Seminar

    Department of Systems Engineering and Engineering Management
            The Chinese University of Hong Kong

Title     : Identifying Bug Signatures Using Discriminative Graph Mining

Speaker    : Prof. Hong Cheng  
Date       : Sep. 21st, 2012 (Friday)
Time       : 4:30 p.m. - 5:30 p.m.
Venue      : Room 513
             William M.W. Mong Engineering Building
             CUHK

Abstract:
Bug localization has attracted a lot of attention recently. Most existing methods focus on pinpointing a single statement or function call which is very likely to contain bugs. Although such methods could be very accurate, it is usually very hard for developers to understand the context of the bug, given each bug location in isolation. In our work, we model software executions as graphs at two levels of granularity: methods and basic blocks. An individual node represents a method or basic block and an edge represents a method call, method return or transition (at the method or basic block granularity). Given a set of graphs of correct and faulty executions, we propose to extract the most discriminative subgraphs which contrast the program flow of correct and faulty
executions. The extracted subgraphs not only pinpoint the bug, but also provide an informative context for understanding and fixing the bug. Different from traditional graph mining which mines a very large set of frequent subgraphs, we formulate subgraph mining as an optimization problem and directly generate the top-K most discriminative subgraphs representing distinct locations which may contain bugs. Experimental results and case studies show that our proposed method is both effective and efficient to mine
discriminative subgraphs for bug localization and context identification.

Biography:
Dr. Hong Cheng is an Assistant Professor in the Department of Systems Engineering and Engineering Management at the Chinese University of Hong Kong. She received her Ph.D. degree from University of Illinois at Urbana-Champaign in 2008.

Dr. Cheng\'s research interests include data mining, database systems and machine learning. She also studies analyzing software code and execution using data mining approaches. She has published over 50 research papers in international conferences and journals, including SIGMOD, VLDB, SIGKDD, ICDE, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Knowledge Discovery from Data, and Data Mining and Knowledge Discovery, and received research paper awards at ICDE\'07, SIGKDD\'06 and SIGKDD\'05. She received the certificate of recognition for the 2009 SIGKDD Doctoral Dissertation Award.

************************* ALL ARE WELCOME ************************

Host         : Prof. Hong Cheng
Tel          : (852) 3943-8300
Email        : hcheng@se.cuhk.edu.hk
Enquiries    : Prof. Hong Cheng
               Department of Systems Engineering and Engineering Management
               CUHK
Website      : http://www.se.cuhk.edu.hk/~seem5201
Email        : seem5201@se.cuhk.edu.hk