CSCI 136 - Fall 2019
Data Structures & Advanced Programming
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This week we will continue to build our skills with the command line and git.
We will write a program with several classes. This week’s lab program will analyze letter frequencies in text documents and then generate new documents based on those frequencies. Each class will implement unique functionality and together they will solve a larger problem.
We will explore what is called a has a relationship: where one class has a member variable that stores an instance of another class. Careful planning will help tremendously, so take the time to write a well thought-out design document before arriving for lab.
staticThere is nothing to hand in for this part of the lab, but make sure you understand the following.
What is printed by the following program?
class Example {
public int num;
public Example(int initial) {
num = initial;
}
public int getNum() {
num = num + 1;
return num;
}
public static void main(String args[]) {
Example first = new Example(10);
Example second = new Example(20);
System.out.println(first.getNum());
System.out.println(second.getNum());
}
}What would be printed if the declaration of num were changes as follows? public static int num;
What does this tell you about static fields?
Be sure to ask your TAs and instructors if you have any questions. The static keyword is one of the more confusing features of the Java programming language, but it is an important concept that will show up in all of our labs (and exams!).
Browse the javadoc documentation for the structure5 classes. Look up the Vector and Association classes. Become familiar with how to look up information on classes in the structure5 package. For this lab, we link to the documentation directly for convenience. Learn how to navigate the documentation yourself, as in future labs we will assume that you know where to find documentation.
Please read through the rest of this document before lab. You should prepare a written design for your program before lab on Wednesday. You must think about this lab before writing code! In the past, students have found it very helpful to draw a picture showing the relationship between each of the classes.
Be sure to bring two printouts of your design document to lab, as we will be collecting one of them during lab.
By the start of lab, you should see a new private repository called cs136lab2-USERNAME in your GitHub account (where USERNAME is replaced by your GitHub username). Submit answers to the following book questions inside Problems.md, a file that was included in the Lab 2 starter code. (Note the difference between Self Check problems and Regular problems in the book!):
Consider the following three quotes:
Call me Ishmael. Some years ago–never mind how long precisely–having repeatedly smelt the spleen respectfully, not to say reverentially, of a bad cold in his grego pockets, and throwing grim about with his tomahawk from the bowsprit?
Call me Ishmael. Some years ago–never mind how long precisely–having little or no money in my purse, and nothing particular to interest me on shore, I thought I would sail about a little and see the watery part of the world.
Call me Ishmael, said I to myself. We hast seen that the lesser man is far more prevalent than winds from the fishery.
The second quote is the first sentence of Herman Melville’s 1851 novel, Moby Dick. The other two quotes were generated “in Melville’s style” using a simple algorithm developed by Claude Shannon in 1948 [footnote: 1]. You will implement Shannon’s algorithm in this week’s lab.
In addition to producing mildly entertaining output, this lab introduces you to:
Vector and Association classes,The following algorithm is based on letter probability distributions. Imagine taking the novel Tom Sawyer and counting the frequency with which each character occurs. You’d probably find that spaces are the most common, that the character 'e' is fairly common, and that the character 'q' is rather uncommon. After completing this level 0 analysis, you’d be able to produce Tom Sawyer-esque text based on character frequencies. The idea is to randomly select each character based on the probability of it’s occurrence in the text. This random text wouldn’t have much in common with the real novel, but characters would tend to appear with the same proportions. In fact, here’s an example of what a level 0 analysis might produce:
rla bsht eS ststofo hhfosdsdewno oe wee h .mr ae irii ela
iad o r te u t mnyto onmalysnce, ifu en c fDwn oee iteoNow imagine doing a slightly more sophisticated level 1 analysis by determining the frequency with which each character follows every other character. You would probably discover that 'h' is more likely to follow 't' than 'x', and you would probably discover that a space follows '.' more frequently than ',' does.
More concretely, if you are analyzing the text "the theater is their thing", 'e' appears after ’h' three times, and 'i' appears after 'h' one time; no other letters appear after 'h'. So, given this example,
'e' follows 'h' is 0.75,'i' follows 'h' is 0.25,'h' is 0.Using a level 1 analysis, you could produce randomly generated Tom Sawyer-esque text by 1) picking a character, and then 2) always choosing the next character based on the probability of the next character given the chosen character. Here’s an example of level 1 random text:
"Shand tucthiney m?" le ollds mind Theybooure
He, he s whit Pereg lenigabo Jodind alllld ashanthe ainofevids tre
lin--p asto oun theanthadomoereNow imagine doing a level k analysis by determining the probability with which each character follows every possible sequence of characters of length k. For example, a level 5 analysis of Tom Sawyer would reveal that 'r' follows "Sawye" more frequently than any other character. After a level k analysis, you would be able to generate Tom Sawyer-esque text by always choosing the next character based on the previous k characters and the probabilities revealed by the analysis.
At only a moderate level of analysis (levels 5—7), randomly-generated text begins to take on many of the characteristics of the source text. It probably won’t make complete sense, but you’ll be able to tell that it was derived from Tom Sawyer as opposed to, say, Moby Dick. Here are some more examples:
(Level 2:) "Yess been." for gothin, Tome oso; ing, in to
weliss of an'te cle - armit. Papper a comeasione, and smomenty,
fropeck hinticer, sid, a was Tom, be suck tied. He sis tred a
youck to themen
(Level 4) en themself, Mr. Welshman, but him awoke, the
balmy shore. I'll give him that he couple overy because in the
slated snufflindeed structure's kind was rath. She said that the
wound the door a fever eyes that WITH him.
(Level 6:) people had eaten, leaving. Come - didn't stand it
better judgment; His hands and bury it again, tramped herself!
She'd never would be. He found her spite of anything the one was a
prime feature sunset, and hit upon that of the forever.
(Level 8:) look-a-here - I told you before, Joe. I've heard
a pin drop. The stillness was complete, however, this is awful
crime, beyond the village was sufficient. He would be a good
enough to get that night, Tom and Becky.
(Level 10:) you understanding that they don't come around in
the cave should get the word "beauteous" was over-fondled, and
that together" and decided that he might as we used to do - it's
nobby fun. I'll learn you."
Once we have processed input text and stored it in a table structure that allows us to check probabilities, we pick k letters (for example, the first k in the input text) to use as a “seed” for our new text. Then we choose subsequent characters based on the preceding k characters and their probability information.
For now, we will focus on implementing a level 2 analysis. That is, we will compute the next character to print based on the previous two characters only.
Think about the design and prepare a written design description of this program. Just like last week, you should have your design prepared when you come to lab on Wednesday. We will briefly discuss the general structure of the classes together at the beginning of lab. We have provided implementation strategies below to help you decide which classes to include and what functionality each class should implement.
When thinking about the design, focus on what would constitute a good data structure for this problem. Your data structure needs to keep a table of info and be able to support two key operations:
You might try to save the frequency information in a big array, but the size will quickly become too large. For k = 2, you would need a three-dimensional array whose size is about 27,000 entries if you include blanks and punctuation. For larger k, the number of entries grows rapidly.
Instead, you will develop a Table class which is implemented as a Vector of Associations. Each Association should have a character sequence (stored as a String) as its key, along with a value which is a FrequencyList. FrequencyList is a class that keeps track of which characters appear after the given sequence, along with a frequency.
There are many ways to implement a frequency list. A good start is… another Vector of Associations. Thus the frequency list’s Vector consists of Associations in which the key is a single character (which can be stored simply as a String) and the value is a count of the number of times that the given letter occurs after the k-character sequence with which the list is associated (stored as an Integer). Think carefully about what methods the frequency list needs and any instance variables that might be useful.
The data structure design built from these two classes has the benefit of requiring only as many entries as necessary for the given input text. You may find it helpful to look carefully at the word frequency program in Section 3.3 of Bailey.
Your main method for the program should be written in a third class, WordGen, which reads the input text, builds the table, and prints out a randomly-generated string based on the character sequence probabilities from the input text.
To summarize, you will write three classes for this lab: Table, FrequencyList, and WordGen. The design doc you prepare should include a description of each of them. (In addition to text, you may also find it helpful to illustrate how the three classes interact with each other by creating a drawing or diagram.)
To ensure that your program can find the implementations of Vector and Association, you will need to add the following import statement to the top of your Java files:
import structure5.*;The * tells Java to import all classes inside the structure package. Note: To import the Random and Scanner classes use the following imports:
import java.util.Random;
import java.util.Scanner;In these latter imports, observe that there is no *, so only the specific class Random and the specific class Scanner will be imported from the java.util package. If you mistakenly write import java.util.*;, the Java compiler will produce an error message, since another Vector class is already defined in java.util. You must use the structure5 version of Vector for this assignment.
You should build your program in stages that you have planned out ahead of time. While writing and debugging your code, try using a fixed String constant as the input (e.g., "the theater is their thing") and use a fixed k = 2. Using these fixed parameters will help you ensure the correctness of your code since you can verify the correct answers by hand on paper.
After the input is processed you should generate and print out new text using the frequencies in the table. You may start with a fixed sequence of letters that appears in the table or choose starting characters randomly. Generate and print about 500 letters of randomly-generated text so that we can see how your program works. Be sure to handle the special case where you encounter a sequence that has no known successor character in a reasonable way (i.e., your program should not throw an exception).
Once the basic program is working, change it to accept input from the keyboard using the Scanner class. When using the Scanner, build up a string of the entire input line by line before performing any frequency analysis. You can use the hasNextLine() method to find out if there is another line of input ready and the nextLine() to read the next line if it exists, as in the following code snippet. (This code uses a StringBuffer to create large strings efficiently.)
Scanner in = new Scanner(System.in);
StringBuffer textBuffer = new StringBuffer();
while (in.hasNextLine()) {
String line = in.nextLine();
textBuffer.append(line);
textBuffer.append("\n");
}
String text = textBuffer.toString();
// 'text' now contains the full contents of the input.You can signal the end of the input for Java on the Mac or on any Unix system by typing Ctrl-D on a new line.
You may also read your input from any text file, e.g. whosonfirst.txt, with this command:
$ java WordGen < whosonfirst.txtThis way of reading files is not specific to Java. “Input redirection” can be used with any program running on any Unix system.
Finally, change WordGen to support any arbitrary level of analysis k other than 2. If you have designed the structure well, simply passing longer strings to Table’s methods should be sufficient, and you should not need to change any code except in the WordGen class.
You can also change your main method to use a command line parameter to specify the level of analysis. For example, it would be convenient to be able to run the program like so:
$ java WordGen 5 < whosonfirst.txtto specify a level 5 analysis. Command line options are passed to your main method as an array of strings. You can use the following skeleton code to ensure that there is at least one argument and to convert the first argument to an int:
public static void main(String args[]) {
if (args.length == 0) {
// no args, so print usage line and do nothing else
System.out.println("Usage: java WordGen ");
} else {
// convert first argument to k
int k = Integer.parseInt(args[0]);
// ... the rest of your code here ...
}
}When you are finished with your program, answer the questions from Step 0, and put your answers in a separate file called Problems.md. Commit and push Problems.md along with your other lab files as part of your repository. Your repository should have the files:
cs136lab02_wordgen-USERNAME/
FrequencyList.java
MISTAKES.md
Problems.md
README.md
Table.java
Wordgen.java
whosonfirst.txtIf you have a favorite text file you’d like us to try on your code, you can add it, too!
As you complete portions of this lab, you should commit your changes and push them. Commit early and often. When the deadline arrives, we will retrieve the latest version of your code. If you are confident that you are done, please use the phrase "Lab Submission" as the commit message for your final commit. If you later decide that you have more edits to make, it is OK. We will look at the latest commit before the deadline.
push. If not, go back and make sure you have both committed and pushed.We will know that the files are yours because they are in your git repository. Do not include identifying information in the code that you submit. We grade your lab programs anonymously to avoid bias. In your README.md file, please cite any sources of inspiration or collaboration (e.g., conversations with classmates). We take the honor code very seriously, and so should you. Please include the statement "I am the sole author of the work in this repository." in the comments at the top your Java files.
Instead of working at the character level, you could work at the word level. Only attempt this after you get the required work finished and be sure to submit it as a separate class so that we can grade your character-level analysis separately. Does this make the results better or worse in any way?
[1] Claude Shannon, “A mathematical theory of communication”, Bell System Technical Journal, 1948. Shannon’s technique was popularized by A.K. Dewdney’s A potpourri of programmed prose and prosody that appeared in Scientific American, 122-TK, 1989.