hello-algo/en/codes/java/chapter_computational_complexity/time_complexity.java
Yudong Jin 1c0f350ad6
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Java

/**
* File: time_complexity.java
* Created Time: 2022-11-25
* Author: krahets (krahets@163.com)
*/
package chapter_computational_complexity;
public class time_complexity {
/* Constant complexity */
static int constant(int n) {
int count = 0;
int size = 100000;
for (int i = 0; i < size; i++)
count++;
return count;
}
/* Linear complexity */
static int linear(int n) {
int count = 0;
for (int i = 0; i < n; i++)
count++;
return count;
}
/* Linear complexity (traversing an array) */
static int arrayTraversal(int[] nums) {
int count = 0;
// Loop count is proportional to the length of the array
for (int num : nums) {
count++;
}
return count;
}
/* Quadratic complexity */
static int quadratic(int n) {
int count = 0;
// Loop count is squared in relation to the data size n
for (int i = 0; i < n; i++) {
for (int j = 0; j < n; j++) {
count++;
}
}
return count;
}
/* Quadratic complexity (bubble sort) */
static int bubbleSort(int[] nums) {
int count = 0; // Counter
// Outer loop: unsorted range is [0, i]
for (int i = nums.length - 1; i > 0; i--) {
// Inner loop: swap the largest element in the unsorted range [0, i] to the right end of the range
for (int j = 0; j < i; j++) {
if (nums[j] > nums[j + 1]) {
// Swap nums[j] and nums[j + 1]
int 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) */
static int exponential(int n) {
int count = 0, base = 1;
// Cells split into two every round, forming the sequence 1, 2, 4, 8, ..., 2^(n-1)
for (int i = 0; i < n; i++) {
for (int 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) */
static int expRecur(int n) {
if (n == 1)
return 1;
return expRecur(n - 1) + expRecur(n - 1) + 1;
}
/* Logarithmic complexity (loop implementation) */
static int logarithmic(int n) {
int count = 0;
while (n > 1) {
n = n / 2;
count++;
}
return count;
}
/* Logarithmic complexity (recursive implementation) */
static int logRecur(int n) {
if (n <= 1)
return 0;
return logRecur(n / 2) + 1;
}
/* Linear logarithmic complexity */
static int linearLogRecur(int n) {
if (n <= 1)
return 1;
int count = linearLogRecur(n / 2) + linearLogRecur(n / 2);
for (int i = 0; i < n; i++) {
count++;
}
return count;
}
/* Factorial complexity (recursive implementation) */
static int factorialRecur(int n) {
if (n == 0)
return 1;
int count = 0;
// From 1 split into n
for (int i = 0; i < n; i++) {
count += factorialRecur(n - 1);
}
return count;
}
/* Driver Code */
public static void main(String[] args) {
// Can modify n to experience the trend of operation count changes under various complexities
int n = 8;
System.out.println("Input data size n = " + n);
int count = constant(n);
System.out.println("Number of constant complexity operations = " + count);
count = linear(n);
System.out.println("Number of linear complexity operations = " + count);
count = arrayTraversal(new int[n]);
System.out.println("Number of linear complexity operations (traversing the array) = " + count);
count = quadratic(n);
System.out.println("Number of quadratic order operations = " + count);
int[] nums = new int[n];
for (int i = 0; i < n; i++)
nums[i] = n - i; // [n,n-1,...,2,1]
count = bubbleSort(nums);
System.out.println("Number of quadratic order operations (bubble sort) = " + count);
count = exponential(n);
System.out.println("Number of exponential complexity operations (implemented by loop) = " + count);
count = expRecur(n);
System.out.println("Number of exponential complexity operations (implemented by recursion) = " + count);
count = logarithmic(n);
System.out.println("Number of logarithmic complexity operations (implemented by loop) = " + count);
count = logRecur(n);
System.out.println("Number of logarithmic complexity operations (implemented by recursion) = " + count);
count = linearLogRecur(n);
System.out.println("Number of linear logarithmic complexity operations (implemented by recursion) = " + count);
count = factorialRecur(n);
System.out.println("Number of factorial complexity operations (implemented by recursion) = " + count);
}
}