Which statement describes what happens if multiple users make changes simultaneously to a presentation when coauthoring?

Computers and Technology

1 answer:

Marina CMI [18]3 years ago

8 0

Answer:

Explanation:

Co-authoring in PowerPoint is sharing a presentation and allowing your colleagues to work on it at the same time. This option of co-authoring is available when you share or save your file on OneDrive or SharePoint.

The perk of co-authoring a presentation is that PowerPoint keeps a record of all edits under the name of the author. This keeps the conflicts away.

Therefore, the correct answer is option 3.

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Sorting is a technique of arranging the elements in a specific order e.g. numerical sorting, ordering students according to their exam score. This order can be ascending or descending or alphabetical order. Contrary to search it returns the data structure e.g. an array in which the elements of array are sorted in a particular order. Sorting algorithms are used to sort elements in a data structure. Some common examples of sorting algorithms are Bubble Sort, Insertion Sort, Selection Sort, Merge Sort, Quick Sort, Heap Sort etc. JAVA uses Array.Sort() built-in function for sorting an array. By default it sorts the input array in ascending order.

Selection Sort: It is a sorting technique which divides an array into two subarrays. One subarray in the left is sorted and the other one at right is unsorted. This is an in-place algorithm. It is not a good option for large data. Initially the sorted part is empty and all elements are placed in unsorted array. First the element which is the smallest in the unsorted array is selected and swapped with the leftmost array element and becomes part of the sorted array. In each iteration the smallest element from the unsorted array is selected and moved to sorted part of the array.The worst case time complexity of this algorithm is O(n)^2 as we have to find the smallest for every element in the array.

Merge Sort: It is a comparison based algorithm. It works on divide and conquer technique. It uses recursion approach for sorting. This means it breaks the problem(lets say array list to be sorted) into sub problems (smaller parts) and then solves (in this case sorts) each sub problem in a recursive manner. At the end it merges the solutions (hence the merged sorted array). Although selection sort works faster when data set is small merge sort outperforms it for larger data sets. Merge sort is a stable algorithm and works best for linked lists. Its not an in place algorithm. Time complexity of merge sort is O(n*log n) for best, average and worst cases because it always divides the array in two parts and takes linear time to merge these part. O(n(logn)) time complexity makes it better,more efficient and faster to sort large data sets.

Big Oh O notation is an asymptotic annotation written as O(n) which is a mathematical way to represent the upper bound of the running time of algorithm (sorting algorithm in this case). It computes the worst case time complexity. Worst case time complexity means that the longest amount of time or maximum number of operations that will be required for a sorting algorithm to complete. The time complexity mostly gets affected as the size of the input varies.
For example lets find out the worst-case time complexity of Bubble Sort for a list of n elements. Worst case is when the array is reversed sorted. At first iteration it would make n-1 comparisons. At iteration 1, for n-2 times and so total comparison will be O(n^)2. So the time to run program is proportional to the square of the input size.

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