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CSCI 2270 – Data Structures and Algorithms

Assignment 12

A Nation Divided … by Zombies!
Admit it, we all love zombies. Maybe it’s because they don’t actually exist, and we
don’t actually have to worry about navigating a life among the undead. But, imagine
for a second an alternate universe where they do exist and they have attacked –
creating mayhem throughout the country, knocking down communications towers
and taking control of bridges and highways. One could imagine a resourceful zombie
coalition making it impossible to travel between major cities, isolating human
survivors in small districts around the country with no safe means of reaching other
districts.

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CSCI 2270 – Data Structures and Algorithms

Assignment 12

A Nation Divided … by Zombies!
Admit it, we all love zombies. Maybe it’s because they don’t actually exist, and we
don’t actually have to worry about navigating a life among the undead. But, imagine
for a second an alternate universe where they do exist and they have attacked –
creating mayhem throughout the country, knocking down communications towers
and taking control of bridges and highways. One could imagine a resourceful zombie
coalition making it impossible to travel between major cities, isolating human
survivors in small districts around the country with no safe means of reaching other
districts. The US would become a collection of small outposts, where cities within a
district could be reached from within the district, and district residents would need
to be careful about travel even within their district. Knowing the shortest path
between cities to avoid being attacked would be paramount for survival.
What your program needs to do:
Build a graph. There is a file on Moodle called zombieCities.txt that contains the
names of 10 cities and the distances between them stored as an adjacency matrix.
Cities that still have roads connecting them that aren’t controlled by zombies have a
positive distance in the file. Cities that have been cutoff from each other have a -1 as
their distance. When the user starts the program, read in the cities and distances
from the text file and build a graph where each city is a vertex, and the adjacent
cities are stored in an adjacency list for each vertex. For this assignment, you will
not need to use the actual distance, only the fact that there is an edge connecting
two cities. For the next assignment, you will need the distances, so it is probably
best just to set that up now.
Use a command-line argument to handle the filename.
For example, this data:
Boston Boulder Chicago
Boston 0 2000 982
Boulder 2000 0 -1
Chicago 982 -1 0
would generate this graph:
The vertices in the graph are Boston, Boulder, and Chicago. The adjacent vertices for
Boston are Boulder and Chicago. The adjacent vertex for Boulder is Boston, and the
adjacent vertex for Chicago is Boston.
Display a menu. Once the graph is built, your program should display a menu with
the following options:
1. Print vertices
2. Find districts
3. Find shortest path
4. Quit
Menu Items and their functionality:
1. Print vertices. If the user selects this option, the vertices and adjacent
vertices should be displayed. The district ID should also be included in the
display. (There is more about what the district ID is in the Find Districts
menu item.)
An example of how the output should be formatted is shown here:
1:Boston->Boulder**Chicago
1:Boulder->Boston
1:Chicago->Boston
The 1 shown is the district ID. District IDs should all be initialized to -1. If you
call print vertices before finding districts, your display would look like:
-1:Boston->Boulder**Chicago
-1:Boulder->Boston
-1:Chicago->Boston
2. Find districts. If the user selects this option, you need to do a breadth-first
search of the graph to determine the connected cities in the graph, and assign
those cities the same district ID. The connected cities are the vertices that are
connected, either directly by an edge, or indirectly through another vertex.
For example, in the Boulder, Boston, Chicago graph shown above, these three
cities are all connected even though there isn’t an edge connecting Chicago
and Boulder. There is a path between these two cities that goes through
Boston.
In your graph, add a parameter to each vertex to store a district ID. The ID
should be an integer, 1 to n, where n is the number of districts discovered in
the graph, you will not know this value ahead of time. To get the correct,
expected district ID for each vertex, make sure you read in the
zombieCities.txt file in order so that your vertices are set up in alphabetical
order.
When assigning district IDs, start at the first vertex and find all vertices
connected to that vertex. This is district 1. Next, find the first vertex
alphabetically that is not assigned to district 1. This vertex is the first
member of district 2, and you can repeat the breadth-first search to find all
vertices connected to this vertex. Repeat this process until all vertices have
been assigned to a district.
You do not need to print anything for this menu option. To verify that district
IDs have been assigned, call print vertices again.
3. Find shortest path. If the user selects this option, they should be prompted
for the names of two cities. Your code should first determine if they are in the
same district. If the cities are in different districts, print “No safe path
between cities”. If the cities are in the same district, run a breadth-first
search that returns the number of edges to traverse along the shortest path,
and the names of the vertices along the path. For example, to go from Boulder
to Chicago in the example graph, you would print:
2, Boulder, Boston, Chicago
You will need to include a distance parameter in each vertex. There are
multiple approaches to storing the path and you are welcome to use any
approach that works for you. Some options include storing the parent for
each vertex visited on the search path, or storing the path information in an
array or queue and reconstruct the path from that data. There is more
information about storing the path information in an array in your book.
How to submit your assignment
To submit your work, zip all files together and submit them to COG as
Assignment12.zip. If you do not get your assignment working on COG, you will have
the option of a grading interview.
Additional information
There is sample code on moodle showing how to use vectors and add vertices and
edges to a graph. There is also code showing how to use the built-in C++ queue class
that will make it easier to do the breadth-first search. The files are labeled
GraphIntro.zip and Lecture32STLcpp.
For more information on Vectors, there is a great tutorial here:
http://www.codeguru.com/cpp/cpp/cpp_mfc/stl/article.php/c4027/C-Tutorial-ABeginners-Guide-to-stdvector-Part-1.htm
Appendix A – cout statements
1. Print menu
cout << “======Main Menu======” << endl;
cout << “1. Print vertices” << endl;
cout << “2. Find districts” << endl;
cout << “3. Find shortest path” << endl;
cout << “4. Quit” << endl;
2. Print vertices
cout<< vertices[i].district
<<“:”<<vertices[i].name<<“–>”;
for each adjacent vertex:
cout<<vertices[i].adj[j].v->name;
if (j != vertices[i].adj.size()-1)
cout<<“***”;
3. Find districts
Nothing to print.
4. Find shortest path
cout << “Enter a starting city:” << endl;
cout << “Enter an ending city:” << endl;
One or both cities not found:
cout << “One or more cities doesn’t exist” << endl;
Cities in different districts:
cout << “No safe path between cities” << endl;
Districts not set yet:
cout << “Please identify the districts before checking
distances” << endl;
Algorithm successful:
cout << edgesTraversed;
for all cities in path
cout << “,” << path[j]->name;
cout << endl;
5. Quit
cout << “Goodbye!” << endl;

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