报 告 人: Haifeng Guo 博士
美国内布拉斯加(奥马哈)大学计算机科学系
报告时间: 2013年6月 27日（周四）10:00～11:30
报告地点: 上海大学 行健楼7楼734室
邀 请 人: 缪淮扣 教授
Abstract：
We propose a new fault detection approach for those software which requires structured input data. Our approach takes consideration a sufficient set of test cases, isolates fine-grained structured failure-inducing patterns from failing test cases, and understands failure causes by considering those failure-inducing patterns comprehensively.
We adopt a symbolic grammar to represent structured data input, and use an automatic grammar-based test generator to produce well-distributed test cases, each of which is equipped with a set of interlaced test requirements. By learning those structured test requirements associated with failing test cases and optionally incorporating user-defined pattern dependency, we identify accurate fine-grained causes of software testing failure. Experimental results demonstrate the feasibility of our approach of isolating failure causes.

Biography：
Dr. Haifeng Guo is an associate professor in Computer Science department of University of Nebraska at Omaha. He is currently the Graduate Program Chair in the CS department. Dr. Guo got his Master of Science and PHD in Computer Science, respectively, from Peking University in 1997 and New Mexico State University in 2001. He then spent one and half a year in SUNY Stony Brook as a post-doctoral. Since August 2002, he has been working as an assistant professor of CS department in the University of Nebraska at Omaha. Dr. Guo"s main research interests are software testing, formal methods, computational logic and automated reasoning.