kleeio / time-complexity-of-sorting-algorithms

For Assignment 1 of CS245: Data Structures and Algorithm with Professor Brizan.

Time-Complexity-of-Sorting-Algorithms

For Assignment 1 of CS245: Data Structures and Algorithm with Professor Brizan.

Sort Interface is implemented by each sorting algorithm, which contains functions sort(<double_array>) and isSorted(<double_array>). By uncommenting the main method in Sort.java, the runtime result of the six sorting algorithms in milliseconds will be printed to console.

To run Sort.java: java Sort <desired-array-length>

Navigate to the Issues tab to read more about the time complexities of these sorting algorithms.

time-complexity-of-sorting-algorithms's Issues

Time Complexity of Merge Sort and In-Place Merge Sort

The graph below demonstrates the runtime of Merge sort versus an In-Place Merge sort, which is constant in space complexity. As expected, In-Place Merge sort which requires a merge function that is θ(n^2), whereas merge function in Merge sort is θ(log(n)), which resulted in a far higher runtime than Merge Sort has.

Time Complexity between Fundamental Sorting Algorithms

Using the sorting algorithms: Selection sort, Bubble sort, Insertion sort, Merge sort, and Quick sort, identical copies of arrays between lengths 100,000 and 1,000,000 to each sorting algorithm and the resulting runtime is printed. The below graph displays each sorting algorithms runtime efficiency in milliseconds for a given array length.

As shown in the graph, bubble sort had the longest running time of the five sorting algorithms, whereas quick sort had the shortest.