2011 27th IEEE International Conference on Software Maintenance (ICSM) 2011
DOI: 10.1109/icsm.2011.6080825
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Measuring disruption from software evolution activities using graph-based metrics

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Cited by 4 publications
(4 citation statements)
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“…Paymal et al [63] have investigated the changes to graph vertex properties such as degree, betweenness centrality, clustering coefficient and measured the extent of disruption after perfective maintenance in the evolution of JHotDraw application. Wang et al [80] studied the evo-lution of the call graphs corresponding to 223 consecutive versions of the Linux kernel, employing several graph properties as metrics, observing that the network growth relies heavily on preferential attachment.…”
Section: Tablementioning
confidence: 99%
See 1 more Smart Citation
“…Paymal et al [63] have investigated the changes to graph vertex properties such as degree, betweenness centrality, clustering coefficient and measured the extent of disruption after perfective maintenance in the evolution of JHotDraw application. Wang et al [80] studied the evo-lution of the call graphs corresponding to 223 consecutive versions of the Linux kernel, employing several graph properties as metrics, observing that the network growth relies heavily on preferential attachment.…”
Section: Tablementioning
confidence: 99%
“…With the passage of versions a larger percentage of new classes are linked to higher in-degree classes. Stated in a different way, "important nodes (in software systems) stay important", a fact which is considered as a sign of stability in the design in the work of Paymal et al [63]. To validate empirically whether Preferential Attachment actually holds for the systems under study, we illustrate in Fig.…”
Section: Preferential Attachment and Duplicationmentioning
confidence: 99%
“…Every change to the software involves some disruption. The disruptions are stronger for components that are central to the software [28]. Knowledge of the relative importance of a component in relation to the software as a whole, will enable a developer to quickly assess the potential impact of a change.…”
Section: Introductionmentioning
confidence: 99%
“…Zanetti and Schweitzer (2012) proposed a metric that quantifies the modularity of a system by using its representation as a software network. Paymal et al (2011) have investigated the changes to graph vertex properties such as degree, betweenness centrality, clustering coefficient and measured the extent of disruption after perfective maintenance in the evolution of JHotDraw application. studied the evolution of the call graphs corresponding to 223 consecutive versions of the Linux kernel, employing several graph properties as metrics, observing that the network growth relies heavily on preferential attachment.…”
Section: Software Evolution Modellingmentioning
confidence: 99%