HDU5237 - Base64

本文介绍了一道关于BASE64编码的模拟题解决思路及实现代码。文章详细解释了如何将原字符串每三字节24位重新切分为4个6位,并通过查找表转换为对应的BASE64码,同时处理不足三字节的情况。

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一道比较显而易见的模拟题,相对而言字符串处理对我更难一些。。

有点像之前某校校赛现场做的一道题,完成MD5的解密过程


只需要实现将原字符串每三字节24位重新切分为4个6位,然后从表里转换为对应的BASE64码即可,不足三字节的用0补满至下一个6位(即剩一个字节补4个0补成12位,剩下两个字节补2个0补成18位),然后用'='补齐剩下的空位即可。


代码:(对字符串的处理很丑。。。见谅)

#include<iostream>
#include<cstdio>
#include<string.h>
using namespace std;

char S[1000],Q[1000];
char Std[65]="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/";
void Make(int x)
{
    Q[strlen(Q)]=Std[x];
}
void f(int n) //以二进制方式输出整数n
{ 
    if(n) f(n/2); 
    else return; 
    printf("%d",n%2); 
} 
int main()
{
    int t,tm;
    scanf("%d",&tm);t=tm;
    while(t--)
    {
        int k,i,n;
        scanf("%d %s",&n,S);
        while(n--)
        {
            memset(Q,0,sizeof(Q));
            int l=strlen(S);
            for(i=0;i<l;i++)
            {
                if(i%3==0)
                    Make(S[i]/4);
                if(i%3==1)
                    Make((S[i-1]%4)*16+S[i]/16);
                if(i%3==2)
                {
                    Make((S[i-1]%16)*4+S[i]/64);
                    Make(S[i]%64);
                }
            }
            if(l%3)
            {
                int key=(S[l-1]%4)*16;
                if(l%3==2) key=(S[l-1]%16)*4;
                Make(key);
                strcat(Q,"=");
                if(l%3==1) strcat(Q,"=");    
            }
            Q[strlen(Q)]='\0';
            strcpy(S,Q);
            
        }
        printf("Case #%d: %s\n",tm-t,S);
    }
    return 0;
}


### HDU 1466 Problem Description and Solution The problem **HDU 1466** involves calculating the expected number of steps to reach a certain state under specific conditions. The key elements include: #### Problem Statement Given an interactive scenario where operations are performed on numbers modulo \(998244353\), one must determine the expected number of steps required to achieve a particular outcome. For this type of problem, dynamic programming (DP) is often employed as it allows breaking down complex problems into simpler subproblems that can be solved iteratively or recursively with memoization techniques[^1]. In more detail, consider the constraints provided by similar problems such as those found in references like HDU 6327 which deals with random sequences using DP within given bounds \((1 \leq T \leq 10, 4 \leq n \leq 100)\)[^2]. These types of constraints suggest iterative approaches over small ranges might work efficiently here too. Additionally, when dealing with large inputs up to \(2 \times 10^7\) as seen in reference materials related to counting algorithms [^4], efficient data structures and optimization strategies become crucial for performance reasons. However, directly applying these methods requires understanding how they fit specifically into solving the expectation value calculation involved in HDU 1466. For instance, if each step has multiple outcomes weighted differently based on probabilities, then summing products of probability times cost across all possible states until convergence gives us our answer. To implement this approach effectively: ```python MOD = 998244353 def solve_expectation(n): dp = [0] * (n + 1) # Base case initialization depending upon problem specifics for i in range(1, n + 1): total_prob = 0 # Calculate transition probabilities from previous states for j in transitions_from(i): # Placeholder function representing valid moves prob = calculate_probability(j) next_state_cost = get_next_state_cost(j) dp[i] += prob * (next_state_cost + dp[j]) % MOD total_prob += prob dp[i] %= MOD # Normalize current state's expectation due to accumulated probability mass if total_prob != 0: dp[i] *= pow(total_prob, MOD - 2, MOD) dp[i] %= MOD return dp[n] # Example usage would depend heavily on exact rules governing transitions between states. ``` This code snippet outlines a generic framework tailored towards computing expectations via dynamic programming while adhering strictly to modular arithmetic requirements specified by the contest question format.
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