I am a researcher at the Robust Software Engineering group at the NASA Ames Research Center in California. I graduated with my PhD from Brigham Young University in the Computer Science department.
- C. Pasareanu, N. Rungta, and W. Visser,
Symbolic Execution with Mixed Concrete-Symbolic Solving
In International Symposium on Software Testing and Analysis (ISSTA), July 2011 (To Appear).
- S. Person, G. Yang, N. Rungta, and S. Khurshid,
Directed Incremental Symbolic Execution
In 32nd ACM SIGPLAN conference on Programming Language Design and
Implementation (PLDI), June 2011 (To Appear).
- T. Fischer, E. Mercer, and N. Rungta,
Symbolically Modeling Concurrent MCAPI Executions
In 16th ACM SIGPLAN Annual Symposium on Principles and Practices of Parallel Programming,
San Antonio, Texas, February 2011.
My research on guided test provides a potentially scalable systematic verification technique that uses information derived automatically from the source of the programs to intelligently test parts of the behavior space that are more likely to contain an error. The algorithm is an abstraction refinement technique that uses as input potential errors generated by imprecise, but scalable, static analyses. The symbolic execution is then guided through the program to check the feasibility of the error. A class of heuristics and stochastic methods have been developed to improve the rate of error discovery by the guided symbolic execution technique. The guided test is implemented within the Java Pathfinder (JPF) model checker .