Found 1906 Articles for Data Structure

This sorting technique is similar with the card sorting technique, in other words, we sort cards using insertion sort mechanism. For this technique, we pick up one element from the data set and shift the data elements to make a place to insert back the picked up an element into the data set.The complexity of the Insertion Sort TechniqueTime Complexity: O(n) for best case, O(n^2) for average and worst caseSpace Complexity: O(1)Input and OutputInput: The unsorted list: 9 45 23 71 80 55 Output: Array before Sorting: 9 45 23 71 80 55 Array after Sorting: 9 23 45 55 ... Read More

Heap sort is performed on the heap data structure. We know that heap is a complete binary tree. Heap tree can be of two types. Min-heap or max heap. For min heap the root element is minimum and for max heap the root is maximum. After forming a heap, we can delete an element from the root and send the last element to the root. After these swapping procedure, we need to re-heap the whole array. By deleting elements from root we can sort the whole array.The complexity of Heap Sort TechniqueTime Complexity: O(n log n)Space Complexity: O(1)Input and OutputInput: A ... Read More

Cycle Sort is an in-place sorting algorithm. It is also a comparison based sort and efficient for any other in-place sorting technique. It finds the minimum number of memory write to perform the sorting tasks.The complexity of Cycle Sort TechniqueTime Complexity: O(n^2)Space Complexity: O(1)Input and OutputInput: A list of unsorted data: 23 63 98 74 20 14 36 45 99 78 Output: Array before Sorting: 23 63 98 74 20 14 36 45 99 78 Array after Sorting: 14 20 23 36 45 63 74 78 98 99AlgorithmcycleSort(array, size)Input − An array of data, and the total number in the ... Read More

Counting sort is a stable sorting technique, which is used to sort objects according to the keys that are small numbers. It counts the number of keys whose key values are same. This sorting technique is effective when the difference between different keys are not so big, otherwise, it can increase the space complexity.The complexity of counting Sort TechniqueTime Complexity: O(n+r)Space Complexity: O(n+r)Input and OutputInput: A list of unsorted data: 2 5 6 2 3 10 3 6 7 8 Output: Array before Sorting: 2 5 6 2 3 10 3 6 7 8 Array after Sorting: 2 2 3 ... Read More

The basic idea of comb sort and the bubble sort is same. In other words, comb sort is an improvement on the bubble sort. In the bubble sorting technique, the items are compared with the next item in each phase. But for the comb sort, the items are sorted in a specific gap. After completing each phase, the gap is decreased. The decreasing factor or the shrink factor for this sort is 1.3. It means that after completing each phase the gap is divided by 1.3.The complexity of Comb Sort TechniqueTime Complexity: O(n log n) for the best case. O(n^2/2^p) (p ... Read More

In the Bucket Sorting technique, the data items are distributed in a set of buckets. Each bucket can hold a similar type of data. After distributing, each bucket is sorted using another sorting algorithm. After that, all elements are gathered on the main list to get the sorted form.The complexity of the Bucket Sort TechniqueTime Complexity: O(n + k) for best case and average case and O(n^2) for the worst case.Space Complexity: O(nk) for worst caseInput and OutputInput: A list of unsorted data: 0.25 0.36 0.58 0.41 0.29 0.22 0.45 0.79 0.01 0.69 Array before Sorting: 0.25 0.36 0.58 0.41 ... Read More