Merge branch 'DaleStudy:main' into main

Author: EcoFriendlyAppleSu

contains-duplicate/JisooPyo.kt

@@ -0,0 +1,38 @@
+package leetcode_study
+
+import io.kotest.matchers.shouldBe
+import org.junit.jupiter.api.Test
+
+/**
+ * Leetcode
+ * 217. Contains Duplicate
+ * Easy
+ */
+class ContainsDuplicate {
+    /**
+     * Runtime: 17 ms(Beats: 80.99 %)
+     * Time Complexity: O(n)
+     *   - 배열 순회
+     *
+     * Memory: 50.63 MB(Beats: 70.32 %)
+     * Space Complexity: O(n)
+     *   - HashSet에 최악의 경우 배열 원소 모두 저장
+     */
+    fun containsDuplicate(nums: IntArray): Boolean {
+        val set = hashSetOf<Int>()
+        for (i in nums) {
+            if (set.contains(i)) {
+                return true
+            }
+            set.add(i)
+        }
+        return false
+    }
+
+    @Test
+    fun test() {
+        containsDuplicate(intArrayOf(1, 2, 3, 1)) shouldBe true
+        containsDuplicate(intArrayOf(1, 2, 3, 4)) shouldBe false
+        containsDuplicate(intArrayOf(1, 1, 1, 3, 3, 4, 3, 2, 4, 2)) shouldBe true
+    }
+}

contains-duplicate/jeldo.py

@@ -0,0 +1,4 @@
+class Solution:
+    # O(n)
+    def containsDuplicate(self, nums: list[int]) -> bool:
+        return len(nums) != len(set(nums))  # O(n)

house-robber/JisooPyo.kt

@@ -0,0 +1,74 @@
+package leetcode_study
+
+import io.kotest.matchers.shouldBe
+import org.junit.jupiter.api.Test
+import kotlin.math.max
+
+/**
+ * Leetcode
+ * 198. House Robber
+ * Medium
+ *
+ * 사용된 알고리즘: Dynamic Programming
+ *
+ * i번째 집에서 얻을 수 있는 최대 금액은 다음 두 가지 중 큰 값입니다.
+ *   - (i-2)번째 집까지의 최대 금액 + 현재 집의 금액
+ *   - (i-1)번째 집까지의 최대 금액
+ */
+class HouseRobber {
+    /**
+     * Runtime: 0 ms(Beats: 100.00 %)
+     * Time Complexity: O(n)
+     *
+     * Memory: 34.65 MB(Beats: 40.50 %)
+     * Space Complexity: O(n)
+     */
+    fun rob(nums: IntArray): Int {
+        if (nums.size == 1) {
+            return nums[0]
+        }
+        if (nums.size == 2) {
+            return max(nums[0], nums[1])
+        }
+        val dp = IntArray(nums.size)
+        dp[0] = nums[0]
+        dp[1] = max(nums[0], nums[1])
+        for (i in 2 until nums.size) {
+            dp[i] = max(dp[i - 2] + nums[i], dp[i - 1])
+        }
+        return dp[nums.size - 1]
+    }
+
+    /**
+     * 공간 복잡도를 개선
+     * Runtime: 0 ms(Beats: 100.00 %)
+     * Time Complexity: O(n)
+     *
+     * Memory: 34.95 MB(Beats: 36.98 %)
+     * Space Complexity: O(1)
+     */
+    fun rob2(nums: IntArray): Int {
+        if (nums.size == 1) return nums[0]
+        if (nums.size == 2) return max(nums[0], nums[1])
+
+        var twoBack = nums[0]
+        var oneBack = max(nums[0], nums[1])
+        var current = oneBack
+
+        for (i in 2 until nums.size) {
+            current = max(twoBack + nums[i], oneBack)
+            twoBack = oneBack
+            oneBack = current
+        }
+
+        return current
+    }
+
+    @Test
+    fun test() {
+        rob(intArrayOf(1, 2, 3, 1)) shouldBe 4
+        rob(intArrayOf(2, 7, 9, 3, 1)) shouldBe 12
+        rob2(intArrayOf(1, 2, 3, 1)) shouldBe 4
+        rob2(intArrayOf(2, 7, 9, 3, 1)) shouldBe 12
+    }
+}

house-robber/jeldo.py

@@ -0,0 +1,9 @@
+class Solution:
+    # O(n)
+    def rob(self, nums: list[int]) -> int:
+        if len(nums) <= 2:
+            return max(nums)
+        nums[2] += nums[0]
+        for i in range(3, len(nums)):
+            nums[i] += max(nums[i-3], nums[i-2])
+        return max(nums[-1], nums[-2])

longest-consecutive-sequence/JisooPyo.kt

@@ -0,0 +1,81 @@
+package leetcode_study
+
+import io.kotest.matchers.shouldBe
+import org.junit.jupiter.api.Test
+import kotlin.math.max
+
+/**
+ * Leetcode
+ * 128. Longest Consecutive Sequence
+ * Medium
+ */
+class LongestConsecutiveSequence {
+    /**
+     * Runtime: 58 ms(Beats: 79.06 %)
+     * Time Complexity: O(n)
+     *   - while 루프의 총 반복 횟수는 n을 넘을 수 없다.
+     *
+     * Memory: 62.65 MB(Beats: 10.48 %)
+     * Space Complexity: O(n)
+     */
+    fun longestConsecutive(nums: IntArray): Int {
+        val numsSet: MutableSet<Int> = nums.toHashSet()
+        val startSet: MutableSet<Int> = hashSetOf()
+
+        // 수열의 시작점이 될 수 있는 수를 찾는다.
+        for (num in numsSet) {
+            if (!numsSet.contains(num - 1)) {
+                startSet.add(num)
+            }
+        }
+        var answer = 0
+        for (start in startSet) {
+            // 수열의 시작점부터 몇 개 까지 numsSet에 있는지 확인한다.
+            var count = 0
+            var first = start
+            while (numsSet.contains(first)) {
+                first++
+                count++
+            }
+            // 최대 수열의 개수를 업데이트한다.
+            answer = max(answer, count)
+        }
+        return answer
+    }
+
+    /**
+     * 위 풀이에서 startSet을 제거하여 공간적으로 효율적인 풀이
+     * Runtime: 63 ms(Beats: 65.70 %)
+     * Time Complexity: O(n)
+     *
+     * Memory: 58.47 MB(Beats: 70.81 %)
+     * Space Complexity: O(n)
+     */
+    fun longestConsecutive2(nums: IntArray): Int {
+        val numsSet = nums.toHashSet()
+        var maxLength = 0
+
+        for (num in numsSet) {
+            if (!numsSet.contains(num - 1)) {
+                var currentNum = num
+                var currentLength = 0
+
+                while (numsSet.contains(currentNum)) {
+                    currentLength++
+                    currentNum++
+                }
+                maxLength = max(maxLength, currentLength)
+            }
+        }
+        return maxLength
+    }
+
+    @Test
+    fun test() {
+        longestConsecutive(intArrayOf(100, 4, 200, 1, 3, 2)) shouldBe 4
+        longestConsecutive(intArrayOf(0, 3, 7, 2, 5, 8, 4, 6, 0, 1)) shouldBe 9
+
+        longestConsecutive2(intArrayOf(100, 4, 200, 1, 3, 2)) shouldBe 4
+        longestConsecutive2(intArrayOf(0, 3, 7, 2, 5, 8, 4, 6, 0, 1)) shouldBe 9
+    }
+}

longest-consecutive-sequence/jeldo.py

@@ -0,0 +1,13 @@
+class Solution:
+    # O(n)
+    def longestConsecutive(self, nums: list[int]) -> int:
+        max_length = 0
+        nums_set = set(nums)
+        for n in nums_set:
+            if n - 1 not in nums_set:
+                length = 0
+                while n + length in nums_set:
+                    length += 1
+                    max_length = max(max_length, length)
+
+        return max_length

top-k-frequent-elements/JisooPyo.kt

@@ -0,0 +1,76 @@
+package leetcode_study
+
+import io.kotest.matchers.shouldBe
+import org.junit.jupiter.api.Test
+import java.util.*
+
+/**
+ * Leetcode
+ * 347. Top K Frequent Elements
+ * Medium
+ */
+class TopKFrequentElements {
+    /**
+     * Runtime: 30 ms(Beats: 68.62 %)
+     * Time Complexity: O(n log n)
+     *   - list 정렬
+     *
+     * Memory: 42.20 MB(Beats: 58.82 %)
+     * Space Complexity: O(n)
+     */
+    fun topKFrequent(nums: IntArray, k: Int): IntArray {
+        val countMap: MutableMap<Int, Int> = HashMap()
+
+        for (num in nums) {
+            countMap[num] = countMap.getOrDefault(num, 0) + 1
+        }
+
+        val list = mutableListOf<Node>()
+        for (key in countMap.keys) {
+            list.add(Node(key, countMap[key]!!))
+        }
+        list.sortDescending()
+
+        val answer = IntArray(k)
+        for (i in 0 until k) {
+            answer[i] = list[i].value
+        }
+        return answer
+    }
+
+    /**
+     * 개선된 버전: 우선순위 큐를 사용
+     *
+     * Runtime: 19 ms(Beats: 96.30 %)
+     * Time Complexity: O(n log n)
+     *
+     * Memory: 44.83 MB(Beats: 18.35 %)
+     * Space Complexity: O(n)
+     */
+    fun topKFrequent2(nums: IntArray, k: Int): IntArray {
+        val countMap = nums.groupBy { it }
+            .mapValues { it.value.size }
+
+        val pq = PriorityQueue<Node>(compareByDescending { it.count })
+        countMap.forEach { (num, count) ->
+            pq.offer(Node(num, count))
+        }
+
+        return IntArray(k) { pq.poll().value }
+    }
+
+    data class Node(var value: Int, var count: Int) : Comparable<Node> {
+        override fun compareTo(other: Node): Int {
+            return this.count.compareTo(other.count)
+        }
+    }
+
+    @Test
+    fun test() {
+        topKFrequent(intArrayOf(1, 1, 1, 2, 2, 3), 2) shouldBe intArrayOf(1, 2)
+        topKFrequent(intArrayOf(1), 1) shouldBe intArrayOf(1)
+
+        topKFrequent2(intArrayOf(1, 1, 1, 2, 2, 3), 2) shouldBe intArrayOf(1, 2)
+        topKFrequent2(intArrayOf(1), 1) shouldBe intArrayOf(1)
+    }
+}

top-k-frequent-elements/jeldo.py

@@ -0,0 +1,9 @@
+from collections import Counter
+import heapq
+
+
+class Solution:
+    # O(nlogn)
+    def topKFrequent(self, nums: list[int], k: int) -> list[int]:
+        ls = [(key, value) for key, value in Counter(nums).items()]  # O(n)
+        return [key for _, key in heapq.nlargest(n=k, iterable=ls)]  # O(nlogn)