Discovering Heap Anomalies in the Wild

October 11, 2007
Maria Jump | UT Austin

Despite the best efforts of programmers, programs still ship with bugs. Many of these bugs manifest as anomalies the heap. This talk discusses two low-overhead synergistic techniques for discovering heap anomalies by exploiting the underlying runtime system. The first, dynamic object sampling, is a technique for selectively tagging objects with characteristics. Summarization graphs provide a compact representation of collecting heap characteristics. We show that these techniques can stand alone or work together to provide ways to discover heap-based bugs with low enough overhead to consider using them in production systems.

Speaker Details

Maria Jump is a Ph.D. Candidate in the Department of Computer Sciences at The University of Texas at Austin graduating in 2008. Her primary research interests are programming languages, compilers, runtime systems, and software reliability. Her dissertation work focuses on exploiting the runtime system of modern programming languages to increase software reliability. In her spare time, she enjoys hiking and the great outdoors.Other pertinent information can be found at her web page: http://www.cs.utexas.edu/users/mjump/