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矩阵类的题目能用DFS解答的都要想到memoization来优化,Tree则不能用memo优化

Wildcard Matching

  • 首先想DFS暴力解法的recursion递归的拆解逻辑,不要一上来就想DP

  • 这题提供两种wildcard

'?' Matches any single character.

'*' Matches any sequence of characters (including the empty sequence).

  • 重点就在"*", 可以match 0 or more chars, 那就分成两种情况讨论

    • match 0 char, then return isMatch(s, sIndex, p, pIndex + 1)

    • match at least 1 char, then return isMatch(s, sIndex + 1, p, pIndex)

  • 定义好了递归3要素,至少可以写出DFS brute force solution

  • 这里可以用memoization做优化实现o(m*n) Time, o(m*n) Space

class Solution {
    /*
    "abcab" and "*a*b"
    p is allStar "***"
    isMatch(s, sIndex, p, pIndex)
    
    pIndex == sIndex -> return isMatch(s, sIndex + 1, p, pIndex + 1)
    pIndex == ? -> return isMatch(s, sIndex + 1, p, pIndex + 1)
    group into same isCharMatch(sChar, pChar)
    
    pIndex == * -> return isMatch(s, sIndex, p, pIndex + 1) || isMatch(s, sIndex + 1, p, pIndex)
    
    use memoization to avoid duplicate calculation
    boolean[m][n] visited
    boolean[m][n] memo
    
    O(m * n) Time
    O(m * n) Space
    
    */
    
    public boolean isMatch(String s, String p) {
        if (s == null || p == null) return false;
        int m = s.length(), n = p.length();
        //use memoization to avoid duplicate calculation
        boolean[][] visited = new boolean[m][n];
        boolean[][] memo = new boolean[m][n];
        return isMatch(s, 0, p, 0, visited, memo);
    }
    
    //definition of recursion: check whether s.substring(sIndex) and p.substring(pIndex) can be a match or not
    private boolean isMatch(String s, int sIndex, String p, int pIndex, boolean[][] visited, boolean[][] memo) {
        //base case
        if (pIndex == p.length()) {
            return sIndex == s.length() ;
        }
        if (sIndex == s.length()) {
            return isAllStar(p, pIndex);
        }
        //fetch from memo
        if (visited[sIndex][pIndex]) {
            return memo[sIndex][pIndex];
        }
        //transition
        char sChar = s.charAt(sIndex), pChar = p.charAt(pIndex);
        if (pChar == '*') {
            memo[sIndex][pIndex] =  isMatch(s, sIndex, p, pIndex + 1, visited, memo) ||  isMatch(s, sIndex + 1, p, pIndex, visited, memo);
        } else {
            memo[sIndex][pIndex] = isCharMatch(sChar, pChar) && isMatch(s, sIndex + 1, p, pIndex + 1, visited, memo);
        }
        
        //set memo
        visited[sIndex][pIndex] = true;
        return memo[sIndex][pIndex];
    }
    private boolean isAllStar(String p, int idx) {
        for (int i = idx; i < p.length(); i++) {
            if (p.charAt(i) != '*') {
                return false;
            }
        }
        return true;
    }
    private boolean isCharMatch(char sChar, char pChar) {
        return sChar == pChar || pChar == '?';
    }
}

Regular Expression Matching

  • 做完wildcard matching之后再做这题思路就清晰很多了

  • 和 Wildcard Matching 同样模板的代码, 只需要更改“*“ 的matching logic,就好

  • '*' Matches zero or more of the preceding element.

  • '*' 不会单独出现或者出现在首位

  • 需要把'*'和前面的char连起来看, ‘‘c*a*b" -> "c*", 不能直接判断'*' char

Word Break

  • state:canBreak[i] means whether sb.substring(0, i) can be break

  • canBreak[i] = dict.contains(s.susbtring(j, i)) && canBreak[j]

  • i from [1, n]

  • j from [0, i)

  • return canBreak[n]

Word Break II

  • same idea of wordBreak, use memo to avoid duplicate calculation

  • use Map for memo, key is string, value is List<String> that can be break for key

  • optimization: get maxLen of word in wordDict, then we just need to iterate for length of maxLen instead of iterate through whole string s.

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