Monday, October 17, 2011
11:00 AM
Computer Studies Bldg. 209
Wei Le
A Practical, Path-Based Framework for Detecting and Diagnosing Software Faults
One of the important challenges in developing software is the avoidance of software faults. Since a fault occurs along an execution path, program path information is essential for both detecting and diagnosing a fault. Manual inspection can identify a path where a fault occurs; however, the approach does not scale. Dynamic techniques, such as testing, are also effective in finding faulty paths, but only in a sampled space. In this talk, I present a practical framework that statically detects faults in path segments. The framework applies an interprocedural, demand-driven analysis to address the precision and scalability challenges of static path computation. It integrates a specification technique that enables automatic generation of analyses for detecting different types of faults. In the second part of my talk, I describe how the computed path information can be applied to automate the diagnostic tasks. In particular, I demonstrate that detecting fault correlationóa causal relationship between faultsócan help prioritize and group faults, and that my analysis is able to automatically detect such relationships.

Bio: Wei Le is an assistant professor at the PhD program in Computing and Information Sciences at the Rochester Institute of Technology. Wei received her Ph.D. in Computer Science from the University of Virginia in December 2010. Her research focuses on developing automatic, practical solutions for improving software reliability and security, covering the areas of program analysis, software testing and software security. Wei received the best presentation award at the 16th ACM SIGSOFT International Symposium on the Foundation of Software Engineering and also is a recipient of a Google Anita Borg Memorial Scholarship.

Refreshments will be provided at 10:45AM