TY - JOUR
T1 - Comparing communication and development networks for predicting file change proneness
T2 - An exploratory study considering process and social metrics
AU - Wiese, Igor Scaliante
AU - Junior, Douglas Nassif
AU - Re, Reginaldo
AU - Steinmacher, Igor
AU - Gerosa, Marco Aurelio
N1 - Funding Information:
The authors of this work thank Fundacao Araucaria and NAWEB for the financial support. Marco Aurelio Gerosa receives individual grant from the Brazilian National Research Council (CNPq) and FAPESP. Igor Wiese and Igor Steinmacher receive grants from CAPES (Process BEX 2039-13-3 and BEX 2038-13-7)
Publisher Copyright:
© Software Quality and Maintainability 2014.
PY - 2014
Y1 - 2014
N2 - Previous studies have shown that social factors of software engineering influence software quality. Communication and development networks represent the interactions among software developers. We explored the statistical relationships between file change proneness and a set metrics extracted from the issue tracker and version control system data to find the relative importance of each metric in understanding the evolution of file changes in the Rails project. Using hierarchical analysis, we found that code churn, number of past changes, and number of developers explain the evolution of changes in the Rails project better than Social Network Analysis (SNA) metrics. Considering the relative importance of each predictor, we got the same results. We also conducted a factor analysis and found that social metrics contribute to explain a group of files different from those explained by process metrics.
AB - Previous studies have shown that social factors of software engineering influence software quality. Communication and development networks represent the interactions among software developers. We explored the statistical relationships between file change proneness and a set metrics extracted from the issue tracker and version control system data to find the relative importance of each metric in understanding the evolution of file changes in the Rails project. Using hierarchical analysis, we found that code churn, number of past changes, and number of developers explain the evolution of changes in the Rails project better than Social Network Analysis (SNA) metrics. Considering the relative importance of each predictor, we got the same results. We also conducted a factor analysis and found that social metrics contribute to explain a group of files different from those explained by process metrics.
KW - Evolution of changes
KW - Github
KW - Prediction change proneneness
KW - Social metrics
KW - Social Network
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U2 - 10.14279/tuj.eceasst.0.905.888
DO - 10.14279/tuj.eceasst.0.905.888
M3 - Article
AN - SCOPUS:85028237730
SN - 1863-2122
VL - 65
JO - Electronic Communications of the EASST
JF - Electronic Communications of the EASST
ER -