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日期:2021-03-01 11:03

Programming assignment 2 (120 points)

Due Monday by 11:59pm Points 120 Submitting a file upload File Types tar

Available until May 12 at 11:59pm

Submit Assignment

Graph algorithms in C

Rutgers University

2021 Spring

0. Introduction and setup

Learning goals

You will practice programming more complicated C programs. This includes using header files to organize your source code, using and

building data structures, and using recursive function calls. At the same time, you will review and learn about important graph algorithms

found throughout computer science.

Resources

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2021/2/27 Programming assignment 2 (120 points)

https://rutgers.instructure.com/courses/104725/assignments/1245909 2/13

Get started early! You can post questions to the class Piazza (please avoid sending emails to the TAs and instructor). You can discuss the

assignment with your classmates, but you cannot copy code from your classmates. We will be checking the assignments for identical

and/or plagiarized code using automated tools. See the academic integrity policy at: https://nbprovost.rutgers.edu/academic-integritystudents

(https://nbprovost.rutgers.edu/academic-integrity-students) . We will report any violations.

Setup

The autograder script for this assignment needs two Python packages that you can easily install. Once you are logged into ilab, run the

following command in any directory:

python -m pip install scipy networkx

Access the programming assignment files for this assignment by pulling new files from the class Github repository, 2021_0s_211:

git pull

If you do not have this directory already, clone the repository:

git clone https://github.com/yipenghuang0302/2021_0s_211.git

The files for this assignment are in the directory 2021_0s_211/pa2/.

1. edgelist: Loading, representing, and printing an undirected unweighted

graph (easy) (22 points)

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2021/2/27 Programming assignment 2 (120 points)

https://rutgers.instructure.com/courses/104725/assignments/1245909 3/13

Graphs are fundamental data structures. A graph consists of nodes and edges connecting pairs of nodes. A basic kind of graph is an

undirected, unweighted graph, meaning that the edges are not directional, and each edge doesn't have any additional properties. Here is

an example of an undirected, unweighted graph G=(V,E), V={0,1,2,3}, E={(0,1),(0,2),(0,3),(1,3)} of four nodes and four edges:

There are several important ways to represent graphs.

The first graph representation is an adjacency matrix (https://en.wikipedia.org/wiki/Adjacency_matrix) . The adjacency matrix of the

above graph is:

0 1 1 1

1 0 0 1

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2021/2/27 Programming assignment 2 (120 points)

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1 0 0 0

1 1 0 0

The 0, 1, 1, 1 in the first row of the matrix indicates the 0th node is connected to the 1st, 2nd, and 3rd nodes, and so on.

The second graph representation is an adjacency list (https://en.wikipedia.org/wiki/Adjacency_list) . For a graph consisting of N nodes,

the adjacency list data structure is an array of N separate linked lists for each node p, where each link in the linked list records a node q if

the edge (p,q) exists. For example, the adjacency list representation of the above graph is:

0->1->2->3->/

1->0->3->/

2->0->/

3->0->1->/

The ->/ indicates a null pointer terminating the linked list.

The third graph representation is by listing the edges of the graph. For example, the edge list of the above graph is:

0 2

0 3

0 1

1 3

In the first part of this assignment, you will write a program that:

1. Loads an adjacency matrix representation of an undirected unweighted graph,

2. Holds that graph representation as a adjacency list data structure,

3. Prints out the edge list representation of the graph.

Input format

Your program should take a single command line argument specifying the path to an input file. Test cases for your program are in the

tests/ directory. In each test case, the first line records the number of nodes N in the graph. Then, the adjacency matrix is recorded in the

subsequent N rows of the file.

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Output format

Expected outputs from your program for each test case are in the answers/ directory. You should print one line for each edge of the graph;

each line should list the pair of nodes (separated by a space) constituting a graph edge.

This is an undirected graph, so the order of the nodes does not matter. The autograder will recognize re-ordering of the nodes as correct.

The ordering of which edges are printed first also does not matter. The autograder will recognize re-ordering of the edges as correct.

How to compile, run, and test your code

Instructions from Programming Assignment 1 carry over, with two important points.

First, an important C header file, graphutils.h, is provided to you in 2021_0s_211/pa2/graphutils.h. This file offers ready-to-use functions for

loading a adjacency matrix, creating an adjacency list data structure, and freeing the adjacency list. You should call these functions to

simplify your code.

Second, the autograder.py scripts for this assignment only work with Python version 2 on the ilab machines. This means that the correct

way to invoke the autograder script is through either of these two commands:

./autograder.py

or

python2 autograder.py ?

2021/2/27 Programming assignment 2 (120 points)

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2. isTree: Determining whether an undirected graph is a tree using depthfirst

search (medium) (22 points)

An undirected graph is a tree if and only if the graph contains no cycles. For example, this is a tree because it contains no cycles:

While this graph contains cycles and therefore is not a tree:

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In this second part of the assignment, you will write a depth-first search through a graph to determine whether the graph contains cycle. A

cycle is detected when depth-first search find a graph node that was already visited.

Input format

Your program should take a single command line argument specifying the path to an input file. Test cases for your program are in the

tests/ directory. In each test case, the first line records the number of nodes N in the graph. Then, the adjacency matrix is recorded in the

subsequent N rows of the file.

Output format

You should print "yes" if the graph is a tree, "no" if the graph is not a tree. Expected outputs from your program for each test case are in

the answers/ directory.

3. solveMaze: Finding the shortest path through a maze with cycles using

breadth-first search (hard) (22 points)

In this third part of the assignment, you will write a program to find a shortest path in a graph from a source node to a destination node

using breadth-first search. The graph representing the maze may contain cycles, so it is important avoid revisiting nodes that have already

been visited.

Many important problems in artificial intelligence, robotics motion planning, and self-driving cars boil down to solving mazes on graphs. In

classes such as AI and robotics, you will learn about advanced algorithms for solving mazes using heuristics (or guesses) that minimize

search time.

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Input format

Your program should take TWO command line arguments. The first argument specifies the path to an input file describing a graph like

previous portions of this assignment. The second argument specifies the path to an input file describing a query. The first line of the query

file specifies the source node where you begin your search. The second line of the query file specifies the target node you want to reach.

Output format

You should print a list of edges that, taken together, connect the source node to the target node in the graph. Again, the ordering of the

nodes in each edge does not matter. The ordering of the edges does not matter. The autograder will check to see if you give a minimal set

of edges that connect the source and target nodes.

4. mst: Finding the minimum spanning tree of a undirected weighted graph

(medium) (22 points)

A weighted graph is a graph that has a numerical weight property on each edge. The minimum spanning tree (MST) of an undirected

weighted graph is a tree that connects all nodes in the graph, and at the same time minimizing the sum of the weights of the tree's edges.

Many important problems in computer networking and operations research boil down to finding MSTs on graphs. As an example, this is a

undirected weighted graph:

And this is its MST:

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The edges (0,1) and (1,2) connects all nodes in the graph, and picking these edges minimizes the total weight of the tree. If all the weights

in an undirected weighted graph are unique, then the MST is also unique, meaning everyone will find the same MST for a given graph.

In this fourth part of the assignment, you will write a program implementing a greedy algorithm to find the MST. Several algorithms solve

this problem, but Prim's algorithm (https://en.wikipedia.org/wiki/Prim%27s_algorithm) is likely the easiest to implement.

Input format

Your program should take a single command line argument specifying the path to an input file. Test cases for your program are in the

tests/ directory. In each test case, the first line records the number of nodes N in the graph. Then, the adjacency matrix is recorded in the

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subsequent N rows of the file. This time, the adjacency matrix contains floating point numbers. 0.0 indicates no edge between two nodes.

Any other value indicates an edge with the given value as the edge weight.

Output format

Expected outputs from your program for each test case are in the answers/ directory. You should print a list of edges that, taken together,

form the MST of the input graph. Again, the ordering of the nodes in each edge does not matter. The ordering of the edges does not

matter.

5. findCycle: Finding a cycle in a directed graph using depth-first search

(hard) (22 points)

A directed graph is a graph where edges are directional; that is, edges (p,q) and (q,p) are distinct. An important class of directed graphs

are directed acyclic graphs (DAGs), which have broad applications in programming languages and compilers. A DAG is any directed

graph with no cycles. For example, this is a directed graph:

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The above graph is not a DAG because it contains cycles. The cycles are:

1 2

4 7

4 5 7

By extension, these rotated versions are also valid cycles of the above graph:

2 1

7 4

5 7 4

7 4 5

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In this fifth and final part of the assignment, you will bring together ideas you have used throughout this assignment to find and print a

cycle in a directed graph. If no cycles are found, your program will report that the graph is a DAG. You can use any algorithm for this task;

either the DFS or the BFS approaches you have used in this assignment so far can be useful.

Input format

Your program should take a single command line argument specifying the path to an input file. Test cases for your program are in the

tests/ directory. In each test case, the first line records the number of nodes N in the graph. Then, the adjacency matrix is recorded in the

subsequent N rows of the file. This time, the adjacency matrix represents a directed graph.

Output format

You should print a single line of nodes (separated by spaces) that forms a cycle in the input directed graph. For example, for the example

directed graph above you can print any one of the seven cycles listed above. This time, the ordering of the nodes does matter as this is a

directed graph. If no cycles were found, your program should print "DAG". The known cycles for each test case are in the answers/

directory. You can print out rotated versions of the known cycles; the autograder will see that rotated cycles are equivalent.

Hint

Suppose you enter the graph from 0, and find a cycle by following the path

0->7->4->5->7

Upon seeing 7 again, you know you have detected a cycle. You have to carefully determine where the cycle begins and ends in the path

you have traversed.

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How to submit

From the pa2/ directory, you can run this command to check on the outputs of our autograder script.

./assignment_autograder

or

python2 assignment_autograder.py

When you are ready to submit, from the 2021_0s_211/ directory where you see the pa2/ directory, run this command:

tar cvf pa2.tar pa2/

Upload the file pa2.tar here on Canvas.

By submitting your assignment, you are agreeing to the Rutgers Honor Pledge: “On my honor, I have neither received nor given any

unauthorized assistance on this examination assignment.”

We will not be accepting late assignments. The Canvas submission site will close to enforce the deadline, so be sure to submit early.

If anything is not clear, reach out to your classmates and the instructors on the class Piazza!

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