What’s Next After “Source-Available”?

Venture capital plays an important role in open source: It funds startups innovative commercial open source products for the benefit of all as part of the equation. For venture capital to keep flowing, the startup needs to make money eventually, at a level similar to traditional software startups. This is always achieved by withholding something that is not made available for free, generically called “the complement” in this article. This is not human services (labor), because it doesn’t scale well. Rather, it is intellectual property, usually packaged today with machine services (computing). This does scale well.

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Open Source Hardware (Hannig & Teich, IEEE Computer Column)

I’m happy to report that the 17th article in the Open Source Expanded column of IEEE Computer has been published.

TitleOpen Source Hardware
KeywordsOpen Source Hardware, Integrated Circuits, Ecosystems, Hardware, Open Source Software
AuthorsFrank Hannig, Jürgen Teich
PublicationComputer vol. 54, no. 10 (October 2021), pp. 111-115

Abstract: Hardware that can be manufactured from free and open source descriptions has gained a lot of momentum. This article gives a general introduction, focusing on electronics and integrated circuits, corresponding open ecosystems and organizations, and highlights benefits and challenges.

As always, the article is freely available (local copy).

Also, check out the full list of articles.

Calculating the Costs of Inner Source Collaboration by Computing the Time Worked (HICSS 55)

Abstract: A key part of taxation, controlling, and management of international collaborative programming workflows is determining the costs of a supplied software artifact. The OECD suggests the use of the Cost Plus method for calculating these costs. However, in the past, this method has been implemented using only coarse-grain data from the costs of whole organizational units. Due to the move to inner source software development, we need a much more fine-grain solution for computing the detailed time spent on programming specific components. This is necessary, because a more accurate work time distribution is required to fulfill the fiscal and administrative challenges posed by collaborating across organizational boundaries. In this article, we present a novel method to determine the time spent on an individual code contribution (commit) to a software component for use within cost calculation, especially for taxation purposes. We demonstrate the usefulness of our approach by application to a real-world data set gathered at a large multi-national corporation. We evaluate our work through feedback received from this corporation and from the German Ministry of Finance.

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A Validation of QDAcity‑RE for Domain Modeling Using Qualitative Data Analysis

Abstract: Using qualitative data analysis (QDA) to perform domain analysis and modeling has shown great promise. Yet, the evaluation of such approaches has been limited to single-case case studies. While these exploratory cases are valuable for an initial assessment, the evaluation of the efficacy of QDA to solve the suggested problems is restricted by the common single-case case study research design. Using our own method, called QDAcity-RE, as the example, we present an in-depth empirical evaluation of employing qualitative data analysis for domain modeling using a controlled experiment design. Our controlled experiment shows that the QDA-based method leads to a deeper and richer set of domain concepts discovered from the data, while also being more time efficient than the control group using a comparable non-QDA-based method with the same level of traceability.

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Making Open Source Project Health Transparent (Goggins et al., IEEE Computer Column)

I’m happy to report that the 16th article in the Open Source Expanded column of IEEE Computer has been published.

TitleMaking Open Source Project Health Transparent
KeywordsOpen source software
AuthorsSean P. Goggins, Matt Germonprez, Kevin Lumbard
PublicationComputer vol. 54, no. 8 (August 2021), pp. 104-111

Abstract: This article explores the Community Health Analytics for Open Source Software (CHAOSS) project and how it plays an integral role in the automation of key measures to make the state of open source readily observable.

As always, the article is freely available (local copy).

Also, check out the full list of articles.

Pattern Discovery and Validation Using Scientific Research Methods (TPLoP)

Abstract: Pattern discovery, the process of discovering previously unrecognized patterns, is often performed as an ad-hoc process with little resulting certainty in the quality of the proposed patterns. Pattern validation, the process of validating the accuracy of proposed patterns, remains dominated by the simple heuristic of “the rule of three”. This article shows how to use established scientific research methods for the purpose of pattern discovery and validation. We present a specific approach, called the handbook method, that uses the qualitative survey, action research, and case study research for pattern discovery and evaluation, and we discuss the underlying principle of using scientific methods in general. We evaluate the handbook method using three exploratory studies and demonstrate its usefulness.

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Whose Open Source Freedom is it Anyway?

It is 2021 and there is still a lot of fighting about “freedom” in open source software development. Here is an analytical breakdown of the issues.

Freedom can refer to people or artifacts (source code). When it refers to people, it is typically freedom of choice regarding what to do. There are three main roles in open source: The original programmer, an intermediary (another programmer or a software vendor), and the users or customers of the vendor. I’m simplifying, but this matches the distribution use-case in which license clauses put the most obligations on people.

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