CS计算机代考程序代写 algorithm Tutorial

Tutorial
COMP20007 Design of Algorithms
Week 5 Workshop
We¡¯ll begin the tutorial by going over any graph representation questions from last week which we didn¡¯t get to.
1. Graph representations Consider the following graphs.
(a) An undirected graph: (b) A directed graph:
AB AB EE
CD CD
Give their representations as:
(i) adjacency lists (ii) adjacency matrices (iii) sets of vertices and edges
Which node from (a) has the highest degree? Which node from (b) has the highest in-degree?
2. Graph representations continued Different graph representations are favourable for different applications. What is the time complexity of the following operations if we use (i) adjacency lists (ii) adjacency matrices or (iii) sets of vertices and edges?
(a) determining whether the graph is complete
(b) determining whether the graph has an isolated node
Assume that the graphs are undirected. A complete graph is one in which there is an edge between
every pair of nodes. An isolated node is a node which is not adjacent to any other node. Assume that the graph has n vertices and m edges.
3. Sparse and dense graphs (optional) We consider a graph to be sparse if the number of edges, m, is order ¦¨(n). On the other hand we say a graph is dense if m ¡Ê ¦¨(n2).
Give examples of types of graphs which are sparse and types which are dense. What is the space complexity (in terms of n) of a sparse graph if we store it using:
(i) adjacency lists (ii) adjacency matrix (iii) sets of vertices and edges
4. Depth First Search and Breadth First Search List the order of the nodes visited in the following graph when the following search algorithms are run:
1

(i) depth first search (ii) breadth first search Start at A and break ties by choosing nodes in alphabetic order.
ACF
BD
EG
5. Tree, Back, Forward and Cross Edges A depth-first search of a directed graph can be represented as a tree (or a collection of trees, i.e., a forest). Each edge of the graph can then be classified as a tree edge, a back edge, a forward edge, or a cross edge. A tree edge is an edge to a previously un-visited node, a back edge is an edge from a node to an ancestor, a forward edge is an edge to a non-child descendent and a cross edge is an edge to a node in a different sub-tree (i.e., neither a descendent nor an ancestor). Draw a depth-first search tree based on the following graph, and classify its edges into these categories. Begin the depth-first search at A.
B AC
DE
In an undirected graph, you wont find any forward edges or cross edges. Why is this true? You might like to consider the graph above, with each of its edges replaced by undirected edges.
6. Finding Cycles Explain how one can also use breadth-first search to see whether an undirected graph is cyclic. Which of the two traversals, depth-first and breadth-first, will be able to find cycles faster? (If there is no clear winner, give an example where one is better, and another example where the other is better.)
7. 2-Colourability Design an algorithm to check whether an undirected graph is 2-colourable, that is, whether its nodes can be coloured with just 2 colours in such a way that no edge connects two nodes of the same colour.
To get a feel for the problem, try to 2-colour the following graph.
SA
EFB
DC
Do you expect we could extend such an algorithm to check if a graph is 3-Colourable, or in general: k-Colourable?
2

8. Minimum Spanning Tree with Prim¡¯s Algorithm Prim¡¯s algorithm finds a minimum span- ning tree for a weighted graph. Discuss what is meant by the terms ¡®tree¡¯, ¡®spanning tree¡¯, and ¡®minimum spanning tree¡¯.
Run Prim¡¯s algorithm on the following graph, using A as the starting node. What is the resulting minimum spanning tree for this graph? What is the cost of this minimum spanning tree?
A2B 4139 C2D7E 5846 F1G
9. Single Source Shortest Path with Dijkstra¡¯s Algorithm Dijkstra¡¯s algorithm computes the shortest path to each node in a graph from a single starting node (the ¡®source¡¯). Trace Dijkstra¡¯s algorithm on the graph from Question 7, with node E as the source. Repeat the algorithm with node A as the source. How long is the shortest path from E to A? How about A to F?
Computer Lab
Use today¡¯s lab time to work on Assignment 1. Make sure you can log in to dimefox, copy your code over, compile and run your program on the server.
If you¡¯ve completed the assignment already feel free to use this time to complete previous lab exercises.
3