Description
For this assignment, you will code 3 different graph algorithms. This homework has many files included,
so be sure to read ALL of the documentation given before asking questions.
Graph Data Structure
You are provided a Graph class. The important methods to note from this class are:
• getVertices returns a Set of Vertex objects (another class provided to you) associated with a
graph.
• getEdges returns a Set of Edge objects (another class provided to you) associated with a graph.
• getAdjList returns a Map that maps Vertex objects to Lists of VertexDistance objects. This
Map is especially important for traversing the graph, as it will efficiently provide you the edges
adjacent to any vertex (the outgoing edges of any vertex). For example, consider an adjacency list
where vertex A is associated with a list that includes a VertexDistance object with vertex B and
distance 2 and another VertexDistance object with vertex C and distance 3. This implies that in
this graph, there is an edge from vertex A to vertex B of weight 2 and another edge from vertex A
to vertex C of weight 3.
Vertex Distance Data Structure
In the Graph class and Dijkstra’s algorithm, you will be using the VertexDistance class implementation
that we have provided. In the Graph class, this data structure is used by the adjacency list to represent
which vertices a vertex is connected to. In Dijkstra’s algorithm, you should use this data structure along
with a PriorityQueue. When utilizing VertexDistance in this algorithm, the vertex attribute should
represent the destination vertex and the distance attribute should represent the minimum cumulative
path cost from the source vertex to the destination vertex.
DFS
Depth-First Search is a search algorithm that visits vertices in a depth based order. Similar to pre/post/inorder traversal in BSTs, it depends on a Stack-like behavior to work. In your implementation, the Stack
will be the recursive stack, meaning you should not create a Stack data structure. It searches along one
path of vertices from the start vertex and backtracks once it hits a dead end or a visited vertex until it
finds another path to continue along. Your implementation of DFS must be recursive to receive
credit.
Single-Source Shortest Path (Dijkstra’s Algorithm)
The next algorithm is Dijkstra’s Algorithm. This algorithm finds the shortest path from one vertex
to all of the other vertices in the graph. This algorithm only works for non-negative edge weights, so
you may assume all edge weights for this algorithm will be non-negative. In order to keep track of the
cumulative distance from the source vertex to the vertices you visit in this algorithm, you will need to
use the VertexDistance data structure we are providing you. At any stage throughout the algorithm,
the PriorityQueue of VertexDistance objects will tell you which vertex currently has the minimum
cumulative distance from the source vertex.
There are two commonly implemented terminating condition variants for Dijkstra’s Algorithm. The
first variant is where you depend purely on the PriorityQueue to determine when to terminate. You only
terminate once the PriorityQueue is empty. The other variant, the classic variant, is the version where
you maintain both a PriorityQueue and a visited set. To terminate, still check if the PriorityQueue
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Homework 08: GraphAlgorithms Due: See Canvas
is empty, but you can also terminate early once all the vertices are in the visited set. You should
implement the classic variant for this assignment. The classic variant, while using more memory,
is usually more time efficient since there is an extra condition that could allow it to terminate early.
Self-Loops and Parallel Edges
In this framework, self-loops and parallel edges work as you would expect. If you recall, self-loops are
edges from a vertex to itself. Parallel edges are multiple edges with the same orientation between two
vertices. In other words, parallel edges are edges that are incident on precisely the same vertices. These
cases are valid test cases, and you should expect them to be tested. However, most implementations of
these algorithms handle these cases automatically, so you shouldn’t have to worry too much about them
when implementing the algorithms.
Prim’s Algorithm
A tree is a graph that is acyclic and connected. A spanning tree is a subgraph that contains all the
vertices of the original graph and is a tree. An MST has two main qualities: being minimum and a
spanning tree. Being minimum dictates that the spanning tree’s sum of edge weights must be minimized.
By the properties of a spanning tree, any valid MST must have |V | − 1 edges in it. However, since
all undirected edges are specified as two directional edges, a valid MST for your implementation will
have 2(|V | − 1) edges in it.
Prim’s algorithm builds the MST outward from a single component, starting with a starting vertex.
At each step, the algorithm adds the cheapest edge connected to the incomplete MST that does not
cause a cycle. Cycle detection can be handled with a visited set like in Dijkstra’s..
Visualizations of Graphs
The directed graph used in the student tests is:
1
2 3
4
5
6
7
The undirected graph used in the student tests is:
A B
C
D E
F
7
5
4 3
8
2
1
6
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Homework 08: GraphAlgorithms Due: See Canvas
Grading
Here is the grading breakdown for the assignment. There are various deductions not listed that are
incurred when breaking the rules listed in this PDF and in other various circumstances.
Methods:
DFS 20pts
Dijkstra’s 30pts
Prim’s 25pts
Other:
Checkstyle 10pts
Efficiency 15pts
Total: 100pts
Provided
The following file(s) have been provided to you. There are several, but we’ve noted the ones to edit.
1. GraphAlgorithms.java
This is the class in which you will implement the different graph algorithms. Feel free to add
private static helper methods but do not add any new public methods, new classes, instance variables, or static variables.
2. Graph.java
This class represents a graph. Do not modify this file.
3. Vertex.java
This class represents a vertex in the graph. Do not modify this file.
4. Edge.java
This class represents an edge in the graph. It contains the vertices connected to this edge and
its weight. Do not modify this file.
5. VertexDistance.java
This class holds a vertex and a distance together as a pair. It is meant to be used with Dijkstra’s algorithm. Do not modify this file.
6. GraphAlgorithmsStudentTests.java
This is the test class that contains a set of tests covering the basic algorithms in the GraphAlgorithms
class. It is not intended to be exhaustive and does not guarantee any type of grade. Write your
own tests to ensure you cover all edge cases. The graphs used for these tests are shown
above in the pdf.
Deliverables
You must submit all of the following file(s). Make sure all file(s) listed below are in each submission, as
only the last submission will be graded. Make sure the filename(s) matches the filename(s) below, and
that only the following file(s) are present. Do NOT submit Graph.java, Vertex.java, Edge.java, or
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Homework 08: GraphAlgorithms Due: See Canvas
VertexDistance.java, or else your submission will not compile on Gradescope.
Once submitted, double check that it has uploaded properly on Gradescope. To do this, download
your uploaded file(s) to a new folder, copy over the support file(s), recompile, and run. It is your sole
responsibility to re-test your submission and discover editing oddities, upload issues, etc.
1. GraphAlgorithms.java
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