The Divide & Conquer Technique Used In the Analysis and Design of Algorithms
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 4
Abstract
Some sorting algorithms are simple and spontaneous, such as the bubble sort. Others, such as the quick sort are enormously complex, but produce superfast results. Some sorting algorithm work on less number of elements, some are suitable for floating point numbers, some are good for specific range, some sorting algorithms are used for huge number of data, and some are used if the list has repeated values. We sort data either in statistical order or lexicographical, sorting numerical value either in increasing order or decreasing order and alphabetical value. The complexity of algorithmic is generally written in a form known as Big – O (n) notation, where the O represents the complexity of the algorithm and a value n represents the size of the set the algorithm is run against. The two groups of sorting algorithms are O(), which includes the bubble, insertion, selection, and shell sorts, and O(n log n) which includes the heap, merge, and quick sort. Since the advancement in computing, much of the research is done to solve the sorting problem, perhaps due to the complexity of solving it efficiently despite its simple, familiar statement. It is always very difficult to say that one sorting algorithm is better than another. Performance of various sorting algorithms depends upon the data being sorted.
Authors and Affiliations
Shivangi Shandilya, Surekha Sangwan, Ritu Yadav
Keywords
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