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3291. Minimum Number of Valid Strings to Form Target I

Description

You are given an array of strings words and a string target.

A string x is called valid if x is a prefix of any string in words.

Return the minimum number of valid strings that can be concatenated to form target. If it is not possible to form target, return -1.

 

Example 1:

Input: words = ["abc","aaaaa","bcdef"], target = "aabcdabc"

Output: 3

Explanation:

The target string can be formed by concatenating:

  • Prefix of length 2 of words[1], i.e. "aa".
  • Prefix of length 3 of words[2], i.e. "bcd".
  • Prefix of length 3 of words[0], i.e. "abc".

Example 2:

Input: words = ["abababab","ab"], target = "ababaababa"

Output: 2

Explanation:

The target string can be formed by concatenating:

  • Prefix of length 5 of words[0], i.e. "ababa".
  • Prefix of length 5 of words[0], i.e. "ababa".

Example 3:

Input: words = ["abcdef"], target = "xyz"

Output: -1

 

Constraints:

  • 1 <= words.length <= 100
  • 1 <= words[i].length <= 5 * 103
  • The input is generated such that sum(words[i].length) <= 105.
  • words[i] consists only of lowercase English letters.
  • 1 <= target.length <= 5 * 103
  • target consists only of lowercase English letters.

Solutions

Solution 1: Trie + Memoization

We can use a trie to store all valid strings and then use memoization to calculate the answer.

We design a function $\textit{dfs}(i)$, which represents the minimum number of strings needed to concatenate starting from the $i$-th character of the string $\textit{target}$. The answer is $\textit{dfs}(0)$.

The function $\textit{dfs}(i)$ is calculated as follows:

  • If $i \geq n$, it means the string $\textit{target}$ has been completely traversed, so we return $0$;
  • Otherwise, we can find valid strings in the trie that start with $\textit{target}[i]$, and then recursively calculate $\textit{dfs}(i + \text{len}(w))$, where $w$ is the valid string found. We take the minimum of these values and add $1$ as the return value of $\textit{dfs}(i)$.

To avoid redundant calculations, we use memoization.

The time complexity is $O(n^2 + L)$, and the space complexity is $O(n + L)$. Here, $n$ is the length of the string $\textit{target}$, and $L$ is the total length of all valid strings.

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def min(a: int, b: int) -> int:
    return a if a < b else b


class Trie:
    def __init__(self):
        self.children: List[Optional[Trie]] = [None] * 26

    def insert(self, w: str):
        node = self
        for i in map(lambda c: ord(c) - 97, w):
            if node.children[i] is None:
                node.children[i] = Trie()
            node = node.children[i]


class Solution:
    def minValidStrings(self, words: List[str], target: str) -> int:
        @cache
        def dfs(i: int) -> int:
            if i >= n:
                return 0
            node = trie
            ans = inf
            for j in range(i, n):
                k = ord(target[j]) - 97
                if node.children[k] is None:
                    break
                node = node.children[k]
                ans = min(ans, 1 + dfs(j + 1))
            return ans

        trie = Trie()
        for w in words:
            trie.insert(w)
        n = len(target)
        ans = dfs(0)
        return ans if ans < inf else -1

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class Trie {
    Trie[] children = new Trie[26];

    void insert(String w) {
        Trie node = this;
        for (int i = 0; i < w.length(); ++i) {
            int j = w.charAt(i) - 'a';
            if (node.children[j] == null) {
                node.children[j] = new Trie();
            }
            node = node.children[j];
        }
    }
}

class Solution {
    private Integer[] f;
    private char[] s;
    private Trie trie;
    private final int inf = 1 << 30;

    public int minValidStrings(String[] words, String target) {
        trie = new Trie();
        for (String w : words) {
            trie.insert(w);
        }
        s = target.toCharArray();
        f = new Integer[s.length];
        int ans = dfs(0);
        return ans < inf ? ans : -1;
    }

    private int dfs(int i) {
        if (i >= s.length) {
            return 0;
        }
        if (f[i] != null) {
            return f[i];
        }
        Trie node = trie;
        f[i] = inf;
        for (int j = i; j < s.length; ++j) {
            int k = s[j] - 'a';
            if (node.children[k] == null) <