Software Development Team Leader, the Fraunhofer Center
5825 University Research Ct., Suite 1300, College Park, MD 20740
Dr. Song is a Software Development Team Leader at the Fraunhofer Center. His research interests include applications of static/dynamic analysis, machine learning techniques and distributed computing to tackle software testing problems. He received his Ph.D. in computer science from the University of Maryland, College Park in 2011. In his dissertation, he performed empirical studies on highly configurable software using symbolic execution and developed a decision tree based approach to select small but effective sets of configurations to test such systems under. Before pursuing graduate studies, he worked as a software engineer at CA Technologies. He received his B.S. in computer science and business from the University of Maryland in 2003.
SELECTED PUBLICATIONS AND PRESENTATIONS
- Charles Song, Adam Porter, Jeffrey S.Foster, “iTree: Efficiently Discovering High-Coverage Configurations Using Interaction Trees,” 34th International Conference on Software Engineering, June 2012
- Elnatan Reisner, Charles Song, Kin-Keung Ma, Jeffrey S.Foster, Adam Porter, “Using Symbolic Evaluation to Understand Behavior in Configurable Software Systems,” 32nd International Conference on Software Engineering, May 2010
- Vivek Sehgal, Charles Song, “SOPS: Stock Prediction using Web Sentiment,” 2007 IEEE International Conference on Data Mining, Data Mining in Web 2.0 Environments Workshop, October 2007