hello-algo/en/codes/go/chapter_computational_complexity/time_complexity.go

131 lines
2.5 KiB
Go

// File: time_complexity.go
// Created Time: 2022-12-13
// Author: msk397 (machangxinq@gmail.com)
package chapter_computational_complexity
/* Constant complexity */
func constant(n int) int {
count := 0
size := 100000
for i := 0; i < size; i++ {
count++
}
return count
}
/* Linear complexity */
func linear(n int) int {
count := 0
for i := 0; i < n; i++ {
count++
}
return count
}
/* Linear complexity (traversing an array) */
func arrayTraversal(nums []int) int {
count := 0
// Loop count is proportional to the length of the array
for range nums {
count++
}
return count
}
/* Quadratic complexity */
func quadratic(n int) int {
count := 0
// Loop count is squared in relation to the data size n
for i := 0; i < n; i++ {
for j := 0; j < n; j++ {
count++
}
}
return count
}
/* Quadratic complexity (bubble sort) */
func bubbleSort(nums []int) int {
count := 0 // Counter
// Outer loop: unsorted range is [0, i]
for i := len(nums) - 1; i > 0; i-- {
// Inner loop: swap the largest element in the unsorted range [0, i] to the right end of the range
for j := 0; j < i; j++ {
if nums[j] > nums[j+1] {
// Swap nums[j] and nums[j + 1]
tmp := nums[j]
nums[j] = nums[j+1]
nums[j+1] = tmp
count += 3 // Element swap includes 3 individual operations
}
}
}
return count
}
/* Exponential complexity (loop implementation)*/
func exponential(n int) int {
count, base := 0, 1
// Cells split into two every round, forming the sequence 1, 2, 4, 8, ..., 2^(n-1)
for i := 0; i < n; i++ {
for j := 0; j < base; j++ {
count++
}
base *= 2
}
// count = 1 + 2 + 4 + 8 + .. + 2^(n-1) = 2^n - 1
return count
}
/* Exponential complexity (recursive implementation)*/
func expRecur(n int) int {
if n == 1 {
return 1
}
return expRecur(n-1) + expRecur(n-1) + 1
}
/* Logarithmic complexity (loop implementation)*/
func logarithmic(n int) int {
count := 0
for n > 1 {
n = n / 2
count++
}
return count
}
/* Logarithmic complexity (recursive implementation)*/
func logRecur(n int) int {
if n <= 1 {
return 0
}
return logRecur(n/2) + 1
}
/* Linear logarithmic complexity */
func linearLogRecur(n int) int {
if n <= 1 {
return 1
}
count := linearLogRecur(n/2) + linearLogRecur(n/2)
for i := 0; i < n; i++ {
count++
}
return count
}
/* Factorial complexity (recursive implementation) */
func factorialRecur(n int) int {
if n == 0 {
return 1
}
count := 0
// From 1 split into n
for i := 0; i < n; i++ {
count += factorialRecur(n - 1)
}
return count
}