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Predicting defects using network analysis on dependency graphs

Authors:

Thomas Zimmermann,

Nachiappan NagappanAuthors Info & Claims

ICSE '08: Proceedings of the 30th international conference on Software engineering

Pages 531 - 540

https://doi.org/10.1145/1368088.1368161

Published: 10 May 2008 Publication History

Abstract

In software development, resources for quality assurance are limited by time and by cost. In order to allocate resources effectively, managers need to rely on their experience backed by code complexity metrics. But often dependencies exist between various pieces of code over which managers may have little knowledge. These dependencies can be construed as a low level graph of the entire system. In this paper, we propose to use network analysis on these dependency graphs. This allows managers to identify central program units that are more likely to face defects. In our evaluation on Windows Server 2003, we found that the recall for models built from network measures is by 10% points higher than for models built from complexity metrics. In addition, network measures could identify 60% of the binaries that the Windows developers considered as critical-twice as many as identified by complexity metrics.

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Cited By

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Published In

cover image ACM Conferences

ICSE '08: Proceedings of the 30th international conference on Software engineering

May 2008

558 pages

ISBN:9781605580791

DOI:10.1145/1368088

General Chair:
Wilhelm Schäfer
University of Paderborn
,
Program Chairs:
Matthew B. Dwyer
University of Nebraska
,
Volker Gruhn
University of Leipzig

Copyright © 2008 ACM.

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Published: 10 May 2008

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May 10 - 18, 2008

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ICSE '08 Paper Acceptance Rate 56 of 370 submissions, 15%;

Overall Acceptance Rate 276 of 1,856 submissions, 15%

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https://doi.org/10.1016/j.jss.2024.112263
YAZICI SGÜNAY OTUNÇMAN DKESMEZACAR FYEYİN NAKSOY SDEMIR MÇAVDAR KARAÇAM S(2024)Evaluating Radiation Exposure to Oral Tissues in C-Arm Fluoroscopy A Dose AnalysisInternational Journal of Computational and Experimental Science and Engineering10.22399/ijcesen.31310:2Online publication date: 3-Jun-2024
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Fehrer TCabrera Lozoya RSabetta ADi Nucci DTamburri D(2024)Detecting Security Fixes in Open-Source Repositories using Static Code AnalyzersProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661217(429-432)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661217
Wan XZheng ZQin FLu X(2024)Data Complexity: A New Perspective for Analyzing the Difficulty of Defect Prediction TasksACM Transactions on Software Engineering and Methodology10.1145/364959633:6(1-45)Online publication date: 27-Jun-2024
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