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.
Break down a hard problem into reliable checkpoints, edge-case handling, and complexity trade-offs.
You are given a list of strings of the same length words and a string target.
Your task is to form target using the given words under the following rules:
target should be formed from left to right.ith character (0-indexed) of target, you can choose the kth character of the jth string in words if target[i] = words[j][k].kth character of the jth string of words, you can no longer use the xth character of any string in words where x <= k. In other words, all characters to the left of or at index k become unusuable for every string.target.Notice that you can use multiple characters from the same string in words provided the conditions above are met.
Return the number of ways to form target from words. Since the answer may be too large, return it modulo 109 + 7.
Example 1:
Input: words = ["acca","bbbb","caca"], target = "aba"
Output: 6
Explanation: There are 6 ways to form target.
"aba" -> index 0 ("acca"), index 1 ("bbbb"), index 3 ("caca")
"aba" -> index 0 ("acca"), index 2 ("bbbb"), index 3 ("caca")
"aba" -> index 0 ("acca"), index 1 ("bbbb"), index 3 ("acca")
"aba" -> index 0 ("acca"), index 2 ("bbbb"), index 3 ("acca")
"aba" -> index 1 ("caca"), index 2 ("bbbb"), index 3 ("acca")
"aba" -> index 1 ("caca"), index 2 ("bbbb"), index 3 ("caca")
Example 2:
Input: words = ["abba","baab"], target = "bab"
Output: 4
Explanation: There are 4 ways to form target.
"bab" -> index 0 ("baab"), index 1 ("baab"), index 2 ("abba")
"bab" -> index 0 ("baab"), index 1 ("baab"), index 3 ("baab")
"bab" -> index 0 ("baab"), index 2 ("baab"), index 3 ("baab")
"bab" -> index 1 ("abba"), index 2 ("baab"), index 3 ("baab")
Constraints:
1 <= words.length <= 10001 <= words[i].length <= 1000words have the same length.1 <= target.length <= 1000words[i] and target contain only lowercase English letters.Problem summary: You are given a list of strings of the same length words and a string target. Your task is to form target using the given words under the following rules: target should be formed from left to right. To form the ith character (0-indexed) of target, you can choose the kth character of the jth string in words if target[i] = words[j][k]. Once you use the kth character of the jth string of words, you can no longer use the xth character of any string in words where x <= k. In other words, all characters to the left of or at index k become unusuable for every string. Repeat the process until you form the string target. Notice that you can use multiple characters from the same string in words provided the conditions above are met. Return the number of ways to form target from words. Since the answer may be too large, return it modulo 109 + 7.
Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.
Pattern signal: Array · Dynamic Programming
["acca","bbbb","caca"] "aba"
["abba","baab"] "bab"
Source-backed implementations are provided below for direct study and interview prep.
// Accepted solution for LeetCode #1639: Number of Ways to Form a Target String Given a Dictionary
class Solution {
private int m;
private int n;
private String target;
private Integer[][] f;
private int[][] cnt;
private final int mod = (int) 1e9 + 7;
public int numWays(String[] words, String target) {
m = target.length();
n = words[0].length();
f = new Integer[m][n];
this.target = target;
cnt = new int[n][26];
for (var w : words) {
for (int j = 0; j < n; ++j) {
cnt[j][w.charAt(j) - 'a']++;
}
}
return dfs(0, 0);
}
private int dfs(int i, int j) {
if (i >= m) {
return 1;
}
if (j >= n) {
return 0;
}
if (f[i][j] != null) {
return f[i][j];
}
long ans = dfs(i, j + 1);
ans += 1L * dfs(i + 1, j + 1) * cnt[j][target.charAt(i) - 'a'];
ans %= mod;
return f[i][j] = (int) ans;
}
}
// Accepted solution for LeetCode #1639: Number of Ways to Form a Target String Given a Dictionary
func numWays(words []string, target string) int {
m, n := len(target), len(words[0])
f := make([][]int, m)
cnt := make([][26]int, n)
for _, w := range words {
for j, c := range w {
cnt[j][c-'a']++
}
}
for i := range f {
f[i] = make([]int, n)
for j := range f[i] {
f[i][j] = -1
}
}
const mod = 1e9 + 7
var dfs func(i, j int) int
dfs = func(i, j int) int {
if i >= m {
return 1
}
if j >= n {
return 0
}
if f[i][j] != -1 {
return f[i][j]
}
ans := dfs(i, j+1)
ans = (ans + dfs(i+1, j+1)*cnt[j][target[i]-'a']) % mod
f[i][j] = ans
return ans
}
return dfs(0, 0)
}
# Accepted solution for LeetCode #1639: Number of Ways to Form a Target String Given a Dictionary
class Solution:
def numWays(self, words: List[str], target: str) -> int:
@cache
def dfs(i: int, j: int) -> int:
if i >= m:
return 1
if j >= n:
return 0
ans = dfs(i + 1, j + 1) * cnt[j][ord(target[i]) - ord('a')]
ans = (ans + dfs(i, j + 1)) % mod
return ans
m, n = len(target), len(words[0])
cnt = [[0] * 26 for _ in range(n)]
for w in words:
for j, c in enumerate(w):
cnt[j][ord(c) - ord('a')] += 1
mod = 10**9 + 7
return dfs(0, 0)
// Accepted solution for LeetCode #1639: Number of Ways to Form a Target String Given a Dictionary
/**
* [1639] Number of Ways to Form a Target String Given a Dictionary
*
* You are given a list of strings of the same length words and a string target.
* Your task is to form target using the given words under the following rules:
*
* target should be formed from left to right.
* To form the i^th character (0-indexed) of target, you can choose the k^th character of the j^th string in words if target[i] = words[j][k].
* Once you use the k^th character of the j^th string of words, you can no longer use the x^th character of any string in words where x <= k. In other words, all characters to the left of or at index k become unusuable for every string.
* Repeat the process until you form the string target.
*
* Notice that you can use multiple characters from the same string in words provided the conditions above are met.
* Return the number of ways to form target from words. Since the answer may be too large, return it modulo 10^9 + 7.
*
* Example 1:
*
* Input: words = ["acca","bbbb","caca"], target = "aba"
* Output: 6
* Explanation: There are 6 ways to form target.
* "aba" -> index 0 ("<u>a</u>cca"), index 1 ("b<u>b</u>bb"), index 3 ("cac<u>a</u>")
* "aba" -> index 0 ("<u>a</u>cca"), index 2 ("bb<u>b</u>b"), index 3 ("cac<u>a</u>")
* "aba" -> index 0 ("<u>a</u>cca"), index 1 ("b<u>b</u>bb"), index 3 ("acc<u>a</u>")
* "aba" -> index 0 ("<u>a</u>cca"), index 2 ("bb<u>b</u>b"), index 3 ("acc<u>a</u>")
* "aba" -> index 1 ("c<u>a</u>ca"), index 2 ("bb<u>b</u>b"), index 3 ("acc<u>a</u>")
* "aba" -> index 1 ("c<u>a</u>ca"), index 2 ("bb<u>b</u>b"), index 3 ("cac<u>a</u>")
*
* Example 2:
*
* Input: words = ["abba","baab"], target = "bab"
* Output: 4
* Explanation: There are 4 ways to form target.
* "bab" -> index 0 ("<u>b</u>aab"), index 1 ("b<u>a</u>ab"), index 2 ("ab<u>b</u>a")
* "bab" -> index 0 ("<u>b</u>aab"), index 1 ("b<u>a</u>ab"), index 3 ("baa<u>b</u>")
* "bab" -> index 0 ("<u>b</u>aab"), index 2 ("ba<u>a</u>b"), index 3 ("baa<u>b</u>")
* "bab" -> index 1 ("a<u>b</u>ba"), index 2 ("ba<u>a</u>b"), index 3 ("baa<u>b</u>")
*
*
* Constraints:
*
* 1 <= words.length <= 1000
* 1 <= words[i].length <= 1000
* All strings in words have the same length.
* 1 <= target.length <= 1000
* words[i] and target contain only lowercase English letters.
*
*/
pub struct Solution {}
// problem: https://leetcode.com/problems/number-of-ways-to-form-a-target-string-given-a-dictionary/
// discuss: https://leetcode.com/problems/number-of-ways-to-form-a-target-string-given-a-dictionary/discuss/?currentPage=1&orderBy=most_votes&query=
// submission codes start here
const MOD: i32 = 1e9 as i32 + 7;
impl Solution {
pub fn num_ways(words: Vec<String>, target: String) -> i32 {
let (m, n) = (words[0].len(), target.len());
let mut hash = vec![vec![0; 26]; m];
let target_chars: Vec<char> = target.chars().collect();
for word in words.iter() {
for (i, c) in word.chars().enumerate() {
hash[i][c as usize - 'a' as usize] += 1;
}
}
let mut dp = vec![vec![0 as i64; n]; m];
dp[0][0] = hash[0][target_chars[0] as usize - 'a' as usize];
for i in 1..m {
dp[i][0] =
(dp[i - 1][0] + hash[i][target_chars[0] as usize - 'a' as usize]) % MOD as i64;
for j in 1..n {
dp[i][j] = (dp[i - 1][j]
+ dp[i - 1][j - 1] * hash[i][target_chars[j] as usize - 'a' as usize])
% MOD as i64;
}
}
dp[m - 1][n - 1] as i32
}
}
// submission codes end
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_1639_example_1() {
let words = vec_string!["acca", "bbbb", "caca"];
let target = "aba".to_string();
let result = 6;
assert_eq!(Solution::num_ways(words, target), result);
}
#[test]
fn test_1639_example_2() {
let words = vec_string!["abba", "baab"];
let target = "bab".to_string();
let result = 4;
assert_eq!(Solution::num_ways(words, target), result);
}
}
// Accepted solution for LeetCode #1639: Number of Ways to Form a Target String Given a Dictionary
function numWays(words: string[], target: string): number {
const m = target.length;
const n = words[0].length;
const f = new Array(m + 1).fill(0).map(() => new Array(n + 1).fill(0));
const mod = 1e9 + 7;
for (let j = 0; j <= n; ++j) {
f[0][j] = 1;
}
const cnt = new Array(n).fill(0).map(() => new Array(26).fill(0));
for (const w of words) {
for (let j = 0; j < n; ++j) {
++cnt[j][w.charCodeAt(j) - 97];
}
}
for (let i = 1; i <= m; ++i) {
for (let j = 1; j <= n; ++j) {
f[i][j] = f[i][j - 1] + f[i - 1][j - 1] * cnt[j - 1][target.charCodeAt(i - 1) - 97];
f[i][j] %= mod;
}
}
return f[m][n];
}
Use this to step through a reusable interview workflow for this problem.
Pure recursion explores every possible choice at each step. With two choices per state (take or skip), the decision tree has 2ⁿ leaves. The recursion stack uses O(n) space. Many subproblems are recomputed exponentially many times.
Each cell in the DP table is computed exactly once from previously solved subproblems. The table dimensions determine both time and space. Look for the state variables — each unique combination of state values is one cell. Often a rolling array can reduce space by one dimension.
Review these before coding to avoid predictable interview regressions.
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.
Wrong move: An incomplete state merges distinct subproblems and caches incorrect answers.
Usually fails on: Correctness breaks on cases that differ only in hidden state.
Fix: Define state so each unique subproblem maps to one DP cell.