Applied math and probability project for discrete math/theoretical foundations of computer engineering (CprE 310).
Creating configurable packaged Java applications runnable from the command line; understanding of the basic PageRank algorithm, automated program performance testing
My compiled code can be found here.
This was a free-form programming project in which I was to design an implementation of the PageRank algorithm to run on edge files, which contain two whitespace-delimited node indices per line, where each line is a directed edge from the first index to the second index. I chose to implement the traditional iterative version of PageRank, but opted to implement a Monte Carlo simulation in order to compare results between the different representations of popularity of a particular page. I enjoyed configuring this as a command line utility, providing various optional arguments to the user that configured the variables in the algorithms. As no specification was given as to how to accomplish this implementation, I researched the algorithm and processed simple examples by hand in order to ensure my understanding of its functionality. I wrote out simple pseudocode of a linked node graph implementation, set up my class structure, and then fleshed out the code. In order to ensure the accuracy of my implementation, I compared my results to my own hand calculated examples, an online PageRank calculator, and the results of my peers’ independent implementations. I wrote a generator class to produce random edge files of provided specifications that allowed automation of performance testing. This project demonstrated to me the apparent difficulty of retrieving relevant searches on massive-scale data.
My project presentation, with more complete details and analysis is embedded below.