ums = Array(a.dropFirst()).map { $0 as! Int } kthLargest = KthLargest(k, nums) case "add": results.append(kthLargest.add(a[0] as! Int)) default: break } } return "[" + results.map(String.init).joined(separator: ", ") + "]" }17:T40c,import java.util.* // Design a class to find the kth largest element in a stream. // // Think about: How to efficiently maintain the kth largest? // Hint: Use a min-heap of size k. // // Example: // KthLargest(3, [4, 5, 8, 2]) // add(3) → 4 // add(5) → 5 // add(10) → 5 import java.util.PriorityQueue class KthLargest(val k: Int, nums: IntArray) { fun add(value: Int): Int { return 0 } } fun runKthLargestScript(commands: List, args: List>): String { var kthLargest: KthLargest? = null val results = mutableListOf() commands.forEachIndexed { i, cmd -> val a = args[i] when (cmd) { "KthLargest" -> { val k = (a[0] as Number).toInt() val nums = a.drop(1).map { (it as Number).toInt() }.toIntArray() kthLargest = KthLargest(k, nums) } "add" -> results.add(kthLargest!!.add((a[0] as Number).toInt())) } } return "[" + results.joinToString(", ") + "]" }18:T440,import java.util.* import java.util.PriorityQueue class KthLargest(val k: Int, nums: IntArray) { private val minHeap = PriorityQueue() init { for (num in nums) { add(num) } } fun add(value: Int): Int { if (minHeap.size < k) { minHeap.offer(value) } else if (value > minHeap.peek()) { minHeap.poll() minHeap.offer(value) } return minHeap.peek() } } fun runKthLargestScript(commands: List, args: List>): String { var kthLargest: KthLargest? = null val results = mutableListOf() commands.forEachIndexed { i, cmd -> val a = args[i] when (cm

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