// File: time_complexity.go // Created Time: 2022-12-13 // Author: msk397 (machangxinq@gmail.com) package chapter_computational_complexity /* Constant order */ func constant(n int) int { count := 0 size := 100000 for i := 0; i < size; i++ { count++ } return count } /* Linear order */ func linear(n int) int { count := 0 for i := 0; i < n; i++ { count++ } return count } /* Linear order (traversing array) */ func arrayTraversal(nums []int) int { count := 0 // Number of iterations is proportional to the array length for range nums { count++ } return count } /* Exponential order */ func quadratic(n int) int { count := 0 // Number of iterations is quadratically related to the data size n for i := 0; i < n; i++ { for j := 0; j < n; j++ { count++ } } return count } /* Quadratic order (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 rightmost end of that 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 unit operations } } } return count } /* Exponential order (loop implementation) */ func exponential(n int) int { count, base := 0, 1 // Cells divide into two every round, forming 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 order (recursive implementation) */ func expRecur(n int) int { if n == 1 { return 1 } return expRecur(n-1) + expRecur(n-1) + 1 } /* Logarithmic order (loop implementation) */ func logarithmic(n int) int { count := 0 for n > 1 { n = n / 2 count++ } return count } /* Logarithmic order (recursive implementation) */ func logRecur(n int) int { if n <= 1 { return 0 } return logRecur(n/2) + 1 } /* Linearithmic order */ 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 order (recursive implementation) */ func factorialRecur(n int) int { if n == 0 { return 1 } count := 0 // Split from 1 into n for i := 0; i < n; i++ { count += factorialRecur(n - 1) } return count }