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Data Structure Articles
Page 162 of 164
Anagram Pattern Search
Anagrams are basically all permutations of a given string or pattern. This pattern searching algorithm is slightly different. In this case, not only the exact pattern is searched, it searches all possible arrangements of the given pattern in the text.To solve this problem, we will divide the whole texts into several windows of length same as patterns. Then count on each character of the pattern is found and stored in an array. For each window, we also try to find the count array, then check whether they are matching or not.The time Complexity of Anagram Pattern Search Algorithm is O(n).Input ...
Read MoreBad Character Heuristic
The bad character heuristic method is one of the approaches of Boyer Moore Algorithm. Another approach is Good Suffix Heuristic. In this method we will try to find a bad character, that means a character of the main string, which is not matching with the pattern. When the mismatch has occurred, we will shift the entire pattern until the mismatch becomes a match, otherwise, pattern moves past the bad character.Here the time complexity is O(m/n) for best case and O(mn)for the worst case, where n is the length of the text and m is the length of the pattern.Input and ...
Read MorePrim's MST for Adjacency List Representation
It is similar to the previous algorithm. Here the only difference is, the Graph G(V, E) is represented by an adjacency list.Time complexity adjacency list representation is O(E log V).Input and OutputInput: The cost matrix: Output: Edge: A--B And Cost: 1 Edge: B--E And Cost: 2 Edge: A--C And Cost: 3 Edge: A--D And Cost: 4 Edge: E--F And Cost: 2 Edge: F--G And Cost: 3 Total Cost: 15Algorithmprims(g: Graph, start)Input − The graph g and the seed vertex named ‘start’Output − The Tree after adding edges.Begin create two set B, N add the start node in B ...
Read MoreDijkstra's Algorithm for Adjacency List Representation
There is a given graph G(V, E) with its adjacency list representation, and a source vertex is also provided. Dijkstra’s algorithm to find the minimum shortest path between source vertex to any other vertex of the graph G.To Solve this problem, we will use two lists. One is to store vertices which have been considered as the shortest path tree, and another will hold the vertices which are not considered yet. In each phase of the algorithm, we find the unconsidered vertex and which has the minimum distance from the source.Another list is used to hold the predecessor node. Using ...
Read MoreEfficient Huffman Coding for Sorted Input
In the previous Huffman code problem, the frequency was not sorted. If the frequency list is given in sorted order, the task of assigning code is being more efficient.In this problem, we will use two empty queues. Then create a leaf node for each unique character and insert it into the queue in increasing order of frequency.In this approach, the complexity of the algorithm is O(n).Input and OutputInput: Different letters and their frequency in sorted order Letters: {L, K, X, C, E, B, A, F} Frequency: {1, 1, 2, 2, 2, 2, 3, 4} Output: Codes for the letters L: ...
Read MoreMinimum Coin Change Problem
There is a list of coin C(c1, c2, ……Cn) is given and a value V is also given. Now the problem is to use the minimum number of coins to make the chance V.Note − Assume there are an infinite number of coins CIn this problem, we will consider a set of different coins C{1, 2, 5, 10} are given, There is an infinite number of coins of each type. To make change the requested value we will try to take the minimum number of coins of any type.As an example, for value 22 − we will choose {10, 10, 2}, ...
Read MoreMinimum Number of Platforms Problem
A list of arrival and departure time is given. Now the problem is to find the minimum number of platforms are required for the railway as no train waits.By sorting all timings in sorted order, we can find the solution easily, it will be easy to track when the train has arrived but not left the station.The time complexity of this problem is O(n Log n).Input and OutputInput: Lists of arrival time and departure time. Arrival: {900, 940, 950, 1100, 1500, 1800} Departure: {910, 1200, 1120, 1130, 1900, 2000} Output: Minimum Number of Platforms Required: 3AlgorithmminPlatform(arrival, departure, int n)Input − The ...
Read MoreCycle Sort
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 MorePigeonhole Sort
This is an example of the non-comparison sorting technique. It is used where the number of items and the range of possible key values is approximately the same.To perform this sort, we need to make some holes. The number of holes needed is decided by the range of numbers. In each hole, items are inserted. Finally deleted from the hole and stored into an array for sorted order.The complexity of Pigeon-Hole Sort TechniqueTime Complexity: O(n+2^k)Space Complexity: O(2^k)Input and OutputInput: The unsorted list: 802 630 20 745 52 300 612 932 78 187 Output: Data before Sorting: 802 630 20 745 ...
Read MoreComb Sort
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 ...
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