InnerSource practices, inspired by open source methodologies, offer significant value to organizations by fostering software reuse, improving collaboration, and eliminating inefficiencies [1]. However, quantifying this value is essential to justify investments and sustain InnerSource initiatives. This paper presents a framework to measure the impact of InnerSource projects in the financial industry defining four key areas and their corresponding data gathering strategies. It focuses on metrics for cost savings through reuse, enhanced time-to-market, reduced maintenance expenses, and improved engineering health. By leveraging automated tools, surveys, and analytical models, organizations can assess the financial benefits of InnerSource contributions while fostering transparency and collaboration among teams [2]. This approach provides actionable insights to drive strategic decisions and optimize software development processes.

Many software development projects have introduced mandatory code review for every change to the code. This means that the project needs to devote a significant effort to review all proposed changes, and that their merging into the code base may get considerably delayed. Therefore, all those projects need to understand how code review is working, and the delays it is causing in time to merge.

The Metrics Grimoire system is composed by a set of tools designed to retrieve data from repositories related to software development. Their aim is to produce organized databases suitable for easy querying with research and industrial purposes. The data in those databases have a similar structure, to easy cross-database studies, and can be enriched with information such as linkage of the multiple identities of actors, or their affiliation. This paper presents the general structure of those databases, and a collection of up-to-date database dumps that are publicly available. They correspond to two well-known projects, Open Stack, and Eclipse, including data from source code management repositories, issue tracking systems, mailing lists, and code review systems.

Because of the distributed and collaborative nature of free / open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially ---but not only--- because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations with bounded margins of error.