D - Prime Path

本文介绍了一种算法,用于解决两个四位质数间转换的问题,在每一步转换中生成新的质数,并尽量减少替换数字的成本。通过使用图搜索算法,如广度优先搜索(BFS),来找到最经济的转换路径。

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The ministers of the cabinet were quite upset by the message from the Chief of Security stating that they would all have to change the four-digit room numbers on their offices. 
— It is a matter of security to change such things every now and then, to keep the enemy in the dark. 
— But look, I have chosen my number 1033 for good reasons. I am the Prime minister, you know! 
— I know, so therefore your new number 8179 is also a prime. You will just have to paste four new digits over the four old ones on your office door. 
— No, it’s not that simple. Suppose that I change the first digit to an 8, then the number will read 8033 which is not a prime! 
— I see, being the prime minister you cannot stand having a non-prime number on your door even for a few seconds. 
— Correct! So I must invent a scheme for going from 1033 to 8179 by a path of prime numbers where only one digit is changed from one prime to the next prime. 

Now, the minister of finance, who had been eavesdropping, intervened. 
— No unnecessary expenditure, please! I happen to know that the price of a digit is one pound. 
— Hmm, in that case I need a computer program to minimize the cost. You don't know some very cheap software gurus, do you? 
— In fact, I do. You see, there is this programming contest going on... Help the prime minister to find the cheapest prime path between any two given four-digit primes! The first digit must be nonzero, of course. Here is a solution in the case above. 
1033 
1733 
3733 
3739 
3779 
8779 
8179
The cost of this solution is 6 pounds. Note that the digit 1 which got pasted over in step 2 can not be reused in the last step – a new 1 must be purchased.

Input
One line with a positive number: the number of test cases (at most 100). Then for each test case, one line with two numbers separated by a blank. Both numbers are four-digit primes (without leading zeros).

Output

One line for each case, either with a number stating the minimal cost or containing the word Impossible.

Sample Input
3
1033 8179
1373 8017
1033 1033
Sample Output
6
7

代码:


#include<cstdio>
#include<iostream>
#include<string>
#include<queue>
#include<vector>
#include<cstring>
using namespace std;
vector<int>pr(10010,1);
vector<int>in(10010);
struct prime
{
	int x;
	int times;
	prime(int xx,int tt):x(xx),times(tt){
	}
};

int main(void)
{
	int t,x,y;
	scanf("%d",&t);
	int i,j;
	for(i=2;i<101;i++)
	{
		if(pr[i])
		{
			for(j=2*i;j<=10000;j+=i)
			{
				pr[j]=0;
			}
		}
	}
	while(t--)
	{
		scanf("%d %d",&x,&y);
		if(x==y){
		printf("0\n");
		continue;}
		in.assign(in.size(),0);//vector清0 
		queue<prime> q;
		q.push(prime(x,0));
		in[x]=1;
		while(q.size())
		{
			prime now=q.front();
			if(now.x==y)
			{
				break;
			}
			q.pop();
			int a=now.x%10;
			int b=(now.x%100)/10;
			int c=(now.x%1000)/100;
			int d=now.x/1000;
			int sum;
			for(i=0;i<=9;i++)
			{
				sum=d*1000+c*100+b*10+i;
				if(pr[sum]&&!in[sum])
				{
					q.push(prime(sum,now.times+1));
					in[sum]=1;
				}
			}
			for(i=0;i<=9;i++)
			{
				sum=d*1000+c*100+i*10+a;
				if(pr[sum]&&!in[sum])
				{
					q.push(prime(sum,now.times+1));
					in[sum]=1;
				}
			}
			for(i=0;i<=9;i++)
			{
				sum=d*1000+i*100+b*10+a;
				if(pr[sum]&&!in[sum])
				{
					q.push(prime(sum,now.times+1));
					in[sum]=1;
				}
			}
			for(i=1;i<=9;i++)//从1开始哦 
			{
				sum=i*1000+c*100+b*10+a;
				if(pr[sum]&&!in[sum])
				{
					q.push(prime(sum,now.times+1));
					in[sum]=1;
				}
			}
		}
		if(q.size())
		printf("%d\n",q.front().times); 
		else
		printf("Impossible\n");
	}
	return 0;
 } 

### Prime Path 测试路径选择方法概述 Prime Path 是一种用于软件工程中的结构化测试技术,旨在通过识别程序控制流图 (CFG) 中的所有基本环路来提高代码覆盖率和测试效率[^1]。 #### 定义与目标 Prime Path 方法的目标是在不重复覆盖其他更短路径的前提下,确保每条独立执行路径至少被测试一次。这有助于发现隐藏在复杂分支逻辑中的潜在缺陷[^2]。 #### 控制流图构建 为了应用 Prime Path 技术,首先需要基于源代码创建一个表示程序流程的有向无环图(DAG),即控制流图(CFG)[^3]。该图表由节点(代表语句或指令)和边(指示可能的转移方向)组成: ```mermaid graph TD; A[Start] --> B{Condition}; B -->|True| C[Action]; B -->|False| D[Else Action]; C --> E[End]; D --> E; ``` #### 路径分类 根据长度不同,可以将 CFG 上的路径分为三类: - **Trivial Paths**: 单一节点到自身的自循环; - **Nonprime Paths**: 可以分解成多个较短子路径组合而成的复合路径; - **Prime Paths**: 无法进一步拆分的独特最小程序单元之间的连接序列[^4]。 #### 算法实现 以下是 Python 实现的一个简单版本算法,用来找出给定 DAG 的所有素数路径(Prime Paths): ```python from collections import defaultdict, deque def find_prime_paths(cfg): """Find all prime paths in a given control flow graph.""" def dfs(node, visited, path_stack): nonlocal result if node not in cfg or len(path_stack) >= max_length: return for neighbor in cfg[node]: new_path = tuple(list(path_stack) + [neighbor]) if new_path not in seen and \ ((len(set(new_path)) == len(new_path)) or any(x in path_stack for x in cycle_nodes)): seen.add(new_path) result.append(new_path) if neighbor != start_node: dfs(neighbor, visited | {node}, path_stack + [neighbor]) # Initialize variables result = [] seen = set() cycles = [] # Store detected loops/cycles # Detect simple cycles first ... # Identify nodes involved in cycles cycle_nodes = set().union(*cycles) # Perform DFS traversal from each starting point for start_node in cfg.keys(): max_length = min(len(cfg), 8) # Limit depth to avoid excessive recursion dfs(start_node, set(), [start_node]) return result ```
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