The goal of this machine problem is to extend the two-way linked list ADT from machine problem 2 to include four algorithms for sorting a list. Extend machine problem 2 to include two new commands:
SORT x sorts the queue in ascending order based on su_id, where x is one of the four sorting algorithms defined below.
ADDTAIL su_id is similar to ADDSU except for the following changes. First, unlike ADDSU, do NOT check if the secondary user information is already found in assigned list or waiting queue. Simply add the new secondary user record to the tail of the waiting queue. This implies that there CAN be duplicate su_id’s (we will fix this problem in a later assignment!). Second, only the su_id is given on the input line. The remaining parameters in the su_info_t structure are all set to zero by default. Don’t call the sas_record_fill function. Just collect the su_id (and use calloc so all other values in the structure are zero).
The code must consist of the following files:
lab3.c – the main() function for testing the sort algorithms. Use lab2.c as a template.
list.c – Extension of the two-way linked list ADT from lab2
sas_support.c – Use the same sas_support.c file from machine problem 2.
sas_support.h – The data structures for secondary user records, and the prototype definitions.
list.h – The data structures and prototype definitions for the list ADT.
datatypes.h – Key definitions of the secondary user structure
makefile – Compiler commands for all code files
Sorting the two-way linked list ADT
Create the prototype definition void list_sort(ListPtr list_ptr, int sort_type) in your list.h file. For this function, sort_type can take one of the following values:
Insertion sort. We can use the other functions in list.c to implement a very simple sort function. To sort the list, use list_remove to take the first (or head) item from the list and list_insert_sorted to put the item into a second list that is sorted. When all the elements have been inserted into the sorted list, adjust the pointers in list_ptr to point to the newly sorted list. Note this is a simple variation of the priority queue sort described by Standish in Section 4.3 of the book.
Recursive Selection Sort. Implement the recursive version of the selection sort as defined by program 5.19 on page 152 in the book by Standish. Except, change the code so the sorted list is increasing. Update the algorithm so that it properly handles our two-way linked list (as opposed to the implementation for an array in program 5.19). The calculations of the sort algorithm should not change; just change the algorithm to work with pointers instead of indexes into an array. You will also need to implement Standish’s FindMax algorithm defined in program 5.20 on page 152. The source code from Standish is available on Canvas. See also the note at the end of this document.
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5.35 on page 171 in the book by Standish. Read Section 5.4 for an explanation of how the recursive version of the program is transformed into the iterative version.
Merge Sort. Implement the recursive version of merge sort as defined by the program 6.19 on page 237 of the book by Standish. Note that you will need to implement two support functions. The first is a function to partition a list into two half-lists (this is easy to implement as you just step through the linked list until half the list size and then break the list into two lists). This second function merges two lists that are sorted into a single list. Read the paragraph on page 237 that discusses how to merge two lists, and note that it is a simple process of using list_remove at the head of either the left or right list and list_insert at the tail of the merged list. See also the MergeSort powerpoint file for an illustration of the algorithm in the textbook.
Be careful to design your algorithms so that you do not change their complexity class. Do not redesign the algorithm! The final two lines of the function list_sort must be
list_ptr->list_sorted_state = SORTED_LIST; list_debug_validate(list_ptr);
Note that ADDTAIL is implemented using list_insert(), and the list_insert function changes list_sorted_state to UNSORTED_ LIST. Thus, SORT is used the change the list status to the sorted state.
Measuring time to sort
To measure the performance of a sorting algorithm use the built in C function clock to count the number of cycles used by the program. In sas_support.c add a function for sorting and use:
clock_t start, end;
double elapse_time; /* time in milliseconds */
int initialsize = list_size(L);
start = clock();
end = clock();
elapse_time = 1000.0 * ((double) (end – start)) / CLOCKS_PER_SEC; assert(list_size(L) == initialsize);
printf(“%d\t%f\t%d\n”, initialsize, elapse_time, sort_type);
where CLOCKS_PER_SEC and clock_t are defined in <time.h>.
Additional requirements for SORT
Your final code must use the exact printf() statement given in the above example. You will collect output from multiple runs to plot performance curves, showing run time for various list sizes. Your program must verify that the size of the list after the completion of the call to list_sort matches the size before the list is sorted. Your program must not have any memory leaks or array boundary violations.
Suppress prints and unnecessary validation calls during performance evaluation and for final submission
Do not include any printf calls for your new sas_add_tail function. We don’t need to see 250,000 prints about prompting and adding to the queue. Also, comment out the welcome menu and goodbye
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prints in lab3.c to avoid unnecessary chatter. Also, comment out the printf’s in sas_create. The only output should be the one new print statement added to measure the sorting time.
The list_debug_validate() function is very inefficient. After all your code works correctly, remove list_debug_validate() from all list_() functions except list_sort(), where it must remain as the last line called before the function returns.
Generating large inputs for testing
See the supplemental program geninput.c to create input for testing. The program takes three options on the command line. The first specifies the size of the list, the second specifies the type of list, and the third the type of sorting algorithm. There are three possible types:
List with elements in a random order.
List with elements already in ascending order.
List with elements in descending order.
To run, pipe the output of the geninput program into lab3. For example, for a merge sort trial on a list with 10,000 elements in random order use:
./geninput 10000 1 4 | ./lab3
The final code you submit must operate with geninput.c. In particular, you must have commented out the calls to the validation function (except the call in list_sort). Your program should be able to sort approximately 12,000 items (or more) in about one second for insertion sort or either selection sort. For merge sort, your program should be able to sort approximately 250,000 items (or more) in about one second
Final testing and PDF for the testing log
Test each of the four sorting algorithms and each of the three list types (random, ascending, descending) with at least five different list sizes. You must create graphs to illustrate your results. In particular, for the tests involving random list types, you must include in your graph the result for at least one list size that requires more than one second to sort as determined using the C function clock.
In your Test Log document, in addition to reporting your data using graphs, describe
For lists that are initially random, explain the differences in running time for the sorting algorithms. Do your iterative and recursive selection sort algorithms show dramatic differences in running times or are they similar? Why does the mergesort algorithm show a dramatic improvement in run time? If the runtime for merge sort is not dramatically faster than the other algorithms you have a bug.
If a list is already in ascending or descending order, some sort algorithms are very fast while others still have to perform a similar number of comparisons as when the list is not sorted. Describe which algorithm(s) show extremely fast performance if the list is already sorted, and explain why.
You must submit your test log as a PDF file. Both Microsoft Word and LibreOffice have tools that convert the document to PDF format.
Your test script is a simple listing of the lab3 commands you used to generate the data for your test log. See the example script posted on Canvas. You just need to make small changes to the test script to account for the speed of your computer.
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An optional experiment is to recompile your final code taking out the –Wall and –g options and adding the –O option (capital letter o, not zero) to all calls with gcc. The –O option turns on compiler optimizations and you should find your code runs faster. While the run times are reduced and you can sort larger lists, has the complexity class for any of the sorting algorithms changed?
When converting Standish’s selection sort algorithms from working with arrays to working with pointers, don’t try to add array-like features to our two-way linked list. Instead rewrite Standish’s code to use pointers. For example, change
void SelectionSort(InputArray A, int m, int n)
void SelectionSort(list_t *A, list_node_t *m, list_node_t *n)
Submit all the files listed on page 1, your test script, and a PDF document that includes graphs showing performance of all sorting algorithm. You submit by email to firstname.lastname@example.org. Use as subject header ECE223-1,#3. When you submit to the assign server, verify that you get an automatically generated confirmation email within a few minutes. You must include your files as attachments, and your email must be in text only format. You can make more than one submission but we will only grade the final submission. A re-submission must include all files. You cannot add files to an old submission.
To receive credit for this assignment your code must compile and at a minimum sort small lists using all four sorting algorithms. Code that does not compile or does not sort sets of 100 records will not be accepted or graded.
See the ECE 2230 Programming Guide for additional requirements that apply to all programming assignments.
Work must be completed by each individual student, and see the course syllabus for additional policies.
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