For this project you need to implement two different variations of Randomized Selection. Your Selection algorithms must work correctly on any length input we provide, and needs to try to run as quickly as possible on any data that is Comparable. We are not assuming unique elements in the lists for this project.

For simplicity of debugging and testing, we are using integers. However, if your code would not also work (for example) on strings, your project will not be considered as correct.

This project will have three files; two that we provide that you cannot change, P1driver.java and CMSC351P1lib.class, and one in which you will write your code to implement Selection, CMSC351P1.java. We have added a JAR file containing that class file in case you need that for a newer version of Eclipse to be happy. You can add any helper methods to this class that you wish, and you can use the Java class Random to generate random numbers. You can also use other random number libraries, or implement random number generation algorithms you find elsewhere (document where you get them from). Within your code, anywhere a comparison to a data value takes place, you must increment the counter called comps in the CMSC351P1 class. If there are data comparisons that are not counted, your project will lose points. Anywhere you use a random number, you must increment the rands counter. If there are random numbers created that are not counted, your project will lose points.

There are several ways in which a randomized Selection could be implemented. You can also "mix and match" techniques of randomization, and/or use more than one random number generator. You are required to submit a PDF file named README.pdf with a one-page description of the technique(s) you used, and an explanation of why you chose to use them. Additionally, you should indicate which of the two algorithms you implemented is better than the other, and whether either (or both) is better than the select we provided in the library. If you find that there are certain situations in which one is better than the others, describe those situations. You may include any graphs of your experiments that you'd like to show your work. To create a PDF file from a word processing document, you can install the free CutePDF Writer virtual printer on a Windows machine, or print to PDF on a Mac.

• Your primary goal is to have an actual running time (in terms of data comparisons) that has a small linear coefficient on all inputs. Again, for comparison purposes, we have provided a selection algorithm in the library CMSC351P1lib that doesn't use any random numbers, and runs in reasonably fast linear time on average, using the Median-of-Medians technique. 
• Your secondary goal is to use at most linear additional memory space in your work. 
• Your final goal is to avoid too many costly computations (such as computing lots of random numbers) that might not increase the number of comparisons, but would increase the actual clock time for your program. 

You will submit a ZIP file containing your CMSC351P1.java and your README.pdf files using the submit.cs.umd.edu server. Some primary inputs are posted below. You can test your submission using those. You should also create your own inputs to try to look for "bad" input scenarios, and then try to modify your algorithm if it does not perform well. Grading will be based on (a) your program actually finds the specified value correctly for all of the input lists we generate, (b) the correctness of your comparison counting which will be determined by the teaching assistants reading your code, (c) the efficiency of your code across inputs, and (d) your written description and discussion of the techniques you used.

The following are links to some input files: in1, in2, in3, in4, in5, in6. This is a non-exhaustive set of input scenarios. There will also be a second set used during testing of submitted projects. Again, we suggest you develop your own test suite.

We're planning on doing grading on the GLUE cluster using Java 1.5 so if you test it there and it compiles and works, then it should for us as well.