A Comparative Analysis of Sorting Algorithm

Data structure is one of the most important tools for organizing a large data. It is seen as a method to systematically manage data in a computer that leads towards efficiently implementing different data type to make it suitable for various application (Chhjed, 2014). In addition, data structure is considered as a key and essential factor for designing algorithm with good effectiveness and efficiency. Algorithms have been developed such as Merge sort, Insertion sort, Selection Sort and Quick sort, meanwhile, several efforts have been taken to improve techniques like merge sort, bubble sort, Insertion sort, selection sort, each of them has a different mechanism to reorder elements which increase the performance and efficiency of the practical application and reduce the time complexity of each one. It is worth nothing that when various sorting algorithm are been checked there are few parameters that must be checked such as complexity and execution time. In general, the complexity of an algorithm is generally written in the form of O(n) notation, where O represent the complexity of the algorithm and the value it represents the number of element operation performed by the algorithm (Jadoom, 2013). So far, several researchers have focused on how to described and improve the algorithm and ignoring data structure, while the data structures significantly affect the performance and efficiency of an algorithm. Hence, this study analyzes the Quick sort, Merge sort, Selection sort, Insertion sort, Bucket sort, Bubble Sort, and Radix sort algorithm and their behavior on large data set using the total number of students in the School of Technology Federal Polytechnic Idah. To accomplished the major tasks, proposed methodology comprises of three phases which are Introduction of the sorting algorithm, implementation and its performance