Clinic Projects

Please click on a link below to view the Harvey Mudd College Computer Science Clinic projects for the corresponding time period.

Clinic Projects for 2004-2005

PCRNet 2.0

Client
Applied Biosystems

Faculty Advisor
Professor Belinda Thom

Student Team
Jacob Seene (Project Manager), Timothy Chew, Krislin Lee, Paul Scott
PCR (Polymerase Chain Reaction) Net is a piece of software used to monitor and control GeneAmp PCR 9700 instruments. These instruments, inturn, are used to amplify DNA samples. Amplified DNA samples can be analyzed and then used in forensic analysis, gene sequencing, and genetic defect determination. The team enchanced PCRNet by improving the user interface, extending the error logging capabilities, and enabling core features of the application to be run across a local network.

Constrained Optimization in Convex Programming

Client
Fair Isaac Corporation

Faculty Advisor
Professor Ran Libeskind-Hadas

Student Team
Brian Tagiku (Project Manager), Dave Buchfuhrer, Dan Halperin, Brad Tennis, Chris Weisiger
Fair Isaac Corporation provides companies with mathematically-based solutions for a variety of business problems. Many of these problems can be modeled using quadratic programs with large numbers of variables and linear constraints. The team has taken on the task of developing a prototypical software package that solves linear and quadratic programs. A number of algorithms have been incorporated into this package to accurately solve these types of problems.

Differential Test Coverage Analysis in the Context of the Wine Project

Client
Google, Inc.

Faculty Advisor
Professor Elizabeth Sweedyk

Student Team
Cal Pierog (Project Manager), Aaron Arvey, Edward Kim, Evan Parry
This project will help ensure that Google's Windows applications run properly under Wine, which is a program that allows Windows programs to run under Linux. The team improved coverage tools to identify areas of untested code used by an application. The team also used these new tools to identify bugs in Wine that affect Google applications, focusing on the Picasa application.

Distributing Search in a Document Database

Client
Laserfiche

Faculty Advisor
Professor Zachary Dodds

Student Team
Adam Kangas (Project Manager), Janna DeVries, Joseph Walker, Kamil Wnuk
As organizations make the shift from paper documents to electronic document imaging systems, the size of electronic document repositories is constantly growing. This team has researched distributed methods for reducing the amount of time required to perform full-text searching in large document databases.

Mesh Optimizatiion Algorithms for Parallel Computing with MESQUITE

Client
Sandia National Laboratories

Faculty Advisor
Professor Melissa O'Neill

Student Team
Dominik Slusarczyk (Project Manager), Elisa Celis, John Hicks, Yu-Min Kim
This Clinic project extended the MESQUITE mesh smoothing toolkit developed by Sandia National Laboratories to operate on a distributed processing cluster. Parallel smoothing requires efficient partitioning of meshes into subparts, correct smoothing of those subparts, and effective cross-cluster synchronization during and after computation. The project drew on existing research in the field of distributed mesh smoothing and on established tools, including MESQUITE itself, the Zoltan partitioning toolkit, and the MPI toolkit for distributed computing. Distributed computation would be pointless without speedup over ordinary singe-CPU computation, so the team also developed and deployed performance analysis methods which have inspired further optimizations to the code.

Grid-Enabling the VISPERS Application

Client
The Aerospace Corporation

Faculty Advisor
Professor Robert Keller

Student Team
Brian Bentow (Project Manager), Jon Dodge, Aaron Homer, Chris Moore
The team designed and implemented a version of waveform analysis tool, VAIL, based on the "grid" highly-parallel computing paradigm, using the Globus toolkit. VAIL is part of a larger system that analyzes real-time sensor data to characterize the vibroacoustic shock environment of launch vehicles. The team conducted a performance analysis of the grid-enabled tool, measured speedup, and analyzed communication bootlenecks. They also researched and surveyed the current state-of-the-art in grid computing tools and provided a study to facilitate future grid implementations by The Aerospace Corporation.

Modeling and Simulation of GPS

Client
The Boeing Company

Faculty Advisor
Professor Michael Erlinger

Student Team
Victoria Krafft (Project Manager), Tarun Abhichandani, Brian Merdian, Trudi Miller, Sonya Zhang
The current United States Air Force's Global Postioning System (GPS) consists of earth-orbiting satellites and a world-wide network of monitoring stations. The team developed a simulation model representing the GPS using the OPNET network modeling platform. The model has been verified via data provided by Boeing and other sources. The team created a set of "what if" scenarios and applied them to the GPS model to evaluate possible modifications to the GPS infrastructure.