Anagram Detector

Level: Beginner 15–30 min

Concepts: AlgorithmsStringsValidation

Solutions: C# | TypeScript | Python

Build an anagram detection system that can check pairs, filter lists, and group words by their anagram sets.

Requirements

Step 1: Pair Detection

Given two words, determine if they are anagrams of each other.

  • An anagram uses exactly the same letters, the same number of times
  • Comparison should be case-insensitive
  • Spaces and punctuation are ignored
  • A word is not an anagram of itself

Examples:

  • "listen" and "silent" → true
  • "hello" and "world" → false
  • "Astronomer" and "Moon starer" → true
  • "rail safety" and "fairy tales" → true
  • "cat" and "cat" → false (same word)

Step 2: Find Anagrams in a List

Given a subject word and a list of candidates, return the candidates that are anagrams of the subject.

subject: "listen"
candidates: ["enlists", "google", "inlets", "banana", "silent"]
result: ["inlets", "silent"]

Step 3: Group Anagrams

Given a list of words, group them by their anagram sets.

input: ["eat", "tea", "tan", "ate", "nat", "bat"]
output: [["eat", "tea", "ate"], ["tan", "nat"], ["bat"]]

Test Cases

Pair detection:

Word AWord BAnagram?
"listen""silent"true
"hello""world"false
"cat""tac"true
"cat""cat"false
"Cat""tac"true
""""false
"a""a"false
"ab""ba"true
"aab""abb"false

Find anagrams:

SubjectCandidatesResult
"listen"["silent", "tinsel"]["silent", "tinsel"]
"listen"["hello", "world"][]
"master"["stream", "maters", "pigeon"]["stream", "maters"]

Group anagrams:

InputGroups
["eat", "tea", "ate"][["eat", "tea", "ate"]]
["abc", "def"][["abc"], ["def"]]
[][]

Bonus

  • Find the longest anagram pair in a dictionary file
  • Detect partial anagrams — words where one is an anagram of a substring of the other
  • Generate all possible anagrams of a given word (permutations that are real words, given a dictionary)

Hint

The key insight: two words are anagrams if they have the same sorted characters. Sorting the letters of "listen" and "silent" both give "eilnst". This sorted form is the anagram “key” — use it for grouping and comparison.

Reference Walkthrough

Reference implementations in C#, TypeScript, and Python live at tddbuddy-reference-katas/anagram-detector. This is an F1 kata — 18 scenarios across three pure functions (pair detection, find-in-list, group), shared across all three languages, built around a single sorted-letters “anagram key” helper.

This kata ships in Agent Full-Bake mode at high gear: the algorithm is small enough to land as one commit per language, with a brief walkthrough noting there are no builders because the algorithm’s inputs and outputs are the domain. Strings and lists of strings go in, booleans and lists of strings come out — no aggregates to construct, no value types to introduce, no collaborators to inject. See the repo’s Gears section for when high gear is the right call.

Related reading

  • Examples Pin Intent. Properties Pin the Invariants.
    Example-based tests anchor scenarios in the team's vocabulary. Property-based tests anchor invariants across the input space. The agent needs both axes, and most suites only carry one.
  • Katas Are Rehearsal, Not Performance
    You don't practice TDD on production code. You practice on katas and bring the muscle memory to production. The gap between knowing TDD and doing TDD is reps.
  • The Test Pyramid Was an Economic Argument
    The test pyramid was not a quality law. It was a cost structure: unit tests were cheap, integration tests were expensive, so you wrote many of the first and few of the second. Agents collapsed the cost of writing tests at every level, and the cheapest test that still tells the truth is the one that pins a seam the agent cannot fake.