Soft-delete a task GET /tasks?status=&assignee= List with optional filters + pagination ``` **Expected Request/Response:** ``` POST /tasks Body: {"title": "Fix bug", "due_date": "2025-04-30", "assignee_id": "u42"} Response 201: {"id": "t123", "title": "Fix bug", "status": "open", ...} GET /tasks?status=open&page=2&limit=20 Response 200: {"items": [...], "total": 87, "page": 2, "limit": 20} ``` ## Follow-ups 1. How do you validate request bodies and return structured 422 errors? 2. Where and how would you add authentication/authorization (e.g., only assignee can update)? 3. How do you version the API when you need to introduce breaking changes? 4. Describe how you would rate-limit the list endpoint per client.
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