DSA Tracker

Medium

Letter Combinations of a Phone Number

A medium Backtracking problem included in Apna College, Love Babbar 450, Striver A2Z. Below: the roles whose interviews prioritise this topic, and how to practise it.

Topic
Backtracking
Sheets
3
Core for
0 roles
Platform
LeetCode
Practice in the compilerWatch this solved step by step

The problem

Given a string containing digits from 2 to 9 inclusive, return all possible letter combinations that the number could represent, following the standard phone keypad mapping where each digit maps to a set of letters. Return the answer in any order.

Example 1

Input
digits = "23"
Output
["ad","ae","af","bd","be","bf","cd","ce","cf"]
Why
Digit 2 maps to "abc" and digit 3 maps to "def". The Cartesian product gives all 9 combinations.

Example 2

Input
digits = ""
Output
[]
Why
An empty string produces no combinations.

Example 3

Input
digits = "2"
Output
["a","b","c"]
Why
Digit 2 maps to three letters: a, b, and c.

Constraints

  • 0 <= digits.length <= 4
  • digits[i] is a digit in the range ['2', '9']

How to think about it

Updated 2026-09-09

Each digit index represents an independent slot that must be assigned one character from that digit's letter set. This is a pure Cartesian product: no pruning or constraint checking is necessary because every combination formed by selecting one letter per digit is valid.

Approaches, worst first

  1. Iterative queue expansion

    time O(4^n * n) · space O(4^n * n)

    Start with a queue containing an empty string. For each digit, pop every string currently in the queue, concatenate each corresponding letter, and push the new strings back. Generates combinations level-by-level without recursion.

  2. Backtracking character bufferWrite this one

    time O(4^n * n) · space O(n)

    Maintain a character array or string builder. Recurse with digit index i. Loop over the letters mapped to digits[i], assign to buffer[i], and recurse to i + 1. Join buffer into a string when i == digits.length. Operates with minimal memory allocation.

Where people lose marks · 3
  • Returning [""] instead of [] when input digits is empty. An empty string has length 0, which if unhandled triggers the base case and incorrectly appends an empty string to the output.
  • Incorrect letter mappings for digits 7 and 9, which contain 4 letters ('pqrs' and 'wxyz') instead of 3.
  • String concatenation overhead inside deep recursive calls when an array buffer could be reused.

The theory behind it

Backtracking — the ground this problem stands on. All Backtracking problems

What Backtracking is

Backtracking is an organized trial-and-error search through a maze of possibilities. You make a tentative choice, move forward to explore where that path leads, and if you hit a dead end or finish finding an answer, you back up and undo that choice. By cleaning up your changes before trying the next option, a single shared board or list is explored thoroughly without needing to clone full copies of your data at every turn.

When to reach for it

Reach for backtracking when a problem asks to generate all possible solutions, like all subsets, permutations, valid parentheses combinations, or word search paths on a board. Signals include puzzles with strict constraint rules, like placing eight non-attacking queens on a chessboard or solving a Sudoku grid. Whenever you must construct combinations step by step and abandon dead-end branches early before wasting time exploring impossible paths, use backtracking.

How the pattern works

Follow a three-step rhythm inside a loop: choose, explore, and unchoose. First, check if the current state satisfies your goal; if so, save a copy of it and return. Next, prune illegal moves immediately using constraint checks so unpromising branches are skipped. For each valid candidate, apply the move to your shared path or board, call the recursive function to explore deeper, and finally undo the move right after the call returns. Undoing restores the shared state so sibling choices start from a clean slate.

What each operation costs

OperationTime
generate all subsets of n elementsO(2^n)
generate all permutations of n elementsO(n!)
auxiliary recursion stack memory depthO(n)
What usually goes wrong with Backtracking
  • Adding a mutable path list directly to the final answers collection without creating a shallow copy, leaving every saved result empty once backtracking finishes.
  • Forgetting to undo a state change after the recursive call returns, contaminating subsequent branches with leftover moves from earlier paths.
  • Generating duplicate subsets or permutations by failing to sort the input array and skip adjacent identical elements during branch selection.

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