A Practical, Path-Based Framework for Detecting and Diagnosing Software Faults

Speaker:	Dr. Wei Le
		University of Virginia

Title:		"A Practical, Path-Based Framework for Detecting and
		 Diagnosing Software Faults"

Date:		Monday, 11 April 2011

Time:		4:00pm - 5:00pm

Venue:		Lecture Theatre F (near lifts 25/26), HKUST

Abstract:

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 omputation. 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 correlation - a causal 
relationship between faults - can help prioritize and group faults, and 
that my analysis is able to automatically detect such relationships.


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Biography:

Wei Le earned 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