Green Laser was apart of my masters thesis and an ongoing project I hope to contribute to in my spare time for a long time to come. The idea is that when shopping, consumers generally don’t have a strong indication as to whether the products they purchase are “green” or not. Our approach was to use every existing rating for any barcode-equipped item in existence and to push that data into the form factor of a mobile device empowered with a barcode scanner. The resulting product was “Green Laser,” which, while ambitious in it’s goal, we think enables consumers to quickly and readily decipher rating information by simply scanning an item. We have many future plans for allowing contributions of data to this project and new features to be built on various mobile platforms in the weeks to come.
The Mutli-Language Metrics Tool is exactely that—a tool for analyzing multiple-programming languages within a system. Our group put the .NET framework, various programming languages (C#, VB, J#) and a nice GUI on top of some disassembled code (with the use of Microsoft’s ILDASM tool) to churn out metrics relating to a system, such as percentages of programming language use, ratios of variables to class sizes, and much more. Read all about it in the paper published at IASTED.
It may seem like a weird project—how are programming languages at all… musical? For my graduate programming languages course I decided to do a survey on the topic. Everything from “Live Programming” (a performance-based form of coding) to aspect-oriented programming is mentioned with a good bit of detail. Anytime one gets to play the star wars theme as part of an explanation to a class of computer scientists is research well spent!
I worked with Bogdan Alexe, a PhD student at UCSC on a project in a cloud computing course called “SQLTurk.” Bogdan and I looked into using Amazon’s Mechanical Turk as a platform for converting natural language queries into semantically correct SQL. To date, research has been rather stagnant in the attempt to do this conversion process, so we proposed using human processing units instead. In the end we came up with a set of workflows which allowed for query-writers on Mechanical Turk to either write a natural language query or vote on a group of semantically valid submissions from other workers. We were able to recover a rather good chunk of data which validated our approach of inserting humans as “mini-computers” in a completely automated form. Read the project for more info!
I worked with Ian Adams on a project for a course with Dr. Jim Whitehead titled “Generative Programming.” We worked mainly in Czarnecki and Eisenecer’s Generative Programming: Methods, Tools and Applications book, but ready a steady stream of conference and pivotal papers in the research area as well. Our project consisted of addressing the utility of utilizing two “generative” programming languages coupled together. In summary, our aim was to look at a method for reducing massive code being generated by the use of feature-oriented programming (FOP) with the introduction of aspect-oriented programming (AOP).
In my computer networks graduate course with Dr. Varma, I looked into analyzing how Snort (an open-source Intrusion Detection System) can continually handle deep-packet inspection as signature sets (i.e. virus definitions) increase. Some network intrusions could occur by overloading an IDS with more traffic than it can handle, such that malicious packets are allowed to flow into a network without being inspected. My goal was to investigate this anomally and to see whether or not Snort is up to the challenge of protecting small- to mid-sized businesses.
I worked with Dr. John Musacchio and Ning Bao on a game-theoretic model for understanding potential courses of action a network administrator could take when knowledge of an intrusion has occured. Does one try to place an intruder in a virtual environment for observation? Are honeynets the best means of deterring attention from critical network locations? Is it best to just kick out attackers whenever they are found? My goal was to investigate metrics that can be used to analyze the knowledge a network administrator has access to in a “perfect” environment—i.e. an environment with an array of intrusion detection systems, firewalls, and endless more technologies galore.
When taking a course, “E-Business Technology & Strategy”, my partner Keven Woo and I decided that geo-locations were all the rage, so why not make a project out of it? We submitted a project, “Location Finder” (the name could use a bit of work), in which a user could have his/her location mapped out within larger campuses and buildings from a cell-phone. The difference between our idea and a off-the-shelf GPS device, was that we wanted to do it with a cell-phone and wifi network. It’s still rough around the edges, but an interesting proposal, nonetheless.