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Empirically verify Big-O efficiency assessments of selected sorting algorithms, and enhance the existing quicksort algorithm. Requirements 1. Write an application to empirically test the performance efficiency of at least two quadratic sort algorithms (O(N2) and two logarithmic algorithms (O(NlogN). You may use the algorithms' Java implementations presented in chapters 3 and 4 directly or group the quadratic and logarithmic algorithms into one or two classes and write a driver class to do the test. 2. Run the algorithms on arrays of different sizes and record the execution time. The array can be populated with random integers. For slower sorting algorithms (chapter 3), you may start with a size of 10,000, then 20,000, etc.. For fast sorting algorithms (chapter 4) you may try array sizes of 100,000, 200,000, and so on. For each algorithm, you will calculate the ratio C value of the assumed Big-O notation under different array sizes. The test will stop when C becomes relatively stable, e.g., the difference of 2 contiguous C values differs no more than 10%. 3. Summarize your testing process and result discovered as well as any observation and comment. 4. A critical point for quicksort algorithm is to select proper pivot values. Furthermore, when the dataset or partition size becomes small, e.g.,