Characterizing software activity: the influence of software to ecosystem health

TY - CHAP

T1 - Characterizing software activity

T2 - European Conference on Software Architecture Workshops 2015

AU - Manikas, Konstantinos

AU - Kontogiorgos, Dimosthenis

N1 - Conference code: 9

PY - 2015/9/7

Y1 - 2015/9/7

N2 - The health of a software ecosystem reects the ability of the ecosystem to endure and remain variable and productive over time. Measurements of health in a software ecosystem are applied to inform on how the ecosystem is evolving, evaluate changes, and predict future states. In this study we in vestigate the inuence of software to the overall health of the ecosystem. We propose an approach of measuring the activ-ity of the ecosystem over time and identifying the inuence to health. We do this in two ways: (i) we study the evolution of the software network over time to identify changes in the structure of the software network and investigate whether they relate to general changes in the ecosystem. (ii) We propose the identification of the inuence of the indepen-dent software components to ecosystem health at an activity level. We do so by defining keystone and dominator activ-ities and propose tentative means of measuring them. We apply our proposed approach to the platform of the Apache Cordova ecosystem, an ecosystem with a community-based platform and independent contributions. Our analysis iden-tifies two points in time where the ecosystem is under major change. These points are confirmed independently by both the measures of software network and keystone and dominator activities.

AB - The health of a software ecosystem reects the ability of the ecosystem to endure and remain variable and productive over time. Measurements of health in a software ecosystem are applied to inform on how the ecosystem is evolving, evaluate changes, and predict future states. In this study we in vestigate the inuence of software to the overall health of the ecosystem. We propose an approach of measuring the activ-ity of the ecosystem over time and identifying the inuence to health. We do this in two ways: (i) we study the evolution of the software network over time to identify changes in the structure of the software network and investigate whether they relate to general changes in the ecosystem. (ii) We propose the identification of the inuence of the indepen-dent software components to ecosystem health at an activity level. We do so by defining keystone and dominator activ-ities and propose tentative means of measuring them. We apply our proposed approach to the platform of the Apache Cordova ecosystem, an ecosystem with a community-based platform and independent contributions. Our analysis iden-tifies two points in time where the ecosystem is under major change. These points are confirmed independently by both the measures of software network and keystone and dominator activities.

KW - ecosystem health, graph analysis, software activity, software ecosystems

U2 - 10.1145/2797433.2797481

DO - 10.1145/2797433.2797481

M3 - Book chapter

SN - 978-1-4503-3393-1

BT - Proceedings of the 2015 European Conference on Software Architecture Workshops

PB - Association for Computing Machinery

Y2 - 7 September 2015 through 11 September 2015

ER -