LeetCode #2135 — MEDIUM

Count Words Obtained After Adding a Letter

Move from brute-force thinking to an efficient approach using array strategy.

Solve on LeetCode
The Problem

Problem Statement

You are given two 0-indexed arrays of strings startWords and targetWords. Each string consists of lowercase English letters only.

For each string in targetWords, check if it is possible to choose a string from startWords and perform a conversion operation on it to be equal to that from targetWords.

The conversion operation is described in the following two steps:

  1. Append any lowercase letter that is not present in the string to its end.
    • For example, if the string is "abc", the letters 'd', 'e', or 'y' can be added to it, but not 'a'. If 'd' is added, the resulting string will be "abcd".
  2. Rearrange the letters of the new string in any arbitrary order.
    • For example, "abcd" can be rearranged to "acbd", "bacd", "cbda", and so on. Note that it can also be rearranged to "abcd" itself.

Return the number of strings in targetWords that can be obtained by performing the operations on any string of startWords.

Note that you will only be verifying if the string in targetWords can be obtained from a string in startWords by performing the operations. The strings in startWords do not actually change during this process.

Example 1:

Input: startWords = ["ant","act","tack"], targetWords = ["tack","act","acti"]
Output: 2
Explanation:
- In order to form targetWords[0] = "tack", we use startWords[1] = "act", append 'k' to it, and rearrange "actk" to "tack".
- There is no string in startWords that can be used to obtain targetWords[1] = "act".
  Note that "act" does exist in startWords, but we must append one letter to the string before rearranging it.
- In order to form targetWords[2] = "acti", we use startWords[1] = "act", append 'i' to it, and rearrange "acti" to "acti" itself.

Example 2:

Input: startWords = ["ab","a"], targetWords = ["abc","abcd"]
Output: 1
Explanation:
- In order to form targetWords[0] = "abc", we use startWords[0] = "ab", add 'c' to it, and rearrange it to "abc".
- There is no string in startWords that can be used to obtain targetWords[1] = "abcd".

Constraints:

  • 1 <= startWords.length, targetWords.length <= 5 * 104
  • 1 <= startWords[i].length, targetWords[j].length <= 26
  • Each string of startWords and targetWords consists of lowercase English letters only.
  • No letter occurs more than once in any string of startWords or targetWords.
Patterns Used

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: You are given two 0-indexed arrays of strings startWords and targetWords. Each string consists of lowercase English letters only. For each string in targetWords, check if it is possible to choose a string from startWords and perform a conversion operation on it to be equal to that from targetWords. The conversion operation is described in the following two steps: Append any lowercase letter that is not present in the string to its end. For example, if the string is "abc", the letters 'd', 'e', or 'y' can be added to it, but not 'a'. If 'd' is added, the resulting string will be "abcd". Rearrange the letters of the new string in any arbitrary order. For example, "abcd" can be rearranged to "acbd", "bacd", "cbda", and so on. Note that it can also be rearranged to "abcd" itself. Return the number of strings in targetWords that can be obtained by performing the operations on any string of

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Array · Hash Map · Bit Manipulation

Example 1

["ant","act","tack"]
["tack","act","acti"]

Example 2

["ab","a"]
["abc","abcd"]

Related Problems

  • Strings Differ by One Character (strings-differ-by-one-character)
  • Count Substrings That Differ by One Character (count-substrings-that-differ-by-one-character)
  • Maximum Score From Removing Substrings (maximum-score-from-removing-substrings)
Step 02

Core Insight

What unlocks the optimal approach

  • Which data structure can be used to efficiently check if a string exists in startWords?
  • After appending a letter, all letters of a string can be rearranged in any possible way. How can we use this to reduce our search space while checking if a string in targetWords can be obtained from a string in startWords?
Interview move: turn each hint into an invariant you can check after every iteration/recursion step.
Step 03

Algorithm Walkthrough

Iteration Checklist

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. Continue until all input is consumed.
Use the first example testcase as your mental trace to verify each transition.
Step 04

Edge Cases

Minimum Input
Single element / shortest valid input
Validate boundary behavior before entering the main loop or recursion.
Duplicates & Repeats
Repeated values / repeated states
Decide whether duplicates should be merged, skipped, or counted explicitly.
Extreme Constraints
Upper-end input sizes
Re-check complexity target against constraints to avoid time-limit issues.
Invalid / Corner Shape
Empty collections, zeros, or disconnected structures
Handle special-case structure before the core algorithm path.
Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #2135: Count Words Obtained After Adding a Letter
class Solution {
    public int wordCount(String[] startWords, String[] targetWords) {
        Set<Integer> s = new HashSet<>();
        for (var w : startWords) {
            int x = 0;
            for (var c : w.toCharArray()) {
                x |= 1 << (c - 'a');
            }
            s.add(x);
        }
        int ans = 0;
        for (var w : targetWords) {
            int x = 0;
            for (var c : w.toCharArray()) {
                x |= 1 << (c - 'a');
            }
            for (var c : w.toCharArray()) {
                if (s.contains(x ^ (1 << (c - 'a')))) {
                    ++ans;
                    break;
                }
            }
        }
        return ans;
    }
}
Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Press Step or Run All to begin.
Step 07

Complexity Analysis

Time
O(n × |\Sigma|)
Space
O(n)

Approach Breakdown

SORT + SCAN
O(n log n) time
O(n) space

Sort the array in O(n log n), then scan for the missing or unique element by comparing adjacent pairs. Sorting requires O(n) auxiliary space (or O(1) with in-place sort but O(n log n) time remains). The sort step dominates.

BIT MANIPULATION
O(n) time
O(1) space

Bitwise operations (AND, OR, XOR, shifts) are O(1) per operation on fixed-width integers. A single pass through the input with bit operations gives O(n) time. The key insight: XOR of a number with itself is 0, which eliminates duplicates without extra space.

Shortcut: Bit operations are O(1). XOR cancels duplicates. Single pass → O(n) time, O(1) space.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.

Mutating counts without cleanup

Wrong move: Zero-count keys stay in map and break distinct/count constraints.

Usually fails on: Window/map size checks are consistently off by one.

Fix: Delete keys when count reaches zero.