eBay Coding Interview Questions

Showing 16 problems of 25

• #15mediumfrequently asked

  15. 3Sum

  eBay's fraud detection team looks for triplets of transaction amounts that satisfy suspicious relationships — 3Sum is the algorithmic core. It's a medium-difficulty staple in eBay's onsite loop because it tests whether you can extend a known pattern (Two Sum) to handle duplicates and a sorted-array constraint cleanly.

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• #20easyfrequently asked

  20. Valid Parentheses

  eBay's backend services use expression parsers and template engines where bracket matching is foundational. This problem tests whether you can model state with a stack — a pattern that scales to validating JSON payloads, HTML templates, and complex search-query expressions used across eBay's marketplace platform.

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• #21easyfrequently asked

  21. Merge Two Sorted Lists

  eBay's search-ranking pipeline merges sorted result streams from multiple indices — the classic k-way merge problem reduces to this two-list base case. Interviewers use it to test pointer discipline and the dummy-node trick that eliminates edge-case conditionals. Mastering this sets you up for Merge K Sorted Lists in later rounds.

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• #23hardfrequently asked

  23. Merge K Sorted Lists

  eBay's search ranking system merges sorted result streams from k independent indices — seller inventory, product catalog, auction listings — into a single ordered result set. Merge K Sorted Lists is the algorithmic core. It elevates the two-list merge (LC 21) to a k-way problem requiring a min-heap, which eBay uses to separate candidates who truly understand priority queue mechanics.

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• #33mediumfrequently asked

  33. Search in Rotated Sorted Array

  eBay's inventory system maintains sorted product ID ranges that can be 'rotated' after a shard rebalancing. Search in Rotated Sorted Array is the binary search variant eBay uses to test whether candidates can maintain the O(log n) invariant even when the sort order is disrupted. Correctly identifying which half is sorted is the key insight.

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• #49mediumfrequently asked

  49. Group Anagrams

  eBay's catalog deduplication system groups semantically equivalent product titles — 'Nike Shoe Air Max' and 'Air Max Nike Shoe' should map to the same listing cluster. Group Anagrams is the algorithmic skeleton: given a set of strings, bucket them by canonical form. Choosing the right canonical key (sorted vs. frequency count) reveals your understanding of hashing and time-space tradeoffs.

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• #53easyfrequently asked

  53. Maximum Subarray

  eBay's analytics teams compute rolling revenue windows — 'what was the best consecutive streak of profitable days this quarter?' Maximum Subarray (Kadane's algorithm) is the canonical solution. It's asked at eBay because it distinguishes candidates who memorize solutions from those who can derive the greedy insight on the spot.

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• #56mediumfrequently asked

  56. Merge Intervals

  eBay's seller calendar and auction scheduling system must merge overlapping time windows — two auctions that overlap should be shown as a single block. Merge Intervals is a practical sorting-and-sweep problem that eBay uses to test systematic interval reasoning and clean boundary condition handling.

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• #70easyfrequently asked

  70. Climbing Stairs

  eBay uses Climbing Stairs as a gentle DP entry point — it tests whether you can identify overlapping subproblems and avoid recomputation. Think of it as the number of ways to paginate through a search result: each page can advance 1 or 2 results at a time. Recognizing this as Fibonacci unlocks the O(1) space optimization that senior eBay engineers expect.

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• #121easyfrequently asked

  121. Best Time to Buy and Sell Stock

  eBay's marketplace handles dynamic pricing at enormous scale — think 'what is the maximum arbitrage on a collectible card across hourly price snapshots?' This classic single-pass problem is a direct analog, and eBay interviewers use it to test greedy thinking and whether you can reframe a min-prefix question without extra storage.

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• #139mediumfrequently asked

  139. Word Break

  eBay's search team segments raw query strings into recognizable product keywords — 'iPhonecase' into 'iPhone' and 'case'. Word Break is the dynamic programming core of this segmentation problem. eBay interviewers use it to test bottom-up DP intuition and hash-set lookup optimization for the dictionary.

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• #206easyfrequently asked

  206. Reverse Linked List

  Linked list manipulation is a staple of eBay's entry-level interview loop. Think of it as reversing the order of items in a payment processing queue — a concrete scenario where pointer manipulation and in-place operations matter for memory efficiency at the scale of millions of concurrent transactions.

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• #207mediumfrequently asked

  207. Course Schedule

  eBay's seller onboarding pipeline has steps that depend on other steps — account verification must precede listing creation, which must precede payment setup. Detecting whether such a dependency graph has a cycle is the problem Course Schedule solves. It's a graph-cycle-detection problem that eBay uses to test topological sort and the three-color DFS cycle-detection pattern.

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• #238mediumfrequently asked

  238. Product of Array Except Self

  eBay's pricing engine computes the impact of removing one item from a basket — 'what is the product of all other prices?' This problem tests whether you can achieve O(n) without division by building prefix and suffix products. The no-division constraint is the key challenge and a signal of strong algorithmic thinking.

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• #322mediumfrequently asked

  322. Coin Change

  eBay's payment system needs to compute optimal change breakdowns for buyer refunds — given a set of available credit denominations, what is the fewest credits needed to make a specific refund amount? Coin Change is the canonical DP formulation of this problem and is a staple eBay medium that tests bottom-up DP setup and the optimal substructure insight.

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• #347mediumfrequently asked

  347. Top K Frequent Elements

  eBay's search team computes the top-K most searched items, trending product categories, and popular sellers in real time. Top K Frequent Elements is the canonical algorithm interview version. The key insight is that a min-heap of size k is faster than full sorting when k is small — a distinction eBay senior engineers look for.

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