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Problem Statement:

You are given a 0-indexed string s and a dictionary of words dictionary. You have to break s into one or more non-overlapping substrings such that each substring is present in dictionary. There may be some extra characters in s which are not present in any of the substrings.

Return the minimum number of extra characters left over if you break up s optimally.

 

Example 1:

Input: s = "leetscode", dictionary = ["leet","code","leetcode"]
Output: 1
Explanation: We can break s in two substrings: "leet" from index 0 to 3 and "code" from index 5 to 8. There is only 1 unused character (at index 4), so we return 1.

Example 2:

Input: s = "sayhelloworld", dictionary = ["hello","world"]
Output: 3
Explanation: We can break s in two substrings: "hello" from index 3 to 7 and "world" from index 8 to 12. The characters at indices 0, 1, 2 are not used in any substring and thus are considered as extra characters. Hence, we return 3.

 

Constraints:

  • 1 <= s.length <= 50
  • 1 <= dictionary.length <= 50
  • 1 <= dictionary[i].length <= 50
  • dictionary[i] and s consists of only lowercase English letters
  • dictionary contains distinct words

Solution:

Let us think through a basic solution. Here is the logic:

  • The largest possible answer is length of string. This is the case where we just add 1 for all values till we reach end.
  • 1+dfs(s,index+1) denotes that we have skipped current index and looking for answer starting from next index.
  • We have a chance of getting lower value if we check set membership for each substring starting from current index. This is the basic idea.

I will provide 3 solutions using above logic. I have kept the variable names same to ease understanding things better.

Naive recursion(TLE)

 
class Solution {
    unordered_set<string> dictSet;
public:
    int dfs(string s, int index)
    {
        if (index>=s.length()) return 0;
        int res = 1 + dfs(s, index+1);
        for (int len=1; len<=s.length()-index;len++)
            if (dictSet.count(s.substr(index,len)))
                    res = min(res, dfs(s, index+len));
        return res;
    }
    int minExtraChar(string s, vector<string>& dictionary) 
    {
        dictSet = unordered_set<string>(dictionary.begin(),dictionary.end());
        return dfs(s,0);
    }
};
 

Recursion with memoization (AC)

 
class Solution {
    unordered_set<string> dictSet;
    vector<int> memo;
public:
    int dfs(string s, int index)
    {
        if (index>=s.length()) return 0;
        if (memo[index]!=-1) return memo[index];
        int res = 1 + dfs(s, index+1);
        for (int len=1; len<=s.length()-index;len++)
            if (dictSet.count(s.substr(index,len)))
                    res = min(res, dfs(s, index+len));
        return memo[index] = res;
    }
    int minExtraChar(string s, vector<string>& dictionary) 
    {
        dictSet = unordered_set<string>(dictionary.begin(),dictionary.end());
        memo = vector<int>(s.length()+1,-1);
        return dfs(s,0);
    }
};
 

Bottom-up DP (AC)

 
class Solution {
public:
    int minExtraChar(string s, vector<string>& dictionary) 
    {
        unordered_set<string> dictSet = unordered_set<string>(dictionary.begin(),dictionary.end());
        vector<int> dp(s.length()+1,0);
        for(int index=s.length()-1; index>=0; index--)
        {
            dp[index] = 1 + dp[index+1];
            for (int len=1; len<=s.length()-index; len++)
                if (dictSet.count(s.substr(index,len)))
                    dp[index] = min(dp[index], dp[index+len]);
        }
        return dp[0];
    }
};