Title:	3IS – INTELLIGENT INTERACTION FOR INNER SOURCING
Author(s):	Ronan Kenny, Enda Fallon, Sheila Fallon, Damian Usher
ISBN:	978-989-8533-60-9
Editors:	Piet Kommers and Pedro Isaías
Year:	2017
Edition:	Single
Keywords:	Inner Source, Open Source, Software Development, Component, Artificial Neural Networks
Type:	Short Paper
First Page:	239
Last Page:	244
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	In the ever evolving world of software development, the complexity of products is increasing. This increased complexity is due to the integration of multiple components built in multiple programming languages. Many companies are turning to open source software components to reduce software development time. These freely available open source components are often tried and tested by the software development community. Similar to open sourcing, inner sourcing involves the reuse of software components from other sections within large organizations. As with open sourcing, inner sourcing is experiencing a high adoption rate by companies. Companies such as Philips, PayPal and Ericsson use the structure of open source software in an internal capacity to encourage the reuse of components. The challenge for system architects considering inner sourced components is to (a) determine the reliability and importance of individual components within an overall product (b) assess the impact and importance of any individual component when components can differ in size and language. This work proposes 3IS – Intelligent Interaction for Inner Sourcing. 3IS is a self-directed artificial neural network which uses historic performance to weigh the relative importance of an individual component within a system architecture. Using 3IS, system architects can gain a fine grained view of the structural relevance of all system components proposed for inner sourcing. This view can be used to promote the delivery of high quality components within an inner source project.
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