{"id":34948,"date":"2024-11-01T09:33:54","date_gmt":"2024-11-01T09:33:54","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=34948"},"modified":"2024-11-01T12:54:32","modified_gmt":"2024-11-01T12:54:32","slug":"%ec%bd%94%ed%8b%80%eb%a6%b0-%ec%bd%94%eb%94%a9%ed%85%8c%ec%8a%a4%ed%8a%b8-%ea%b0%95%ec%a2%8c-%ea%b2%bd%eb%a1%9c-%ec%b0%be%ea%b8%b0-2","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/34948\/","title":{"rendered":"Kotlin coding test course, pathfinding"},"content":{"rendered":"<p><body><\/p>\n<header>\n<\/header>\n<section>\n<h2>1. Introduction to the Problem<\/h2>\n<p>\n            The pathfinding problem is about finding a route between specific nodes (vertices) in a given graph.<br \/>\n            This problem is one of the fundamental and important problems for evaluating coding tests and algorithm problem-solving abilities.<br \/>\n            In this course, we will explain how to solve such problems using Kotlin.\n        <\/p>\n<\/section>\n<section>\n<h2>2. Problem Definition<\/h2>\n<p>\n            Determine whether a path exists between the start node and the goal node in the given graph,<br \/>\n            and if a path exists, print the corresponding path.\n        <\/p>\n<h3>Input Format<\/h3>\n<ul>\n<li>The first line: the number of vertices N (1 &lt;= N &lt;= 1000)<\/li>\n<li>The second line: the number of edges M (0 &lt;= M &lt;= 10000)<\/li>\n<li>From the third line to M lines: edge information (vertex A, vertex B)<\/li>\n<li>The last line: start node and goal node (start, goal)<\/li>\n<\/ul>\n<h3>Output Format<\/h3>\n<ul>\n<li>If a path exists, print that path; if not, print &#8220;No path exists.&#8221;<\/li>\n<\/ul>\n<\/section>\n<section>\n<h2>3. Problem-Solving Strategy<\/h2>\n<p>\n            To solve the pathfinding problem, the following algorithms can be used:\n        <\/p>\n<ul>\n<li>Breadth-First Search (BFS)<\/li>\n<li>Depth-First Search (DFS)<\/li>\n<\/ul>\n<p>\n            Here, we will look at how to search for the shortest path using BFS. Since BFS explores in levels,<br \/>\n            it is advantageous for finding the shortest path.\n        <\/p>\n<\/section>\n<section>\n<h2>4. Algorithm Implementation (Kotlin Example)<\/h2>\n<pre>\n            <code>\n                import java.util.*\n\n                fun bfs(graph: Array<mutableList<Int>>, start: Int, goal: Int): List<Int>? {\n                    val queue: Queue<Int> = LinkedList()\n                    val visited = BooleanArray(graph.size)\n                    val parent = IntArray(graph.size) { -1 }\n\n                    queue.add(start)\n                    visited[start] = true\n\n                    while (queue.isNotEmpty()) {\n                        val current = queue.poll()\n\n                        if (current == goal) {\n                            return constructPath(parent, start, goal)\n                        }\n\n                        for (neighbor in graph[current]) {\n                            if (!visited[neighbor]) {\n                                visited[neighbor] = true\n                                parent[neighbor] = current\n                                queue.add(neighbor)\n                            }\n                        }\n                    }\n                    return null\n                }\n\n                fun constructPath(parent: IntArray, start: Int, goal: Int): List<Int> {\n                    val path = mutableListOf<Int>()\n                    var at = goal\n                    while (at != -1) {\n                        path.add(at)\n                        at = parent[at]\n                    }\n                    path.reverse()\n                    return path\n                }\n\n                fun main() {\n                    val scanner = Scanner(System.`in`)\n                    val N = scanner.nextInt() \/\/ Number of vertices\n                    val M = scanner.nextInt() \/\/ Number of edges\n                    \n                    val graph = Array(N) { mutableListOf<Int>() }\n                    \n                    for (i in 0 until M) {\n                        val u = scanner.nextInt()\n                        val v = scanner.nextInt()\n                        graph[u].add(v)\n                        graph[v].add(u) \/\/ Undirected graph\n                    }\n\n                    val start = scanner.nextInt()\n                    val goal = scanner.nextInt()\n\n                    val path = bfs(graph, start, goal)\n                    if (path != null) {\n                        println(\"Path: ${path.joinToString(\" -> \")}\")\n                    } else {\n                        println(\"No path exists.\")\n                    }\n                }\n            <\/code>\n        <\/pre>\n<\/section>\n<section>\n<h2>5. Code Explanation<\/h2>\n<p>\n            The above code is an implementation of pathfinding based on BFS. <\/p>\n<ul>\n<li><strong>bfs(graph, start, goal)<\/strong>: Searches for a path from the start node to the goal node in the given graph.<br \/>\n                    It uses a queue to proceed with the search and records visited nodes in the visited array.<br \/>\n                    When it reaches the goal node, it returns the path based on parent information.\n                <\/li>\n<li><strong>constructPath(parent, start, goal)<\/strong>: Reconstructs the path from the goal node to the start node.<br \/>\n                    It traces the path using the parent information of each node and returns the array.\n                <\/li>\n<\/ul>\n<\/section>\n<section>\n<h2>6. Time Complexity Analysis<\/h2>\n<p>\n            The time complexity of the BFS algorithm is O(V + E), where V is the number of vertices and E is the number of edges.<br \/>\n            In this problem, there can be a maximum of 1000 vertices and 10000 edges, making it possible to solve efficiently.\n        <\/p>\n<\/section>\n<section>\n<h2>7. Conclusion<\/h2>\n<p>\n            In this course, we explored how to solve the pathfinding problem using Kotlin.<br \/>\n            We presented the most efficient way to search for paths in graphs using the BFS algorithm,<br \/>\n            and verified the process of solving the problem with actual code.<br \/>\n            Additionally, understanding the implementation of DFS and the differences from BFS can provide further insights.\n        <\/p>\n<p>\n            I hope this course will be of great help in preparing for coding tests and understanding algorithms. Thank you!\n        <\/p>\n<\/section>\n<footer>\n<p>\u00a9 2023 Kotlin Coding Test Course<\/p>\n<\/footer>\n<p><\/body><\/p>\n","protected":false},"excerpt":{"rendered":"<p>1. Introduction to the Problem The pathfinding problem is about finding a route between specific nodes (vertices) in a given graph. This problem is one of the fundamental and important problems for evaluating coding tests and algorithm problem-solving abilities. In this course, we will explain how to solve such problems using Kotlin. 2. Problem Definition &hellip; <a href=\"https:\/\/atmokpo.com\/w\/34948\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;Kotlin coding test course, pathfinding&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[106],"tags":[],"class_list":["post-34948","post","type-post","status-publish","format-standard","hentry","category----en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Kotlin coding test course, pathfinding - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/34948\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Kotlin coding test course, pathfinding - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"1. Introduction to the Problem The pathfinding problem is about finding a route between specific nodes (vertices) in a given graph. This problem is one of the fundamental and important problems for evaluating coding tests and algorithm problem-solving abilities. In this course, we will explain how to solve such problems using Kotlin. 2. 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