answer:def can_alice_win(s): Determines if Alice can always make the string a palindrome, regardless of how Bob plays. # Counting the number of position mismatches mismatches = sum(1 for i in range(len(s) // 2) if s[i] != s[-(i + 1)]) # If there are no mismatches, the string is already a palindrome if mismatches == 0: return "Alice wins" # Alice wins if the number of mismatches is less than or equal to her first turn return "Alice wins" if mismatches <= 1 else "Bob wins"

answer:from typing import List def findLongestWord(s: str, d: List[str]) -> str: def can_form(word): it = iter(s) return all(char in it for char in word) longest_word = "" for word in d: if can_form(word): if len(word) > len(longest_word) or (len(word) == len(longest_word) and word < longest_word): longest_word = word return longest_word

answer:def longest_equal_substring(binary_string): Returns the length of the longest substring with an equal number of 0's and 1's. :param binary_string: str: A binary string consisting of '0's and '1's. :return: int: Length of the longest substring with equal number of 0's and 1's. n = len(binary_string) max_len = 0 # Dictionary to store the first occurrence of each count difference count_diff_index = {} count_0 = count_1 = 0 # Difference (count_1 - count_0) count_diff = 0 for i in range(n): if binary_string[i] == '0': count_0 += 1 else: count_1 += 1 count_diff = count_1 - count_0 if count_diff == 0: max_len = i + 1 elif count_diff in count_diff_index: max_len = max(max_len, i - count_diff_index[count_diff]) else: count_diff_index[count_diff] = i return max_len

answer:def canPartition(arr): total_sum = sum(arr) # If total sum is odd, it's not possible to divide it into two equal sum parts if total_sum % 2 != 0: return 'No' target = total_sum // 2 n = len(arr) # Create a 2D DP array dp = [[False] * (target + 1) for _ in range(n + 1)] # Initialize the first column to True, because a sum of 0 can be achieved with an empty subset for i in range(n + 1): dp[i][0] = True # Fill the DP array for i in range(1, n + 1): for j in range(1, target + 1): if arr[i-1] > j: dp[i][j] = dp[i-1][j] else: dp[i][j] = dp[i-1][j] or dp[i-1][j - arr[i-1]] return 'Yes' if dp[n][target] else 'No'