Problem Description<\/h2>\n
\n You are preparing for a coding test for hiring new employees. The coding test problem is
\n centered around the theme of ‘I Don’t Want to Be a Liar’. In this problem, you need to determine
\n if someone is lying based on the stories of several employees. You must develop an algorithm to
\n clearly distinguish who is telling the truth and who is lying in the workplace.\n <\/p>\n
Problem Content<\/h3>\n
\n There are N employees. Each employee (A, B, C, …) claims about another employee, stating
\n things like ‘A is a liar’ or ‘B is a liar’. The claims of each employee are all trustworthy, and
\n if a claim is incorrect, it generally becomes a lie.\n <\/p>\n
Input<\/h3>\n\n- The first line contains the number of employees N (1 \u2264 N \u2264 1000).<\/li>\n
- The following N lines provide information about each employee’s claims. Each claim is in the format “This employee is a liar”.<\/li>\n<\/ul>\n
Output<\/h3>\n
\n Output the number of the employee who has lied the most. If there is only one employee who did not lie,
\n output 0.\n <\/p>\n<\/section>\n\nProblem Solving Process<\/h2>\n
\n To solve this problem, you need to analyze the relationships between employees and calculate
\n the number of employees who are lying based on the claims of each employee. Here, we need to
\n understand how each employee’s claims are connected.\n <\/p>\n
Step 1: Data Structure Design<\/h3>\n
\n First, we need to choose a data structure that can store each employee’s claims. We can use a
\n Map where the employee’s number is the key and the value is a list of the employees they claim are liars.\n <\/p>\n
\n For example, if employee 1 claims that employee 2 is a liar, the Map would look like this:\n <\/p>\n
\n {\n 1: [2],\n 2: [3, 4],\n 3: [1],\n ...\n }\n <\/pre>\nStep 2: Graph Traversal (DFS or BFS)<\/h3>\n
\n Once the Map structure is ready, we need to determine who is telling the truth and who is
\n lying through graph traversal. We can use DFS (Depth-First Search) or
\n BFS (Breadth-First Search) algorithms for this purpose.\n <\/p>\n
Step 3: Calculate Results Based on Collected Data<\/h3>\n
\n After the traversal is complete, calculate who has lied the most based on the information
\n about whether each employee is lying.\n <\/p>\n
Step 4: Write Overall Code<\/h3>\n
\n We will implement the above steps in code using Java. Below is an example code to solve
\n the problem:\n <\/p>\n
\n \n import java.util.*;\n\n public class Main {\n public static void main(String[] args) {\n Scanner scanner = new Scanner(System.in);\n int n = scanner.nextInt();\n Map> statements = new HashMap<>();\n\n \/\/ Inputting employee claims\n for (int i = 1; i <= n; i++) {\n int liarIndex = scanner.nextInt();\n if (!statements.containsKey(i)) {\n statements.put(i, new ArrayList<>());\n }\n statements.get(i).add(liarIndex);\n }\n\n int maxLiars = 0;\n\n \/\/ Calculate the number of liars for each employee\n for (int i = 1; i <= n; i++) {\n HashSet visited = new HashSet<>();\n boolean[] isLiar = new boolean[n + 1];\n isLiar[i] = true;\n\n dfs(i, statements, visited, isLiar);\n\n int countLiars = 0;\n for (int j = 1; j <= n; j++) {\n if (isLiar[j]) countLiars++;\n }\n maxLiars = Math.max(maxLiars, countLiars);\n }\n System.out.println(maxLiars);\n }\n\n private static void dfs(int employee, Map> statements, \n HashSet visited, boolean[] isLiar) {\n if (visited.contains(employee)) return;\n visited.add(employee);\n\n if (statements.containsKey(employee)) {\n for (int liar : statements.get(employee)) {\n isLiar[liar] = true;\n dfs(liar, statements, visited, isLiar);\n }\n }\n }\n }\n <\/code>\n <\/pre>\nConclusion<\/h2>\n
\n In this body, we defined the problem centered around ‘I Don’t Want to Be a Liar’
\n and explained the algorithm to solve that problem step by step.
\n By analyzing the information about the claims of employees, we can determine who has lied,
\n and through those results, we can identify the employee who has lied the most.
\n This process can help improve your preparation for coding tests and your problem-solving skills in algorithms.\n <\/p>\n<\/section>\n
<\/main>
\n<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
Output<\/h3>\n
\n Output the number of the employee who has lied the most. If there is only one employee who did not lie, \n To solve this problem, you need to analyze the relationships between employees and calculate \n First, we need to choose a data structure that can store each employee’s claims. We can use a \n For example, if employee 1 claims that employee 2 is a liar, the Map would look like this:\n <\/p>\n \n Once the Map structure is ready, we need to determine who is telling the truth and who is \n After the traversal is complete, calculate who has lied the most based on the information \n We will implement the above steps in code using Java. Below is an example code to solve \n In this body, we defined the problem centered around ‘I Don’t Want to Be a Liar’ <\/main>
\n output 0.\n <\/p>\n<\/section>\nProblem Solving Process<\/h2>\n
\n the number of employees who are lying based on the claims of each employee. Here, we need to
\n understand how each employee’s claims are connected.\n <\/p>\nStep 1: Data Structure Design<\/h3>\n
\n Map where the employee’s number is the key and the value is a list of the employees they claim are liars.\n <\/p>\n\n {\n 1: [2],\n 2: [3, 4],\n 3: [1],\n ...\n }\n <\/pre>\nStep 2: Graph Traversal (DFS or BFS)<\/h3>\n
\n lying through graph traversal. We can use DFS (Depth-First Search) or
\n BFS (Breadth-First Search) algorithms for this purpose.\n <\/p>\nStep 3: Calculate Results Based on Collected Data<\/h3>\n
\n about whether each employee is lying.\n <\/p>\nStep 4: Write Overall Code<\/h3>\n
\n the problem:\n <\/p>\n\n
\n import java.util.*;\n\n public class Main {\n public static void main(String[] args) {\n Scanner scanner = new Scanner(System.in);\n int n = scanner.nextInt();\n MapConclusion<\/h2>\n
\n and explained the algorithm to solve that problem step by step.
\n By analyzing the information about the claims of employees, we can determine who has lied,
\n and through those results, we can identify the employee who has lied the most.
\n This process can help improve your preparation for coding tests and your problem-solving skills in algorithms.\n <\/p>\n<\/section>\n
\n<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"