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The entries in Figure 95 compare the performance of insertion sort and Shellsort, with various gap sequences These results were obtained on a reasonably fast machine We could easily conclude that Shellsort, even with the simplest gap sequence, provides a significant improvement over the insertion sort, at a cost of little additional code complexity A simple change to the gap sequence can further improve performance More improvement is possible (see in Exercise 924) Some of these improvements have theoretical backing, but no known sequence markedly improves the program shown in Figure 96 The performance of Shellsort is quite acceptable in practice, even for N in the tens of thousands The simplicity of the code makes it the algorithm of choice for sorting up to moderately large input It is also a fine example of a very simple algorithm with an extremely complex analysis



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A dataset from the main data source can be properly submitted to a Web service Secondary data sources can receive a DataSet object but do not track changes, so they cannot be properly submitted back to the Web service Using the main data source is a necessity if you want to submit your data back to the Web service for updating the database The main data source performs change tracking (an ADONET requirement) and serializes the dataset automatically upon submit





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Complete the method name with a meaningful addition based on the parameters that you are doing the select with Figure 215 shows this step for the example, where we are performing a SELECT with a Country column WHERE restriction, so I named the methods FillByCountry and GetByCountry If you are specifying one of the other types of queries that don't fill the data set, you will be given a text box to

Recall from Section 85 that recursion can be used to develop subquadratic algorithms Specifically, a divide-and-conquer algorithm in which two halfsize problems are solved recursively with an O ( N ) overhead results in an O(N log N ) algorithm Mergesort is such an algorithm It offers a better bound, at least theoretically, than the bounds claimed for Shellsort The mergesort algorithm involves three steps

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1 If the number of items to sort is 0 or 1, return 2 Recursively sort the first and second halves separately 3 Merge the two sorted halves into a sorted group

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To claim an O(N log N ) algorithm, we need only to show that the merging of two sorted groups can be performed in linear time In this section we show how to merge two input arrays, A and B, placing the result in a third array, C We then provide a simple implementation of mergesort The merge routine is the cornerstone of most external sorting algorithms, as demonstrated in Section 217

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