NDLI: Mitigating the Dependence Confounding Effect for Effective Predicate-Based Statistical Fault Localization

Content Provider	IEEE Xplore Digital Library
Author	Xingya Wang Shujuan Jiang Xiaolin Ju Heling Cao Yingqi Liu
Copyright Year	2015
Description	Author affiliation: Sch. of Comput. Sci. & Technol., Nantong Univ., Nantong, China (Xiaolin Ju) \|\| Sch. of Comput. Sci. & Technol., China Univ. of Min. & Technol., Xuzhou, China (Xingya Wang; Shujuan Jiang; Heling Cao; Yingqi Liu)
Abstract	The recent studies indicate that predicate-based statistical fault localization suffered from the control dependence confounding effect and the failure flow confounding effect, which decrease the measurement accuracy of fault localization. However, the extent of the potentially confounding effect of data dependence is uncertain. This paper presents a novel approach that accounts for the effects of program dependences to mitigate the confounding effect during statistical predicate-based fault localization. First, we present a variable type-based predicate designation technique to improve the ability of fault-relevant predicate identification. Then, we conduct dependence analysis to examine the extent of the potentially confounding effect of data dependence in fault localization. Finally, we propose a linear regression-based method to mitigate both the data dependence confounding effect and the control dependence confounding effect. Using the open-source software systems, we find that the fault-relevant predicate can be identified effectively by the proposed predicate design technique, and the effectiveness of fault localization can be significantly improved after mitigating the dependence confounding effect.
Starting Page	105
Ending Page	114
File Size	257862
Page Count	10
File Format	PDF
ISSN	07303157
e-ISBN	9781467365642
DOI	10.1109/COMPSAC.2015.37
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Reactive power Fault diagnosis Measurement Software Data models Sociology Statistics predicate designation fault localization confounding effect program dependence
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Mitigating the confounding effects of program dependences for effective fault localization

A Crosstab-based Statistical Method for Effective Fault Localization

Effective Statistical Fault Localization Using Program Slices

Reducing confounding bias in predicate-level statistical debugging metrics

Software fault localization based on program slicing spectrum

Spectrum-Based Multiple Fault Localization

An execution slice and inter-block data dependency-based approach for fault localization

An observation-based model for fault localization

An Improvement to Fault Localization Technique Based on Branch-Coverage Spectra

Mitigating the Dependence Confounding Effect for Effective Predicate-Based Statistical Fault Localization

Similar Documents

Mitigating the confounding effects of program dependences for effective fault localization

A Crosstab-based Statistical Method for Effective Fault Localization

Effective Statistical Fault Localization Using Program Slices

Reducing confounding bias in predicate-level statistical debugging metrics

Software fault localization based on program slicing spectrum

Spectrum-Based Multiple Fault Localization

An execution slice and inter-block data dependency-based approach for fault localization

An observation-based model for fault localization

An Improvement to Fault Localization Technique Based on Branch-Coverage Spectra

Mitigating the Dependence Confounding Effect for Effective Predicate-Based Statistical Fault Localization