This talk first presents Pacer, a deployable, scalable approach for detecting data races, which are a common and serious type of concurrency bug. Second, I describe techniques for efficiently reporting the calling context (stack trace) of concurrency and other bugs -- essential information for understanding the behavior of complex, modern programs. I conclude with my future plans for developing new analyses and frameworks that make concurrent software reliable.
Michael D. Bond is a postdoctoral fellow in Computer Science at UT Austin. He received his PhD from UT Austin in December 2008, supervised by Kathryn S. McKinley. His research makes software more robust by using dynamic analysis to diagnose and tolerate unexpected errors. Michael's interests include programming languages, runtime systems, compilers, and security. His dissertation received the 2008 ACM SIGPLAN Outstanding Doctoral Dissertation Award.
Refreshment provided at 10:45