{"product_id":"new-full-course-guide-cmsc-451-project-study-solution-download_id_451qq1omdv4os_exiuznw451xx","title":"(New Full Course Guide) CMSC 451 Project Study Solution Download","description":"\u003ch1\u003eCMSC451 Project Study Solution Download\u003c\/h1\u003e\n\u003ch2\u003e\n\u003cb\u003e\u003cspan\u003eCMSC451 Project 2 Sorting Algorithms Analytics\u003c\/span\u003e\u003c\/b\u003e\u003cb\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/b\u003e\n\u003c\/h2\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eProject 2 involves an analysis of the results that you obtained in first project. You are to submit a\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003epaper, written with Microsoft Word, that discusses the results of your analysis. Grading of the\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003esecond part will be based on the following items:\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eA brief introduction of the sorting algorithm that you have selected and how the two\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eversions of the algorithm compare\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eA discussion of the critical operation that you chose to count with an explanation of why\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eyou selected it\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eA Big-? analysis of the two versions of the algorithm\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eA discussion of the results of your study, which should include\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003egraphs of your results\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003ea comparison of the performance of the two versions of the algorithm\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003ea comparison of the critical operation results and the actual execution time\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003emeasurements\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003ea discussion of the significance of the standard deviation results and how it reflects the data sensitivity of your algorithm\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003ehow your results compare to your Big-? analysis\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eA conclusion that summarizes the important observations of your study\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eIf for any reason, it was necessary to revise the program you submitted in project 1, the revised\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003esource code should also be included along with the paper.\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eYou May Also Like:\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eCMSC451 Project 1 Benchmarking Sorting Algorithms\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003ch2\u003e\n\u003cb\u003e\u003cspan\u003eCMSC451 Project 1 Benchmarking Sorting Algorithms\u003c\/span\u003e\u003c\/b\u003e\u003cb\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/b\u003e\n\u003c\/h2\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eThe first project involves benchmarking the behavior of Java implementations of one of the following sorting algorithms, bubble sort, selection sort, insertion sort, Shell sort, merge sort, quick sort or heap sort. You must post your selection in the “Ask the Professor” conference. No more than five students may select any one algorithm.\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eProject 1 involves writing the code to perform the benchmarking of the algorithm you selected. Your program must include both an iterative and recursive version of the algorithm. You do not have to write them yourself, you may take them from some source, but you must reference your source. You must identify some critical operation to count that reflects the overall performance and modify each version so that it counts that operation. In addition to counting critical operations you must measure the actual run time. You are to write code to determine their efficiency based on the number of times that the critical operation is executed and actual time measurements. In addition, you should examine the result of each call to verify that the data has been properly sorted to verify the correctness of the algorithm. If the array is not sorted, an exception should be thrown. It should also randomly generate data to pass to the sorting methods. It should produce 50 data sets for each value of n, the size of the data set and average the result of those 50 runs. The exact same data must be used for the iterative and the recursive algorithms. It should also create 10 different sizes of data sets. Choose sizes that will clearly demonstrate the trend as n becomes large. You should also calculate the standard deviation of the critical operation counts and time measurement for the 50 runs of each data set size as a way to gauge the data sensitivity of the algorithm. Your program must be written to conform to the\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003efollowing design:\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eThe data set sizes above are examples. You are to select the actual data set sizes. On the due date\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003efor project 1, you are to submit a .zip file that includes the source code of your complete\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eprogram. All the classes should be in the default package.\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eGrading of the project will be based on the following items:\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eAdhered to the specified design\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eProduced the required output in the specified format\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eCorrectly calculated the statistics\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eChose good test sizes and good random data\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eCorrectly implemented the sorting algorithm\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eYou May Also Like:\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan\u003eCMSC451 Project 2 Sorting Algorithms Analytics\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e","brand":"Take My Online Class","offers":[{"title":"Default Title","offer_id":53388407570707,"sku":null,"price":67.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0966\/3794\/4083\/files\/CMSC451Capture5.png?v=1769546347","url":"https:\/\/takemyonlineclass.store\/products\/new-full-course-guide-cmsc-451-project-study-solution-download_id_451qq1omdv4os_exiuznw451xx","provider":"Take My Online Class","version":"1.0","type":"link"}