Towards reproducible software studies with MAO and Renku

Abstract

In software engineering, the developers’ joy of decomposing and recomposing microservice-based applications has led to an enormous wave of microservice artefact technologies. To understand them better, researchers perform hundreds of experiments and empirical studies on them each year. Improving the reuse and reproducibility of these studies requires two ingredients: A system to automate repetitive experiments, and a research data management system with emphasis on making research reproducible. Both frameworks are now available via the Microservice Artefact Observatory (MAO) and Renku. In this paper, we explain the current capabilities of MAO as a global federated research infrastructure for determining software quality characteristics. Moreover, we emphasise the integration of MAO with Renku to demonstrate how a reproducible end-to-end experiment workflow involving globally distributed research teams looks like.

Keywords

• Software technology
• Data science
• Reproducibility