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168 lines
4.1 KiB
Kotlin
168 lines
4.1 KiB
Kotlin
/**
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* File: time_complexity.kt
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* Created Time: 2024-01-25
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* Author: curtishd (1023632660@qq.com)
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*/
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package chapter_computational_complexity.time_complexity
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/* Constant order */
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fun constant(n: Int): Int {
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var count = 0
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val size = 100000
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for (i in 0..<size)
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count++
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return count
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}
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/* Linear order */
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fun linear(n: Int): Int {
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var count = 0
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for (i in 0..<n)
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count++
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return count
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}
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/* Linear order (traversing array) */
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fun arrayTraversal(nums: IntArray): Int {
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var count = 0
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// Number of iterations is proportional to the array length
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for (num in nums) {
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count++
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}
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return count
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}
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/* Exponential order */
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fun quadratic(n: Int): Int {
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var count = 0
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// Number of iterations is quadratically related to the data size n
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for (i in 0..<n) {
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for (j in 0..<n) {
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count++
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}
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}
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return count
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}
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/* Quadratic order (bubble sort) */
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fun bubbleSort(nums: IntArray): Int {
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var count = 0 // Counter
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// Outer loop: unsorted range is [0, i]
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for (i in nums.size - 1 downTo 1) {
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// Inner loop: swap the largest element in the unsorted range [0, i] to the rightmost end of that range
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for (j in 0..<i) {
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if (nums[j] > nums[j + 1]) {
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// Swap nums[j] and nums[j + 1]
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val temp = nums[j]
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nums[j] = nums[j + 1]
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nums[j + 1] = temp
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count += 3 // Element swap includes 3 unit operations
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}
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}
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}
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return count
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}
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/* Exponential order (loop implementation) */
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fun exponential(n: Int): Int {
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var count = 0
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var base = 1
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// Cells divide into two every round, forming sequence 1, 2, 4, 8, ..., 2^(n-1)
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for (i in 0..<n) {
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for (j in 0..<base) {
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count++
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}
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base *= 2
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}
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// count = 1 + 2 + 4 + 8 + .. + 2^(n-1) = 2^n - 1
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return count
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}
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/* Exponential order (recursive implementation) */
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fun expRecur(n: Int): Int {
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if (n == 1) {
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return 1
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}
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return expRecur(n - 1) + expRecur(n - 1) + 1
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}
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/* Logarithmic order (loop implementation) */
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fun logarithmic(n: Int): Int {
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var n1 = n
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var count = 0
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while (n1 > 1) {
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n1 /= 2
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count++
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}
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return count
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}
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/* Logarithmic order (recursive implementation) */
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fun logRecur(n: Int): Int {
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if (n <= 1)
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return 0
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return logRecur(n / 2) + 1
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}
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/* Linearithmic order */
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fun linearLogRecur(n: Int): Int {
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if (n <= 1)
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return 1
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var count = linearLogRecur(n / 2) + linearLogRecur(n / 2)
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for (i in 0..<n) {
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count++
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}
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return count
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}
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/* Factorial order (recursive implementation) */
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fun factorialRecur(n: Int): Int {
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if (n == 0)
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return 1
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var count = 0
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// Split from 1 into n
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for (i in 0..<n) {
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count += factorialRecur(n - 1)
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}
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return count
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}
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/* Driver Code */
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fun main() {
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// You can modify n to run and observe the trend of the number of operations for various complexities
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val n = 8
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println("Input data size n = $n")
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var count = constant(n)
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println("Constant-time operations count = $count")
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count = linear(n)
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println("Linear-time operations count = $count")
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count = arrayTraversal(IntArray(n))
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println("Linear-time (array traversal) operations count = $count")
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count = quadratic(n)
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println("Quadratic-time operations count = $count")
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val nums = IntArray(n)
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for (i in 0..<n)
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nums[i] = n - i // [n,n-1,...,2,1]
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count = bubbleSort(nums)
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println("Quadratic-time (bubble sort) operations count = $count")
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count = exponential(n)
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println("Exponential-time (iterative) operations count = $count")
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count = expRecur(n)
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println("Exponential-time (recursive) operations count = $count")
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count = logarithmic(n)
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println("Logarithmic-time (iterative) operations count = $count")
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count = logRecur(n)
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println("Logarithmic-time (recursive) operations count = $count")
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count = linearLogRecur(n)
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println("Linearithmic-time (recursive) operations count = $count")
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count = factorialRecur(n)
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println("Factorial-time (recursive) operations count = $count")
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} |