Active Projects »

Exploring Applications of Symbolic Execution to Testing, Debugging and Patch Validation

As a first step, we are investigating an approach to runtime information flow analysis for managed languages that tracks metadata about data values through the execution of a program.  We first considered metadata that propagates labels representing the originating source of each data value, e.g., sensitive data from the address book or GPS of a mobile […]


Reducing Testing Overhead

Unit test virtualization: significantly reducing the time to setup unit tests


Graphical Analysis of Program Behaviors to Discover Opportunities for New APIs

A joint project encompassing computer architecture, machine learning and software engineering


Finding Bugs in Machine Learning, Data Mining and Big Data Applications

Automating metamorphic testing techniques at runtime


Post-Deployment Checking for Bugs, Security Vulnerabilities and Privacy Breaches

Executing tests in the deployment environment, using the state of the running application


A joint project with Profs. Gail KaiserJohn Kender and Jason Nieh.

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