Paper Info
Title
An empirical study of social networks metrics in object-oriented software
Abstract
We study the application to object-oriented software of new metrics, derived from Social Network Analysis. Social Networks metrics, as for instance, the EGO metrics, allow to identify the role of each single node in the information flow through the network, being related to software modules and their dependencies. These metrics are compared with other traditional software metrics, like the Chidamber-Kemerer suite, and software graph metrics. We examine the empirical distributions of all the metrics, bugs included, across the software modules of several releases of two large Java systems, Eclipse and Netbeans. We provide analytical distribution functions suitable for describing and studying the observed distributions. We study also correlations among metrics and bugs. We found that the empirical distributions systematically show fat-tails for all the metrics. Moreover, the various metric distributions look very similar and consistent across all system releases and are also very similar in both the studied systems. These features appear to be typical properties of these software metrics.
Year
DOI
Venue
2010
10.1155/2010/729826
Adv. Software Engineering
Keywords
Field
DocType
empirical distribution,traditional software metrics,software metrics,software module,ego metrics,new metrics,software graph metrics,social networks metrics,empirical study,social network analysis,object-oriented software,social network
Halstead complexity measures,Data mining,Information flow (information theory),Object-oriented programming,Computer science,Social network analysis,Theoretical computer science,Software,Software metric,Java,Empirical research,Reliability engineering
Journal
Volume
Citations 
PageRank 
2010,
10
0.63
References 
Authors
20
4
Name
Order
Citations
PageRank
Giulio Concas142444.83
Michele Marchesi2807120.28
Alessandro Murgia324616.20
Roberto Tonelli414519.35