Dirk Riehle's Industry and Research Publications

The patch-flow method for measuring inner source collaboration [MSR 2018]

Abstract: Inner source (IS) is the use of open source software development (SD) practices and the establishment of an open source-like culture within an organization. IS enables and requires developers to collaborate more than traditional SD methods such as plan-driven or agile development. To better understand IS, researchers and practitioners need to measure IS collaboration. However, there is no method yet for doing so. In this paper, we present a method for measuring IS collaboration by measuring the patch-flow within an organization. Patch-flow is the flow of code contributions across organizational boundaries such as project, organizational unit, or profit center boundaries. We evaluate our patch-flow measurement method using case study research with a software developing multi-industry company. By applying the method in the case organization, we evaluate its relevance and viability and discuss its usefulness. We found that about half (47.9%) of all code contributions constitute patch-flow between organizational units, almost all (42.2%) being between organizational units working on different products. Such significant patch-flow indicates high relevance of the patch-flow phenomenon and hence the method presented in this paper. Our patch-flow measurement method is the first of its kind to measure and quantify IS collaboration. It can serve as a base for further quantitative analyses of IS collaboration.

Keywords: Inner source, internal open source, inner source measurement, patch-flow, open source, open collaboration, software development collaboration measurement, inner source metrics

Reference: Maximilian Capraro, Michael Dorner, and Dirk Riehle. 2018. The Patch-Flow Method for Measuring Inner Source Collaboration. In MSR ’18: 15th International Conference on Mining Software Repositories , May 28–29, 2018, Gothenburg, Sweden. ACM, New York, NY, USA, 11 pages.

A preprint of the paper is available here as a PDF file.

Tagged as (if any)

Subscribe!

Comments

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Navigation

Share the content

Share on LinkedIn

Share by email

Share on X (Twitter)

Share on WhatsApp

Featured startups

QDAcity makes collaborative qualitative data analysis fun and easy.

Featured projects

Open data, easy and social
Engineering intelligence unleashed
Open source in products, easy and safe