November 23, 2011
Title: Fighting Software Bugs Through Automatic Text Analytics
Abstract: Software bugs greatly hurt software reliability. In this talk, I will present our recent research on leveraging software textual information in program comments, source code and bug reports to automatically detect and fix software bugs as well as understand software developers. iComment and aComment automatically extract specifications from source code and code comments written in a natural language, and use these specifications to detect comment-code inconsistencies, i.e., software bugs and bad comments. R2Fix automatically generates bug-fixing patches from bug reports written free-form in a natural language. We show that it is feasible to automatically analyze free-form comments and bug reports to automatically detect and fix software bug.
Biography: Lin Tan is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. Tan received her PhD in Computer Science from the University of Illinois, Urbana-Champaign. Her research interests include software reliability and security with a focus on applying natural language processing and machine learning techniques to improve software systems reliability.