To understand the innerworkings and implementation of the LZW compression algorithm, and to gain a better understanding of the performance it offers.




To understand the innerworkings and implementation of the LZW compression algorithm, and to gain a better understanding of the performance it offers.

High-level description:

As we discussed in lecture, LZW is a compression algorithm that was created in 1984 by Abraham Lempel, Jacob Ziv, and Terry Welch. In its most basic form, it will output a compressed file as a series of fixed-length codewords. This is the approach implemented in the LZW code provided by the authors of the textbook. As we discussed in class, variable-width codewords can be used to increase the size of codewords output as the dictionary fills up. Further, once the dictionary fills up, the algorithm can either stop adding patterns and continue compression with only the patterns already discovered, or the algorithm can reset the codebook to find new patterns. The LZW code provided by the textbook authors simply continues to used patterns added to the codebook.

For this project, you will be modifying the LZW source code provided by the authors of the text book to use variable-width codewords, and to optionally reset the codebook under certain conditions. With these changes in hand, you will then compare the performance of your modified LZW code with the provided LZW code, and further with the performance of a widely used compression application of your choice.


  1. First make a copy of named “”. You will be modifying this file for your assignment. Note that is the example LZW code provided by the textbook.
  2. Before making the required changes to, you will need to read through the code, and run example compressions/decompressions to understand how it is currently working. Note that (and hence your requires the following library files (also developed by the textbook authors):,,,,, and Note that these files have already been added to your repository.
  3. With a firm understanding of the provided code in hand, you can proceed to make the following changes to
    1. Make it so that the algorithm will vary the size of the output/input codewords from 9 to 16 bits.
    2. The codeword size should be increased when all of the codewords of a previous size have been used
    3. Modify the code to have three options when the codebook is filled up (i.e., all 16 bit codewords have been used):
      1. Do Nothing mode Do nothing and continue to use the full codebook (this is already implemented by
      2. Reset mode Reset the dictionary back to empty so that new codewords can be added. Be careful to reset at the appropriate place for both compress and decompress, so that the algorithms remain in sync. This is very tricky and may require a lot of testing/debugging in order to get it working correctly.
      3. Monitor mode Initially do nothing (keep using the full codebook) but begin monitoring the compression ratio after no more 16 bit codewords remain. Define the compression ratio to be the size of the original data divided by the size of the (compressed) output data. At any point in time, the size of the original data is simply the number of bytes that have been read in. The size of the output data can also be easily calculated, and is based on the number of codewords output and the size of each (which will change as the algorithm progresses). If the compression ratio degrades by more than a set threshold from the point when the last codeword was added then reset the dictionary to empty. To determine the threshold for resetting you will take the ratio of compression ratios [(old ratio)/(new ratio)]. If the ratio of ratios exceeds 1.1 then you should reset. For example, if the compression ratio when you start monitoring is 2.5 and the compression ratio at some later point is 2.3, the old compression ratio is 2.5/2.3 = 1.087 times the new one, so you should not reset the dictionary. Continuing, if your new compression ratio drops to 2.2, the old ratio is now 2.5/2.2 or 1.136 times the new one. This means that your ratio of ratios has exceeded the threshold of 1.1 and you should now reset the dictionary. As with the changing of the codeword bits, be very careful to coordinate the code in your compress and expansion so it works correctly.
    4. Which mode should be used should be chosen by the program during compression. Whichever mode is used to compress a file should also be used to expand the file. However, you should not require the user to state the mode on expansion. The mode used to compress a file should be stored at the beginning of the output file, so that it can be automatically retrieved during expansion. To establish the mode to be used during compression, your program should accept 3 new command line arguments:
      1. “n” for Do Nothing mode
      2. “r” for Reset mode
      3. “m” for Monitor mode
    1. Note that the provided LZW code already accepts a command line argument to determine whether compression or expansion should be performed (“-” and “+”, respectively), and that input/output files are provided via standard I/O redirection (“<” to indicate an input file and “>” to indicate an outout file). Hence, your new arguments should be handled in addition to what is provided. For example, to compress the file foo.txt to generate foo.lzw using Reset mode, you should call:

java MyLZW – r < foo.txt > foo.lzw

Similarly to inflate foo.lzw into foo2.txt, you should run:

java MyLZW + < foo.lzw > foo2.txt

Note that this example does not overwrite foo.txt. This is a good approach to take in testing your programs so that you can compare foo.txt and foo2.txt to ensure that they are the same file.

  1. Once all of the required changes have been made to, you should evaluate its performance on the 14 provided example files: all.tar, assig2.doc, bmps.tar, code.txt, code2.txt, edit.exe, frosty.jpg, gone_fishin.bmp, large.txt, Lego-big.gif, medium.txt, texts.tar, wacky.bmp, and winnt256.bmp. Specifically, for each of the provided example files, measure the original file size, compressed file size, and compression ratio (original file size / compressed file size) when compressed using the following techniques:
    1. The unmodified program (i.e., 12 bit codewords)
    2. Your (variable width codewords) using Do Nothing mode
    3. Your (variable width codewords) using Reset mode
    4. Your (variable width codewords) using Monitor mode
    5. Another existing compression application of your choice (e.g., 7zip, WinZIP, gzip, bzip2) You should organize your results of these compressions/inflations into a table in a text file named “results.txt” and submit it along with your code.

Submission Guidelines:

  • DO NOT SUBMIT any IDE package files.
  • You must name the primary driver for your program
  • You must be able to compile your game by running “javac”.
  • You must be able to run your program as shown in the above example.
  • You must fill out info_sheet.txt.
  • Be sure to remember to push the latest copy of your code back to your GitHub repository before the the assignment is due, the repositories will automatically be copied for grading. Whatever is present in your GitHub repository at that time will be considered your submission for this assignment.

Additional Notes/Hints:

  • In the author’s code the bits per codeword (W) and number of codewords (L) values are constants. However, in your version you will need them to be variables. Clearly, as the bits per codeword value increases, so does the number of codewords value.
  • The TST the author uses can grow dynamically, so it does not matter how large the dictionary will be. However, for the expand() method an array of String is used for the dictionary. Make sure this is large enough to accommodate the maximum possible number of codewords.
  • Carefully trace what your code is doing as you modify it. You only have to write a few lines of code for this program, but it could still require a substantial amount of time to get to work properly. Clearly the trickiest parts occur when the bits per codeword values are increased and when the dictionary is reset. I recommend tracing these portions of code, either on paper or with output statements to make sure your compress and expand sections are treating them correctly. One idea is the have an extra output file for each of the compress() and expand() methods to output any trace code. Printing out (codeword, string) pairs in the iterations just before and after a bit change or reset is done can help you a lot to synchronize your code properly.
  • Be especially careful with the dictionary reset and monitor compression ratio options. These are very tricky and take some thought and some trial and error to get to work. Think about what happens when the dictionary is reset and what is necessary to do in the compress() and expand() methods. I recommend getting the variable width codeword part of the program to work first and then moving on to implementing Reset mode and Monitor mode.
  • Start on this project early! Not only will the implementation be tricky, but you will need to finish the programming portion of your project with enough time left over to gather results using your code to compress the example files.
  • Note that (and consequently your rely on redirecting standard in and standard out to the input and output files (respectively). An overview of I/O redirection can be found here:, and here: Note that a consequence of this is that any text printed to standard out (i.e., via System.out.println()) will be redirected to the output file instead of the terminal. Standard error, however, should still be displayed to the terminal, and hence, you can use System.err.println() to output debugging information. This I/O redirection may also complicate running MyLZW from some IDEs. If you are having trouble running MyLZW from your IDE, please try to run your program from the command line.
  • Consider the notes in (and concerning the speed of the substring() function. In order to run your experiments faster, you may want to edit ( and to remove all calls to substring(). There is no penalty for continuing to use substring() for this assignment, but you will experience noticeably slow performance.