Programming Assignment Checklist: Markov Model of Natural Language

Revised for Fall 2012

Pair programming. On this assignment, just like the last one, you are encouraged (not required) to work with a partner provided you practice pair programming (same rules as last assignment).

Frequently Asked Questions

What are the main goals of this assignment? Use a symbol table, learn about natural language processing, and learn about Markov models.

What is the origin of the Markov text generator? It was first described by Claude Shannon in 1948. The first computer version was apparently written by Don P. Mitchell, adapted by Bruce Ellis, and popularized by A. K. Dewdney in the Computing Recreations section of Scientific American. Brian Kernighan and Rob Pike revived the program in a University setting and described it as an example of design in The Practice of Programming. The program is also described in Jon Bentley's Programming Pearls.

Do I have to implement the prescribed API? Yes, or you will lose a substantial number of points.

How do I read in the input text from standard input? Use StdIn.readAll().

Given a string s, is there an efficient way to extract a substring? Use s.substring(i, i+k) to get the k-character substring starting at i. In Java, this operation takes constant time, regardless of the size of k.

How do I emulate the behavior of a circular string? There are a number of approaches. One way is to concatenate the first k characters to the end of the input text.

How do I convert a char to an int? A char is a 16-bit (unsigned) integer. Java will automatically promote a char to an int if you use it as an index into an array.

How do I use StdRandom.discrete() to pick the next character? The argument to StdRandom.discrete() needs to be a double[] holding the probabilities of each character being next. StdRandom.discrete() will return an integer which is the index of the random pick based on those probabilities. That index is the integer value of the next character.

My rand() method calls StdRandom.discrete() as recommended in the Possible Progress Steps, but I get the following error message when I run: java.lang.AssertionError. What does that mean? It means that the probabilities don't sum up to 1. Double check how you are computing the values for the array you send to StdRandom.discrete(). The array elements are the probabilities of each possible event, so the sum of the array elements should be 1. (To learn how to use assertions, see pp. 446-447.)

Should my program generate a different output each time I run it? Yes.

My random text ends in the middle of a sentence. Is that OK? Yes, that's to be expected. We recommend using a StdOut.println(); statement to ensure that there is a new line generated after the last character.

For which values of k should my program work? It should work for all well-defined values of k from and including 0 to and including the length of the input text. Naturally, as k gets larger, your program will use more memory and take longer.

I get an OutOfMemoryException. How do I tell Java to use more of my computer's memory? Depending on your operating system, you may have to ask the Java Virtual Machine for more main memory beyond the default.

% java -Xmx100m TextGenerator 7 1000 < input.txt
The 100m means 100MB, and you should adjust this number depending on the size of the input text.

What is a StringBuilder object? StringBuilder is part of the standard Java library. It is an object that we use because of its more efficient handling of large strings. Here is a subset of the StringBuilder API with some methods you might find useful for this assignment.

public class StringBuilder
              StringBuilder(String s) // create a StringBuilder initialized to the contents of String s
StringBuilder append(char c)          // append the string representation of the char to this sequence
String        toString()              // returns a String representing the data in this sequence


Thoroughly test your MarkovModel. We provide a main() as a start to your testing.

    public static void main(String[] args) {
        MarkovModel mod1 = new MarkovModel("i am sam. sam i am", 3);
        StdOut.println("freq(\"sam\", ' ')    = " + mod1.freq("sam", ' '));
        StdOut.println("freq(\"sam\", '.')    = " + mod1.freq("sam", '.'));
        StdOut.println("freq(\"mi \")         = " + mod1.freq("mi "));
        StdOut.println("freq(\"sam\")         = " + mod1.freq("sam"));

        String text = "now is the time. now is the time to eat. " 
                    + "now is the time to live.";
        MarkovModel mod2 = new MarkovModel(text, 7);
        StdOut.println("freq(\"now is \", ' ') = " + mod2.freq("now is ", ' '));
        StdOut.println("freq(\"now is \", 't') = " + mod2.freq("now is ", 't'));
        StdOut.println("freq(\"now is \")      = " + mod2.freq("now is "));
If your method is working properly, you will get the following output:
%java MarkovModel
freq("sam", ' ')    = 1
freq("sam", '.')    = 1
freq("mi ")         = 1
freq("sam")         = 2

freq("now is ", ' ') = 0
freq("now is ", 't') = 3
freq("now is ")      = 3

Note that this does not test your rand() or gen() methods.

You can use print statements to test rand() to make sure that each non-zero entry of the array passed to StdRandom.discrete() is accurate. (But make sure to remove these print statements from your rand() method before submitting your code.)

To test gen(), use a text that has no repetition (e.g., "abc") and set order k=1. This should only be able to generate text where "a" is followed by "b", "b" is followed by "c", "c" is followed by "a". Then use a text with easy to compute repetition (e.g., "abac"). It should generate "a" followed half the time by "b" and half the time by "c". "b" or "c" should always be followed by "a".

An order-0 Markov model generates a random sequence of letters where each letter appears with probability proportional to its frequency in the input text. For input17.txt there are 9 g's, 7 a's, and 1 c. So we want the probability of generating a 'g' to be 9/17, an 'a' to be 7/17, and a 'c' to be be 1/17. In a sequence of 100 characters, we'd therefore expect on average about 53 g's, 41 a's, and 6 c's.

% java TextGenerator 0 100 < input17.txt

For input17.txt, the next character after "ga" is 'a' with probability 1/5 and 'g' with probability 4/5. If you run the following command 10 times, you should expect (on average) to see "gag" 8 times and "gaa" 2 times.

% java TextGenerator 2 3 < input17.txt

Possible Progress Steps

These are purely suggestions for how you might make progress. You do not have to follow these steps.

  1. Download the directory markov. It contains a number of sample text files, along with this assignment's readme.txt template. You will be using, which is in the directory. You might also want to use, but it is a part of stdlib.jar, so you probably won't need to download it.

  2. Review the material in the textbook on symbol tables as well as

  3. Create an instance variable for your symbol table where the key is a string and the value is an integer array. Each entry of the integer array is a count of frequencies (how many times one character appears after the key in the text).

  4. Write your constructor to create the circular version of the text string. Then initialize and populate your symbol table, using the symbol table methods contains(), get() and put().

  5. Write the order() method. This should be a one-liner.

  6. Using the symbol table instance variable, write the freq() methods.

  7. Using the main() provided above test this part of your MarkovModel data type before continuing. You may wish to add more testing of the constructor and freq() methods.

  8. Write the rand() method. To generate a random character with probability proportional to its frequency you may call or refer to StdRandom.discrete() on p. 226 of the textbook.

  9. It may not be obvious from your final results if rand() is working as you intended, so be sure to test it thoroughly. Then test your complete MarkovModel data type before continuing.

  10. Write the gen() method. To generate a trajectory, create a StringBuilder object which consists of the kgram argument. Then write a loop to generate the remaining characters, one character at a time using other methods from MarkovModel and append each character to the StringBuilder object. (Do not use String concatenation. It is very slow.) You will need to convert the StringBuilder object to a String object to match the method return type.

  11. Write the client program Create an instance of the MarkovModel class with the string read from StdIn. Use the gen() method from the MarkovModel class to generate a T-character trajectory. Output the trajectory, followed by a new line.