Please use this identifier to cite or link to this item: https://doi.org/10.1145/2491411.2491449
Title: Mining succinct predicated bug signatures
Authors: Sun, C.
Khoo, S.-C. 
Keywords: Bug signature
Feature selection
Statistical debugging
Issue Date: 2013
Source: Sun, C.,Khoo, S.-C. (2013). Mining succinct predicated bug signatures. 2013 9th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering, ESEC/FSE 2013 - Proceedings : 576-586. ScholarBank@NUS Repository. https://doi.org/10.1145/2491411.2491449
Abstract: A bug signature is a set of program elements highlighting the cause or effect of a bug, and provides contextual information for debugging. In order to mine a signature for a buggy program, two sets of execution profiles of the program, one capturing the correct execution and the other capturing the faulty, are examined to identify the program elements contrasting faulty from correct. Signatures solely consisting of control flow transitions have been investigated via discriminative sequence and graph mining algorithms. These signatures might be handicapped in cases where the effect of a bug is not manifested by any deviation in control flow transitions. In this paper, we introduce the notion of predicated bug signature that aims to enhance the predictive power of bug signatures by utilizing both data predicates and control-flow information. We introduce a novel "discriminative itemset generator" mining technique to generate succinct signatures which do not contain redundant or irrelevant program elements. Our case studies demonstrate that predicated signatures can hint at more scenarios of bugs where traditional control-flow signatures fail. Copyright 2013 ACM.
Source Title: 2013 9th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering, ESEC/FSE 2013 - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/78233
ISBN: 9781450322379
DOI: 10.1145/2491411.2491449
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

11
checked on Jan 16, 2018

Page view(s)

22
checked on Jan 14, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.