Installation and Configuration
Programming Methodology

Best Practices and Code Optimization

In this exercise, you will learn **programming best practices** in Java and how to optimize your code for superior performance. You will discover how to write **clean** code that is easy to understand and maintain, and how to apply techniques to improve the efficiency of your programs. Through practical examples and exercises, you will become familiar with key concepts such as complexity reduction, algorithm optimization, and the proper use of Java language tools to create faster and more effective solutions.

Topic

Advanced Algorithms and Optimizations

Java Exercise

In this exercise, you will create a Java program that implements several programming and code optimization best practices. The goal is to write clean and efficient code, applying techniques such as complexity reduction, readability improvement, and algorithm optimization. You will work with common data structures and algorithms, ensuring that your code is easy to maintain, understand, and execute efficiently.

Instructions:

  1. Write a program that solves a common problem (e.g., sorting a list of items) using an efficient algorithm.
  2. Apply optimization techniques, such as improving memory usage and runtime.
  3. Refactor your code, ensuring it is readable, modular, and well-commented.
  4. Perform performance tests to compare the performance of your implementation before and after optimization.

This exercise will help you improve your skills in writing optimized and clean code, following development best practices for high-performance Java applications.


import java.util.Arrays;

public class OptimizedSorting {

    // Method to perform the QuickSort algorithm
    public static void quickSort(int[] array, int low, int high) {
        if (low < high) {
            int pivotIndex = partition(array, low, high);
            quickSort(array, low, pivotIndex - 1);  // Sort the left part
            quickSort(array, pivotIndex + 1, high);  // Sort the right part
        }
    }

    // Method to partition the array
    public static int partition(int[] array, int low, int high) {
        int pivot = array[high];  // The last element is the pivot
        int i = (low - 1);

        for (int j = low; j < high; j++) {
            // If the current element is smaller than the pivot
            if (array[j] < pivot) {
                i++;
                // Swap the elements
                int temp = array[i];
                array[i] = array[j];
                array[j] = temp;
            }
        }

        // Swap the pivot with the element at the correct position
        int temp = array[i + 1];
        array[i + 1] = array[high];
        array[high] = temp;

        return i + 1;
    }

    // Main method to execute the program
    public static void main(String[] args) {
        int[] numbers = { 12, 11, 13, 5, 6, 7 };

        System.out.println("Original array: " + Arrays.toString(numbers));

        // Call the optimized sorting algorithm
        long start = System.nanoTime();  // Measure start time
        quickSort(numbers, 0, numbers.length - 1);
        long end = System.nanoTime();  // Measure end time

        // Display the sorted array
        System.out.println("Sorted array: " + Arrays.toString(numbers));

        // Display execution time
        System.out.println("Execution time (in nanoseconds): " + (end - start));
    }
}

 Output:

Original array: [12, 11, 13, 5, 6, 7]  
Sorted array: [5, 6, 7, 11, 12, 13]  
Execution time (in nanoseconds): 21423

This program implements the **QuickSort** algorithm, one of the best solutions for sorting arrays due to its runtime efficiency in most cases. By optimizing the code, it becomes more efficient in both memory and time, and it is refactored to be modular and easy to understand.


 Share this JAVA exercise