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Can Developer-Module Networks Predict Failures?


Pinzger, M; Nagappan, N; Murphy, B (2008). Can Developer-Module Networks Predict Failures? In: ACM SIGSOFT Symposium on the Foundations of Software Engineering, Atlanta, Georgia, USA, 9 November 2008 - 14 November 2008, 2-12.

Abstract

Software teams should follow a well defined goal and keep their
work focused. Work fragmentation is bad for efficiency and
quality. In this paper we empirically investigate the relationship
between the fragmentation of developer contributions and the
number of post-release failures. Our approach is to represent
developer contributions with a developer-module network that we
call contribution network. We use network centrality measures to
measure the degree of fragmentation of developer contributions.
Fragmentation is determined by the centrality of software modules
in the contribution network. Our claim is that central software
modules are more likely to be failure-prone than modules located
in surrounding areas of the network. We analyze this hypothesis
by exploring the network centrality of Microsoft Windows Vista
binaries using several network centrality measures as well as
linear and logistic regression analysis. In particular, we investigate
which centrality measures are significant to predict the probability
and number of post-release failures. Results of our experiments
show that central modules are more failure-prone than modules
located in surrounding areas of the network. Results further
confirm that number of authors and number of commits are
significant predictors for the probability of post-release failures.
For predicting the number of post-release failures the closeness
centrality measure is most significant.

Abstract

Software teams should follow a well defined goal and keep their
work focused. Work fragmentation is bad for efficiency and
quality. In this paper we empirically investigate the relationship
between the fragmentation of developer contributions and the
number of post-release failures. Our approach is to represent
developer contributions with a developer-module network that we
call contribution network. We use network centrality measures to
measure the degree of fragmentation of developer contributions.
Fragmentation is determined by the centrality of software modules
in the contribution network. Our claim is that central software
modules are more likely to be failure-prone than modules located
in surrounding areas of the network. We analyze this hypothesis
by exploring the network centrality of Microsoft Windows Vista
binaries using several network centrality measures as well as
linear and logistic regression analysis. In particular, we investigate
which centrality measures are significant to predict the probability
and number of post-release failures. Results of our experiments
show that central modules are more failure-prone than modules
located in surrounding areas of the network. Results further
confirm that number of authors and number of commits are
significant predictors for the probability of post-release failures.
For predicting the number of post-release failures the closeness
centrality measure is most significant.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:14 November 2008
Deposited On:28 Jan 2009 14:52
Last Modified:05 Apr 2016 12:45
Official URL:https://cgi4.cc.gatech.edu/phps/conferences/fse16/

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