Dirk Riehle's Industry and Research Publications

Category: 3.1 Research (General)

A systematic literature review of pre-requirements specification traceability [RE Journal]

Abstract Requirements traceability (RT) is the ability to link requirements to other software development artifacts. In pre-requirements (pre-RS) traceability, requirements are linked to their origin, such as interviews with stakeholders, meeting protocols, or legacy systems. Compared with post-RS traceability, which links requirements to source code and other later artifacts, pre-RS traceability has seen much less…

2024-01-29
A systematic analysis of problems in open collaborative data engineering [TSC Journal]

Abstract Collaborative workflows are common in open-source software development. They reduce individual costs and improve the quality of work results. Open data shares many characteristics with open-source software as it can be used, modified, and redistributed by anyone, for free. However, in contrast to open-source software engineering, collaborative data engineering on open data lacks a…

2023-11-03
Incentivizing German Universities to Capitalize on Their Intellectual Property

In a recent position paper, SPRIN-D, an innovation agency of the German government, proposed that universities license their intellectual property (IP) to university startups in return for virtual shares. This approach is suggested as a practice to work around universities who stall startup licensing deals due to unrealistic assumptions (e.g. lump-sum upfront payment). The problem…

2022-05-12
Course on commercial open source startups at UC Santa Cruz

In September 2020, I will be teaching a workshop series on commercial open source startups at UC Santa Cruz (and starting November, as a course, at FAU). The series at UCSC is being faciliated by CROSS, the Center for Research in Open Source Software, and I’m getting help from Thomas Otter (@vendorprisey). If you would…

2020-09-01
Open-source research software (Wilhelm Hasselbring et al., IEEE Computer)

For good scientific practice, research software should be open source. It should be both archived for reproducibility and actively maintained for reusability.

2020-08-03
Three open data sources made easy

What are the the top three most promising open data sources that you would like to combine for an innovative app or data analysis? Please let us know and we will try to make it easy for you. In more detail (for developers) Open data can be hard to use: Every data source is different,…

2020-05-13