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47. Group Anagrams

mediumAsked at Workday

Group strings into anagram clusters. Workday uses this for canonical-key bucketing — same shape as grouping department-code aliases that all refer to the same cost center.

By Alex Chen, Founder, InterviewChamp.AI · Last verified

Source citations

Public interview reports confirming this problem appears in Workday loops.

  • Glassdoor (2026-Q1)— Workday SDE2 phone screen — classic hash-map question.

Problem

Given an array of strings strs, group the anagrams together. You can return the answer in any order.

Constraints

  • 1 <= strs.length <= 10^4
  • 0 <= strs[i].length <= 100
  • strs[i] consists of lowercase English letters.

Examples

Example 1

Input
strs = ["eat","tea","tan","ate","nat","bat"]
Output
[["bat"],["nat","tan"],["ate","eat","tea"]]

Example 2

Input
strs = [""]
Output
[[""]]

Example 3

Input
strs = ["a"]
Output
[["a"]]

Approaches

1. Pairwise anagram check

Check each pair, build groups via union-find or graph traversal.

Time
O(n^2 * k)
Space
O(n)
// quadratic — too slow at n=10^4

Tradeoff: Quadratic. Won't pass.

2. Sort each string, hash-map group

Sorted version of each string is the canonical key. Map key -> list.

Time
O(n * k log k)
Space
O(n * k)
function groupAnagrams(strs) {
  const groups = new Map();
  for (const s of strs) {
    const key = [...s].sort().join('');
    if (!groups.has(key)) groups.set(key, []);
    groups.get(key).push(s);
  }
  return [...groups.values()];
}

Tradeoff: Sort-as-canonical-key is simple. Faster: 26-char count tuple as key, O(n*k) total.

Workday-specific tips

Workday accepts either sort-key or count-tuple-key. Mention both; explain that count-tuple is faster but sort-key is shorter to write. Either is fine for the constraint sizes.

Common mistakes

  • Using a Set instead of Map<string, list> — collapses anagrams into one entry.
  • Sorting in place when input is shared — mutates caller's data.
  • Forgetting empty-string edge case.

Follow-up questions

An interviewer at Workday may pivot to one of these next:

  • Valid Anagram (LC 242) — same vs different.
  • What if strings can be very long? (Use count tuple.)
  • Group Shifted Strings (LC 249) — anagram by shift.

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Output

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FAQ

Sort-key vs count-tuple?

Sort-key is O(k log k) per string. Count-tuple is O(k). For k <= 100, both are fine. Count-tuple wins at scale.

Empty string?

Sort-key of '' is ''. All empty strings hash to one bucket. Correct behavior.

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