List the algorithm and the big o notation

Reference no: EM133389676

1. The time required in nanoseconds, the number of comparisons required and the time to execute a basic step (the comparison) in ns for each of the sort methods provided. The basic step is determined by taking the time required to sort an array of a size n and dividing by the number of comparisons required for that algorithm. Report your results for data sets of 30, 300, 30000 elements.

3. The sorta method currently counts the # of comparisons by using a global variable. This is not a good programming technique. Modify the sorta method to count comparisons by passing a parameter. This is a little trickier as the comparisons are done in the part method. You should notice that the number of comparisons can be determined before the call to the part method. You will need to return this value from
the sorta method and modify the sorta header to pass this value into each recursive call. You will need to add the counts recursively. As an alternative to the recursive counting, you can leave the code as is and complete the sorta counting using the global variable.

4. Adding counting to the sortd method. Again, you can use a recursive technique or use a global variable. Recursive counting is preferred. If this is not possible use a global variable like sorta

5. Time the java standard Arrays.sort method for all three sizes.

6. In a Comment section at the TOP of your source file, provide answers to the following:
o Identify the type of sorts for each of the methods provided. Indicate which sort (a,b,c,d,e) is bubble, quick, merge, selection or insertion.
o List in order (fastest to slowest) your selection of algorithm to use when the array to be sorted contains 30 elements. Base this on your results
o List in order (fastest to slowest) your selection of algorithm to use when the array to be sorted contains 30000 elements.
o List the algorithm and the BIG O notation (time complexity, average case) for that algorithm. Does the Big O notation line up with your results for 30000 elements?
o Which algorithm has the best performance of the basic step? Does this have any impact on your selection of fastest algorithm when sorting an array of 30000 elements? Why?
o For the standard Arrays.sort method, which algorithm do the performance results most resemble.1. The time required in nanoseconds, the number of comparisons required and the time to execute a basic step (the comparison) in ns for each of the sort methods provided. The basic step is determined by taking the time required to sort an array of a size n and dividing by the number of comparisons required for that algorithm. Report your results for data sets of 30, 300, 30000 elements.

2. Modify the sorta, sortb, sortc, sortd, sorte methods to count the number of comparisons and return this value from the method. Suggested Steps:
a. Change each of the sort methods from type void to type int.
b. Add a local count variable to each method.
c. Increment the count just before the comparison of two array elements in each of the sort methods.
d. Return the count value from the method and print to the screen in the main method.
3. The sorta method currently counts the # of comparisons by using a global variable. This is not a good programming technique. Modify the sorta method to count comparisons by passing a parameter. This is a little trickier as the comparisons are done in the part method. You should notice that the number of comparisons can be determined before the call to the part method. You will need to return this value from
the sorta method and modify the sorta header to pass this value into each recursive call. You will need to add the counts recursively. As an alternative to the recursive counting, you can leave the code as is and complete the sorta counting using the global variable.

4. Adding counting to the sortd method. Again, you can use a recursive technique or use a global variable. Recursive counting is preferred. If this is not possible use a global variable like sorta

5. Time the java standard Arrays.sort method for all three sizes.

o Which algorithm has the best performance of the basic step? Does this have any impact on your selection of fastest algorithm when sorting an array of 30000 elements? Why?
o For the standard Arrays.sort method, which algorithm do the performance results most resemble.

Reference no: EM133389676

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