Simplify kotlin code and improve code readability (#1198)

* Add kotlin code block for chapter_hashing

* Add kotlin code block for chapter_heap.

* Add kotlin code block for chapter_stack_and_queue and chapter_tree

* fix indentation

* Update binary_tree.md

* style(kotlin): simplify code and improve readability.

* simplify kt code for chapter_computational_complexity.

* style(kotlin): replace ArrayList with MutableList.

* Update subset_sum_i.kt

Use kotlin api instead of java.

* Update subset_sum_ii.kt

use kotlin api instead of java

* style(kotlin): replace ArrayList with mutablelist.

---------

Co-authored-by: Yudong Jin <krahets@163.com>

codes/kotlin/chapter_computational_complexity/space_complexity.kt

@@ -60,9 +60,9 @@ fun linearRecur(n: Int) {
 /* 平方阶 */
 fun quadratic(n: Int) {
     // 矩阵占用 O(n^2) 空间
-    val numMatrix: Array<Array<Int>?> = arrayOfNulls(n)
+    val numMatrix = arrayOfNulls<Array<Int>?>(n)
     // 二维列表占用 O(n^2) 空间
-    val numList: MutableList<MutableList<Int>> = arrayListOf()
+    val numList = mutableListOf<MutableList<Int>>()
     for (i in 0..<n) {
         val tmp = mutableListOf<Int>()
         for (j in 0..<n) {
@@ -104,6 +104,6 @@ fun main() {
     quadratic(n)
     quadraticRecur(n)
     // 指数阶
-    val root: TreeNode? = buildTree(n)
+    val root = buildTree(n)
     printTree(root)
 }

codes/kotlin/chapter_computational_complexity/time_complexity.kt

@@ -9,7 +9,7 @@ package chapter_computational_complexity.time_complexity
 /* 常数阶 */
 fun constant(n: Int): Int {
     var count = 0
-    val size = 10_0000
+    val size = 100000
     for (i in 0..<size)
         count++
     return count
@@ -48,7 +48,7 @@ fun quadratic(n: Int): Int {
 
 /* 平方阶（冒泡排序） */
 fun bubbleSort(nums: IntArray): Int {
-    var count = 0
+    var count = 0 // 计数器
     // 外循环：未排序区间为 [0, i]
     for (i in nums.size - 1 downTo 1) {
         // 内循环：将未排序区间 [0, i] 中的最大元素交换至该区间的最右端
@@ -109,7 +109,7 @@ fun linearLogRecur(n: Int): Int {
     if (n <= 1)
         return 1
     var count = linearLogRecur(n / 2) + linearLogRecur(n / 2)
-    for (i in 0..<n.toInt()) {
+    for (i in 0..<n) {
         count++
     }
     return count
@@ -133,7 +133,7 @@ fun main() {
     val n = 8
     println("输入数据大小 n = $n")
 
-    var count: Int = constant(n)
+    var count = constant(n)
     println("常数阶的操作数量 = $count")
 
     count = linear(n)
@@ -144,7 +144,8 @@ fun main() {
     count = quadratic(n)
     println("平方阶的操作数量 = $count")
     val nums = IntArray(n)
-    for (i in 0..<n) nums[i] = n - i // [n,n-1,...,2,1]
+    for (i in 0..<n)
+        nums[i] = n - i // [n,n-1,...,2,1]
     count = bubbleSort(nums)
     println("平方阶（冒泡排序）的操作数量 = $count")
 

codes/kotlin/chapter_computational_complexity/worst_best_time_complexity.kt

@@ -13,10 +13,9 @@ fun randomNumbers(n: Int): Array<Int?> {
     for (i in 0..<n) {
         nums[i] = i + 1
     }
-    // 随机打乱数组元素
     val mutableList = nums.toMutableList()
+    // 随机打乱数组元素
     mutableList.shuffle()
-    // Integer[] -> int[]
     val res = arrayOfNulls<Int>(n)
     for (i in 0..<n) {
         res[i] = mutableList[i]
@@ -39,8 +38,8 @@ fun findOne(nums: Array<Int?>): Int {
 fun main() {
     for (i in 0..9) {
         val n = 100
-        val nums: Array<Int?> = randomNumbers(n)
-        val index: Int = findOne(nums)
+        val nums = randomNumbers(n)
+        val index = findOne(nums)
         println("\n数组 [ 1, 2, ..., n ] 被打乱后 = ${nums.contentToString()}")
         println("数字 1 的索引为 $index")
     }