feat: add solutions to lc problems: No.2156,3109

solution/0400-0499/0438.Find All Anagrams in a String/README.md

@@ -364,8 +364,8 @@ function findAnagrams(s: string, p: string): number[] {
     if (m < n) {
         return ans;
     }
-    const cnt1: number[] = new Array(26).fill(0);
-    const cnt2: number[] = new Array(26).fill(0);
+    const cnt1: number[] = Array(26).fill(0);
+    const cnt2: number[] = Array(26).fill(0);
     const idx = (c: string) => c.charCodeAt(0) - 'a'.charCodeAt(0);
     for (const c of p) {
         ++cnt1[idx(c)];

solution/0400-0499/0438.Find All Anagrams in a String/README_EN.md

@@ -348,8 +348,8 @@ function findAnagrams(s: string, p: string): number[] {
     if (m < n) {
         return ans;
     }
-    const cnt1: number[] = new Array(26).fill(0);
-    const cnt2: number[] = new Array(26).fill(0);
+    const cnt1: number[] = Array(26).fill(0);
+    const cnt2: number[] = Array(26).fill(0);
     const idx = (c: string) => c.charCodeAt(0) - 'a'.charCodeAt(0);
     for (const c of p) {
         ++cnt1[idx(c)];

solution/0400-0499/0438.Find All Anagrams in a String/Solution2.ts

@@ -5,8 +5,8 @@ function findAnagrams(s: string, p: string): number[] {
     if (m < n) {
         return ans;
     }
-    const cnt1: number[] = new Array(26).fill(0);
-    const cnt2: number[] = new Array(26).fill(0);
+    const cnt1: number[] = Array(26).fill(0);
+    const cnt2: number[] = Array(26).fill(0);
     const idx = (c: string) => c.charCodeAt(0) - 'a'.charCodeAt(0);
     for (const c of p) {
         ++cnt1[idx(c)];

solution/1700-1799/1766.Tree of Coprimes/README.md

@@ -65,7 +65,7 @@
 
 接下来我们可以使用回溯的方法，从根节点开始遍历整棵树，对于每个节点 $i$，我们可以通过 $f$ 数组得到 $nums[i]$ 的所有互质数。然后我们枚举 $nums[i]$ 的所有互质数，找到已经出现过的且深度最大的祖先节点 $t$，即为 $i$ 的最近的互质祖先节点。这里我们可以用一个长度为 $51$ 的栈数组 $stks$ 来获取每个出现过的值 $v$ 的节点以及其深度。每个栈 $stks[v]$ 的栈顶元素就是最近的深度最大的祖先节点。
 
-时间复杂度 $O(n)$，空间复杂度 $O(n)$。其中 $n$ 为节点个数。
+时间复杂度 $O(n \times M)$，空间复杂度 $O(M^2 + n)$。其中 $n$ 为节点个数，而 $M$ 为 $nums[i]$ 的最大值，本题中 $M = 50$。
 
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solution/1700-1799/1766.Tree of Coprimes/README_EN.md

@@ -57,7 +57,13 @@
 
 ## Solutions
 
-### Solution 1
+### Solution 1: Preprocessing + Enumeration + Stack + Backtracking
+
+Since the range of $nums[i]$ in the problem is $[1, 50]$, we can preprocess all the coprime numbers for each number and record them in the array $f$, where $f[i]$ represents all the coprime numbers of $i$.
+
+Next, we can use a backtracking method to traverse the entire tree from the root node. For each node $i$, we can get all the coprime numbers of $nums[i]$ through the array $f$. Then we enumerate all the coprime numbers of $nums[i]$, find the ancestor node $t$ that has appeared and has the maximum depth, which is the nearest coprime ancestor node of $i$. Here we can use a stack array $stks$ of length $51$ to get each appeared value $v$ and its depth. The top element of each stack $stks[v]$ is the nearest ancestor node with the maximum depth.
+
+The time complexity is $O(n \times M)$, and the space complexity is $O(M^2 + n)$. Where $n$ is the number of nodes, and $M$ is the maximum value of $nums[i]$, in this problem $M = 50$.
 
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solution/2100-2199/2156.Find Substring With Given Hash Value/README.md

@@ -56,10 +56,149 @@
 
 ## 解法
 
-### 方法一
+### 方法一：滑动窗口 + 倒序遍历
+
+我们可以维护一个长度为 $k$ 的滑动窗口，用来计算子串的哈希值。考虑到如果正序遍历字符串，在哈希值的计算中，涉及到除法取模的操作，处理起来比较麻烦。因此我们可以倒序遍历字符串，这样在计算哈希值的时候，只需要乘法和取模操作。
+
+我们首先计算字符串末尾的 $k$ 个字符的哈希值，然后从字符串末尾开始倒序遍历，每次计算当前窗口的哈希值，如果等于给定的哈希值，我们就找到了一个满足条件的子串，更新答案字符串的起始位置。
+
+最后返回答案字符串即可。
+
+时间复杂度 $O(n)$，其中 $n$ 是字符串的长度。空间复杂度 $O(1)$。
 
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+```python
+class Solution:
+    def subStrHash(
+        self, s: str, power: int, modulo: int, k: int, hashValue: int
+    ) -> str:
+        h, n = 0, len(s)
+        p = 1
+        for i in range(n - 1, n - 1 - k, -1):
+            val = ord(s[i]) - ord("a") + 1
+            h = ((h * power) + val) % modulo
+            if i != n - k:
+                p = p * power % modulo
+        j = n - k
+        for i in range(n - 1 - k, -1, -1):
+            pre = ord(s[i + k]) - ord("a") + 1
+            cur = ord(s[i]) - ord("a") + 1
+            h = ((h - pre * p) * power + cur) % modulo
+            if h == hashValue:
+                j = i
+        return s[j : j + k]
+```
+
+```java
+class Solution {
+    public String subStrHash(String s, int power, int modulo, int k, int hashValue) {
+        long h = 0, p = 1;
+        int n = s.length();
+        for (int i = n - 1; i >= n - k; --i) {
+            int val = s.charAt(i) - 'a' + 1;
+            h = ((h * power % modulo) + val) % modulo;
+            if (i != n - k) {
+                p = p * power % modulo;
+            }
+        }
+        int j = n - k;
+        for (int i = n - k - 1; i >= 0; --i) {
+            int pre = s.charAt(i + k) - 'a' + 1;
+            int cur = s.charAt(i) - 'a' + 1;
+            h = ((h - pre * p % modulo + modulo) * power % modulo + cur) % modulo;
+            if (h == hashValue) {
+                j = i;
+            }
+        }
+        return s.substring(j, j + k);
+    }
+}
+```
+
+```cpp
+class Solution {
+public:
+    string subStrHash(string s, int power, int modulo, int k, int hashValue) {
+        long long h = 0, p = 1;
+        int n = s.size();
+        for (int i = n - 1; i >= n - k; --i) {
+            int val = s[i] - 'a' + 1;
+            h = ((h * power % modulo) + val) % modulo;
+            if (i != n - k) {
+                p = p * power % modulo;
+            }
+        }
+        int j = n - k;
+        for (int i = n - k - 1; i >= 0; --i) {
+            int pre = s[i + k] - 'a' + 1;
+            int cur = s[i] - 'a' + 1;
+            h = ((h - pre * p % modulo + modulo) * power % modulo + cur) % modulo;
+            if (h == hashValue) {
+                j = i;
+            }
+        }
+        return s.substr(j, k);
+    }
+};
+```
+
+```go
+func subStrHash(s string, power int, modulo int, k int, hashValue int) string {
+	h, p := 0, 1
+	n := len(s)
+	for i := n - 1; i >= n-k; i-- {
+		val := int(s[i] - 'a' + 1)
+		h = (h*power%modulo + val) % modulo
+		if i != n-k {
+			p = p * power % modulo
+		}
+	}
+	j := n - k
+	for i := n - k - 1; i >= 0; i-- {
+		pre := int(s[i+k] - 'a' + 1)
+		cur := int(s[i] - 'a' + 1)
+		h = ((h-pre*p%modulo+modulo)*power%modulo + cur) % modulo
+		if h == hashValue {
+			j = i
+		}
+	}
+	return s[j : j+k]
+}
+```
+
+```ts
+function subStrHash(
+    s: string,
+    power: number,
+    modulo: number,
+    k: number,
+    hashValue: number,
+): string {
+    let h: bigint = BigInt(0),
+        p: bigint = BigInt(1);
+    const n: number = s.length;
+    const mod = BigInt(modulo);
+    for (let i: number = n - 1; i >= n - k; --i) {
+        const val: bigint = BigInt(s.charCodeAt(i) - 'a'.charCodeAt(0) + 1);
+        h = (((h * BigInt(power)) % mod) + val) % mod;
+        if (i !== n - k) {
+            p = (p * BigInt(power)) % mod;
+        }
+    }
+    let j: number = n - k;
+    for (let i: number = n - k - 1; i >= 0; --i) {
+        const pre: bigint = BigInt(s.charCodeAt(i + k) - 'a'.charCodeAt(0) + 1);
+        const cur: bigint = BigInt(s.charCodeAt(i) - 'a'.charCodeAt(0) + 1);
+        h = ((((h - ((pre * p) % mod) + mod) * BigInt(power)) % mod) + cur) % mod;
+        if (Number(h) === hashValue) {
+            j = i;
+        }
+    }
+    return s.substring(j, j + k);
+}
+```
+
 ```js
 /**
  * @param {string} s
@@ -70,34 +209,28 @@
  * @return {string}
  */
 var subStrHash = function (s, power, modulo, k, hashValue) {
-    power = BigInt(power);
-    modulo = BigInt(modulo);
-    hashValue = BigInt(hashValue);
+    let h = BigInt(0),
+        p = BigInt(1);
     const n = s.length;
-    let pk = 1n;
-    let ac = 0n;
-    // 倒序滑动窗口
-    for (let i = n - 1; i > n - 1 - k; i--) {
-        ac = (ac * power + getCode(s, i)) % modulo;
-        pk = (pk * power) % modulo;
-    }
-    let ans = -1;
-    if (ac == hashValue) {
-        ans = n - k;
+    const mod = BigInt(modulo);
+    for (let i = n - 1; i >= n - k; --i) {
+        const val = BigInt(s.charCodeAt(i) - 'a'.charCodeAt(0) + 1);
+        h = (((h * BigInt(power)) % mod) + val) % mod;
+        if (i !== n - k) {
+            p = (p * BigInt(power)) % mod;
+        }
     }
-    for (let i = n - 1 - k; i >= 0; i--) {
-        let pre = (getCode(s, i + k) * pk) % modulo;
-        ac = (ac * power + getCode(s, i) - pre + modulo) % modulo;
-        if (ac == hashValue) {
-            ans = i;
+    let j = n - k;
+    for (let i = n - k - 1; i >= 0; --i) {
+        const pre = BigInt(s.charCodeAt(i + k) - 'a'.charCodeAt(0) + 1);
+        const cur = BigInt(s.charCodeAt(i) - 'a'.charCodeAt(0) + 1);
+        h = ((((h - ((pre * p) % mod) + mod) * BigInt(power)) % mod) + cur) % mod;
+        if (Number(h) === hashValue) {
+            j = i;
         }
     }
-    return ans == -1 ? '' : s.substring(ans, ans + k);
+    return s.substring(j, j + k);
 };
-
-function getCode(str, index) {
-    return BigInt(str.charCodeAt(index) - 'a'.charCodeAt(0) + 1);
-}
 ```
 
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