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Second-Year-CSSE-NUIM

Algorithms and Data structures 2 labs, 2016

These are some of the lab questions are given in second semester CSSE Algorithms and DataStructres 2. Each number corresponds with a partner .java files


lab 1

Grab a stick. Pick a random point on the stick and break it in two. Take the longer piece. Now pick a random point on the longer piece and break it in two, to make three pieces altogether. What is the probability you can form a triangle?

lab 2

The task is to complete the Huffman algorithm so that it takes in a sentence and outputs Huffman codes. Several chunks of the code are missing in Huffman.java: i) Fill in the code that creates the forest of trees for each letter and adds them to the Priority Queue ii) Fill in the code that implements the Huffman algorithm iii) Fill in the code that prints out all the results, including the rate of compression achieved When you have all that finished the output of your program should look like this: Enter your sentence: The cats did not sit on the mat

lab 3

Make yourself unbeatable at Scrabble by writing a computer program that uses your letters to make the longest words possible and gives you the top 10 suggestions, using dictionary .txt

lab 4

Objective 1: To get the system working properly you need to create a decent hash function. Modify the method getHashKey( ) so that it creates a unique number for each word and then hashes it into the appropriate range. Use the modPow( ) method if you are using modulo with large powers. The hash function should always produce a value between 0 and the hash table size. Test to see if the number of collisions has been reduced. Objective 2: If you want to use double hashing then you need a double hash function. Modify the method getDoubleHashKey( ) so that it is based on more characters than just the last one. Remember, the important features of a secondary hash function are that it is different to the primary hash function (so that different items colliding into a particular slot will follow different jumps) and never produces a 0 (so that it doesn’t keep checking the same slot forever). The number that is returned by the function is the size of the jumps that will be taken in case of a collision. Test to see if the number of collisions has been reduced. For full marks, get the number of collisions below 90,000, while keeping the load factor above 0.5.

lab 5

Write a program that identifies the following:

  1. The S&P 500 company with the lowest drawdown between 2008 and mid- 2011, the actual percentage, and the dates between which it occurred
  2. The S&P 500 company with the highest drawdown between 2008 and mid- 2011, the actual percentage, and the dates between which it occurred A drawdown is the peak-to-trough decline during a specific record period of an investment, fund or commodity. A drawdown is usually quoted as the percentage between the peak and the trough. Use the data in the file StockData.txt. The following code can be used for loading it in:

lab 6

Say you start rolling a dice. On average you will need 6 rolls to get a 6. But what if, during the process of rolling for a 6, you get a Snapchat? Given that you received a Snapchat at some point during the rolling process, how many rolls will you need on average to get a 6? Now let’s make it a bit more interesting. What if you sneeze and get a Snapchat while you’re rolling for a 6. Now how many rolls will you need on average to get a 6? One way to answer these questions is to actually roll a dice and wait for these events to happen. Another quicker way is to write a Monte Carlo algorithm.

lab 7

W10ite a program that reads in a file representing a connected undirected weighted graph in the form of an adjacency matrix and outputs the longest path between any two vertices in the graph. For example, if you load in the file graph.txt the output should look something like this: 20 EBCJ The idea is to find the two vertices for which the shortest distance between them is as long as possible. For example, in the graph the shortest distance between E and J is 20. There are no other vertices whose shortest path is as long as this. For any other two vertices, there will be a path between them which is shorter than 20. In effect, all that needs to be done is to run Dijkstra’s algorithm for every possible starting position and find the longest Dijkstra path between any two vertices. This code might be useful as a guide, but it also might be best to code the algorithm from scratch. Just code up what you do on paper, loop for all starting positions, and output the longest Dijkstra path in the graph.

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Algorithms and Data structures 2 labs, 2016

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