Computer Science 501
Data Structures and Algorithm Analysis

Fall 2015, The College of Saint Rose

Lab 11: More Trees, Graphs, and Dijkstra's Road Trip
Due: 6:00 PM, Wednesday, December 9, 2015

This lab, your last, covers our remaining topics and is not due for 3 weeks. It includes tasks related to trees, graphs, and hashing. There is a lot to do here, so please be sure to spread out your work on it over the entire 3 weeks.

No late submissions will be accepted for the lecture and lab questions, as we will go over solutions to all of these problems and programs during class on the due date. However, the programming assignment will be accepted without penalty through 6:00 PM, Monday, December 14, 2015.

You may work alone or in groups of 2 or 3 on this lab. Only one submission per group is needed.

Getting Set Up

To get your BlueJ environment set up for this week's lab assignment, start BlueJ and choose "New Project" from the "Project" menu. Navigate to your folder for this course and choose the name "Lab11" (no spaces) for the project.

Create a document where you will record your answers to the lecture assignment and lab questions. If you use plain text, call it "lab11.txt". If it's a Word document, you can call it whatever you'd like, but when you submit, be sure you convert it to a PDF document "lab11.pdf" before you submit it.

Lecture Assignment Questions

We will usually discuss these questions at the start of class on the lab due date, so no credit can be earned for late submissions of lecture assignment questions.

LA Question 1: Bailey Problem 13.12, p. 339. (2 points)

LA Question 2: Bailey Problem 13.20, p. 340. (2 points)

LA Question 3: Bailey Problem 14.14, p. 365. (2 points)

LA Question 4: Start with a complete AVL tree containing the values 10, 20, 30, 40, 50, 60, and 70. Insert the values 31, then 32, showing any rotations needed to maintain the AVL condition. (3 points)

LA Question 5: Now, starting with the original tree, insert 32 then 31. Show any rotations needed to maintain the AVL condition. (3 points)

LA Question 6: Design an AVL tree of height 4 such that if one more value is inserted, the root is the first unbalanced node on the way back up the tree. Once you have such a tree, insert that value, perform the proper rotation(s) and verify that the AVL condition is once again met. (3 points)

LA Question 7: Bailey Problem 15.2, p. 399. (2 points)

LA Question 8: Bailey Problem 15.6, p. 399. (2 points)

LA Question 9: Bailey Problem 15.8, p. 399. (2 points)

LA Question 10: Bailey Problem 15.12, p. 400. (2 points)

LA Question 11: Bailey Problem 15.16, p. 400. (2 points)

Problem Set Question: Dijkstra's Algorithm Practice

Question 1: Using the graph from Bailey Problem 16.7, p. 436, use Dijkstra's Algorithm to compute the shortest distance from Dover to Phoenix by filling in the tables below, using the algorithm and notation as shown in the example in the graph notes. (10 points)

The data structures and the implementation of Dijkstra's algorithm are similar to those you will be using for the programming assignment below. Vertex labels are of type City and edge labels are of type TravelLink. You may assume that TravelLink provides methods to retrieve road names, distances, and driving times, but those details will not be important. The priority queue will contain objects of type ComparableAssociation<Integer,Edge<City,TravelLink>>, where the keys are the distances or driving times, as appropriate. The algorithm will populate a Map of shortest/fastest routes. The Map's keys will be of type City and the values will be ComparableAssociation<Integer,Edge<City,TravelLink>> objects, from which we can get the total distance/time to the City from the starting City.

For each case, you are to fill in the given table, representing the Map, in the order in which the algorithm fills in entries, and show the values in the priority queue. Do not erase values as they are removed from the priority queue, just cross them out and write a number next to them to indicate the order in which they are removed from the queue. The map and priority queue should indicate their contents at the time the city "Phoenix" is added to the map.

Fill in the table on the PDF version of this document, which is a Map that has City objects as keys and ComparableAssociations of the shortest distance from Dover to the last edge traversed on that shortest route as values.

It is easiest to specify edges by the labels of their endpoints rather than the edge label itself, which might not be unique.

Also, use the table on the PDF version of this document to keep track of your priority queue. Remember, don't erase entries when you remove them from the queue, just cross them out and mark them with a number in the "Seq" column of the table entry to indicate the sequence in which the values were removed from the queue.

Problem Set Questions: Heapsort

Question 2: Consider the construction of a max-heap as the first phase of a heapsort. Start with an array containing the values 98, 2, 0, 32, 15, 50, 7, 23, and 39. Show the contents of the array (in array or tree form, your choice) after each non-trivial iteration of the first phase of the heapsort (which goes from an unsorted array to a max-heap). (5 points)

Question 3: Now, show the transformation from the max-heap to sorted array, completing the heapsort procedure. (5 points)

Problem Set Questions: Generalized Heapsort

You learned about d-heaps as you completed the questions in our previous lab. You also have learned about heapsort, which uses a 2-heap as an intermediate representation to sort the contents of an array. Let's consider a generalization of the heapsort idea:

For heapsort, the PQ is a 2-heap, but any PQ implementation would work (naive array- or list-based with contents either sorted or unsorted, a d-heap, or even a binary search tree). Depending on which underlying PQ is used, the sorting procedure will proceed in a manner similar, in terms of the order in which comparisons occur, to one of the other sorting algorithms we have studied (e.g., selection sort, quicksort, etc.).

Question 4: For each of the following underlying PQ structures, state which sorting algorithm proceeds in the manner most similar to the PQ-based sort using that PQ structure, and explain your answer briefly. (10 points)

Practice Program

Practice Program: Write a program that constructs a graph using one of the structure package's Graph implementations that represents the graph below, then prints it out using the Graph's toString method. (4 points)

Programming Assignment

For your last bigger programming task, you will again be working with the highway graph data files linked from /chm/graphs.html. This time, we will be using the entire file, not just the waypoints.

The Data

Recall that the data is in ".gra" files which have the following format:

Visualization of Graphs and Results

There are several motivations for using the highway data set to help study graphs and graph algorithms. One significant one is the ability to visualize the input data and result data on a map. Our data can be visualized by directing a browser at the "Highway Data Explorer (HDX)" /chm/viewer/ and uploading a graph or other file in the file selection box at the top of the page. HDX is built on the Google Maps API.

The list of graphs at /chm/graphs.html has links to load complete graph files and visualize them with HDX.

Your first task is to augment your WaypointBest program from a few weeks ago that used your BestOf structure to find the collections of waypoints that were the first and last alphabetically by waypoint name, had the longest waypoint name, and were the furthest north, south, east and west. Extend your program so it creates seven output files, one for each of the criteria, in "Waypoint List File (WPL)" format. A WPL file consists of a list of waypoints, one per line, with the waypoint name, followed by a space, followed by the latitude, followed by a space, followed by the longitude. Have your program create each file with a ".wpl" extension. Then, from the HDX, to select one of your WPL files and see the points on the map.

Question 5: Include screen shots from HDX of the plots of the top 25 waypoints by each of the 7 criteria for the usa-all.gra input graph. (7 points)

Building a Graph and Implementing Simple Queries

Your next task is to be able to read the entire contents of a .gra file and to create a Graph structure using the structure package's graph implementations that represent all of the waypoints (graph vertices) and their connections (graph edges).

Question 6: The structure package has 4 implementations of the Graph interface: each combination of directed and undirected, and of list-based and matrix-based. Which graph implementation is most appropriate here, and why? (2 points)

Your overall approach will be to develop a Java program or programs that can read in graph data, store it appropriately in memory, and perform a variety of operations on that data. Two "starter" Java classes will be emailed to you and are available on mogul. You should work with these.

Important note: while you might use an array or a Vector to track some information during the construction of your graph, the only persistent structure in your implementation should be an instance of a Graph class.

Bringing in BestOf

Your next task is to add a capability to your program to be able to find and report the n longest or shortest edges in the graph. Implement these as the commands PrintLongestEdges and PrintShortestEdges in your program.

For example, with the canyt.gra graph, the 10 shortest edges:

YT6@MacBoatLau to YT6@+X646670 via YT6 length 0.0000
YT1@MorLakeRS to YT1@BC/YT via YT1 length 0.0936
YT1@BeaCrkAir to YT1@CanCus via YT1 length 0.1077
YT2@DukeSt to YT2@GeoBlaFry via YT2 length 0.1979
YT4_S/YT6_S to YT4@OldCanRd&YT6@OldCanRd_S via YT4,YT6 length 0.2299
YT6@+x822 to YT6@+x116 via YT6 length 0.2522
YT6@+X297007 to YT6@+X720169 via YT6 length 0.2704
YT4@+x88 to YT4@+x87 via YT4 length 0.2739
YT2@+X456835 to YT2@CliAgaRd via YT2 length 0.3073
YT6@+X401385 to YT6@+x771 via YT6 length 0.3446

and the 10 longest edges:

YT1@+X372730 to YT1@+X931620 via YT1 length 10.3368
YT1@+X687758 to YT1@+X612218 via YT1 length 9.8789
YT3@+X260467 to YT3@+x898989 via YT3 length 9.0087
YT2@+X558217 to YT2@GraRd via YT2 length 8.2056
YT1@+X336247 to YT1@+X858279 via YT1 length 7.4635
YT4@+x48 to YT4@+X800213 via YT4 length 7.1541
YT5@+X717826 to YT5@+X920982 via YT5 length 7.0805
YT1@CanCus to YT1@+X680719 via YT1 length 6.9887
YT2@HunCrkRd to YT2@BonCrkRd via YT2 length 6.9588
YT6@+X620794 to YT6@LapCanTr via YT6 length 6.8125

A format similar to the above would be appropriate for text output. One way to accomplish this is to create a list of all edges and sort them by edge length. But we can do this more efficiently, as you learned in the BestOf lab. For 12 points, compute the set of longest/shortest edges in Θ(n|E|) time, where n is the number of longest/shortest edges you are looking for and |E| is total the number of edges in the graph. Note that you can earn at most 5 points if your implementation is less efficient than the above, or if it does not compute the sets of edges from the graph in memory (as opposed to pre-computing them while the graph data was being loaded in).

For 5 points, you are to implement a second option, where the lists of longest or shortest edges are written to a file in a particular format. These should be implemented in the commands MapShortestEdges and MapLongestEdges. Here, each edge in the set of results should be specified by placing the vertex information for each of its endpoints on consecutive lines of a file. For example, the 3 shortest edges from canyt.gra would be specified in the file as:

YT6@MacBoatLau 62.86788 -130.82806
YT6@+X646670 62.868138 -130.827901
YT1@MorLakeRS 59.998729 -132.116818
YT1@BC/YT 60.000075 -132.117087
YT1@BeaCrkAir 62.407424 -140.860358
YT1@CanCus 62.40891 -140.85935

These files should be given a .nmp extension. Once such a file is created, it can be visualized by directing a browser at /chm/viewer/ and uploading the .nmp file in the file selection box at the top of the page.

Implementing Dijkstra's Algorithm

Your final programming task is to develop a simplified "driving directions" system based on the mapping data you have been working with.

You should use a variant of Dijkstra's Algorithm to compute shortest path from a given starting point (a graph vertex) to a given destination point. The general form of Dijkstra'a Algorithm computes the shortest paths from a starting vertex to all other vertices, but you will be able to stop one you find a shortest path to the specified destination rather than calculating the shortest path to all other places. You will also need to make sure that you can efficiently print/write the computed route in the proper order (starting point to destination point).

Once a shortest path is computed, you will need to be able to output it in a human-readable form (for the FindRoute command) or in a form plottable by HDX (for the MapRoute command).

For example, if you load the ny-all.gra file, and compute a shortest path for a few nearby points: US20@WesAve (the "Y" intersection at Western and Madison right near campus) and NY2/US9 (Latham Circle), your path would traverse the following points:

US20@WesAve, NY443/US9W@US20&US20@US9W, NY5/US9W, US9/US9W
I-90@6/US9, NY377/US9, NY378/US9, NY155/US9 and NY2/US9.

Your "human readable" output might look something like this:

Travel from US20@WesAve to NY443/US9W@US20&US20@US9W
 for 1.56 miles along US20, total 1.56
Travel from NY443/US9W@US20&US20@US9W to NY5/US9W
 for 0.37 miles along US9W, total 1.93
Travel from NY5/US9W to US9/US9W
 for 0.28 miles along US9W, total 2.21
Travel from US9/US9W to I-90@6/US9
 for 0.87 miles along US9, total 3.09
Travel from I-90@6/US9 to NY377/US9
 for 0.44 miles along US9, total 3.53
Travel from NY377/US9 to NY378/US9
 for 2.04 miles along US9, total 5.57
Travel from NY378/US9 to NY155/US9
 for 2.24 miles along US9, total 7.81
Travel from NY155/US9 to NY2/US9
 for 0.78 miles along US9, total 8.59

Your plottable data for the Highway Data Examiner should be in a ".pth" file. This file format must match the following:

START US20@WesAve (42.666502,-73.791776)
US20 NY443/US9W@US20&US20@US9W (42.652458,-73.767786)
US9W NY5/US9W (42.656734,-73.763301)
US9W US9/US9W (42.659938,-73.759975)
US9 I-90@6/US9 (42.669562,-73.748817)
US9 NY377/US9 (42.675873,-73.747659)
US9 NY378/US9 (42.704925,-73.754568)
US9 NY155/US9 (42.736832,-73.76225)
US9 NY2/US9 (42.748115,-73.761048)

Here, each line describes one "hop" along the route, consisting of the road name of the segment (i.e., your edge label), the waypoint name (i.e., the label in your vertex), and the coordinates of that point. The exception is the first line, where we substitute START, since you don't have to take any road to get to your starting point.

These files should be given a .pth extension. Once such a file is created, it can be visualized by directing a browser at /chm/viewer/ and uploading the .pth file in the file selection box at the top of the page.

Printing human-readable directions is worth 20 points, and generating a .pth file is worth 5 points.


Before 6:00 PM, Wednesday, December 9, 2015, submit your lab for grading. There are two things you need to do to complete the submission: (i) Copy your file with the answers to the lecture assignment and lab questions into your project directory. Be sure to use the correct file name. If you prepared your answers in Word, export to a PDF file and submit that. (ii) Email a copy of your lab (a .7z or .zip file containing your project directory) to terescoj AT Please use a meaningful subject line such as "Joe Student Lab11 Submission".


This assignment is worth 145 points, which are distributed as follows:

> FeatureValueScore
LA Question 1 (13.12) 2
LA Question 2 (13.20) 2
LA Question 3 (14.14) 2
LA Question 4 (AVL Tree insert 31,32) 3
LA Question 5 (AVL Tree insert 32,31) 3
LA Question 6 (AVL Tree example) 3
LA Question 7 (15.2) 2
LA Question 8 (15.6) 2
LA Question 9 (15.8) 2
LA Question 10 (15.12) 2
LA Question 11 (15.16) 2
Question 1 (Dijkstra's Algorithm Practice) 10
Question 2 (heapify) 5
Question 3 (complete heapsort) 5
Question 4 (Generalized Heapsort) 10
LittleGraph Practice Program 4
Question 5 (WaypointBest map screen captures) 7
Question 6 (which Graph and why) 2
Mapping graph construction 9
Mapping listPlaces method 3
Mapping listConnections method 3
Mapping Stats method 12
Mapping Print{Shortest,Longest}Edges commands 12
Mapping Map{Shortest,Longest}Edges commands 5
Mapping FindRoute command 20
Mapping MapRoute command 5
Mapping style, documentation, and formatting 8
Total 145