Software Research and the Industry
Open source, building products, software startups, and industry strategy by Prof. Dr. Dirk Riehle
We will be hosting an industry talk on “When Agile Meets Regulatory Compliance.” The talk is free and open to the public.
We will be hosting an industry talk on “Do we need agile architecture?”. The talk is free and open to the public.
We will be hosting an industry talk on what happens when Project = 1 Team stops being feasible: Scaling methods, tools and skills, online and IRL. The talk is free and open to the public.
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 like to register, check out the official announcement! If you are affiliated with UC Santa Cruz, talk to Stephanie Lieggi (or me) to get in! If you are just curious, here is the general syllabus.
I’m happy to report that the ninth article in the Open Source Expanded column of IEEE Computer has been published.
| Title | Open Source Research Software |
| Keywords | Open Source Software, Scientific Computing, Software Engineering, Artificial Intelligence, Licenses |
| Authors | Wilhelm Hasselbring, Leslie Carr, Simon Hettrick, Heather Packer, and Thanassis Tiropanis |
| Publication | Computer vol. 53, no. 8 (August 2020), pp. 84-88 |
Software product management is easily the least well understood yet most important business function in software companies. I have been teaching Software Product Management by Case for about ten years now, and it is time I change a gear or two. Hence, I’m asking whether anyone is interested in helping me teach this course, whether in small or large capacity. For details, please see this slide deck:
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.
Continue reading “Three Open Data Sources Made Easy”
Abstract: Pattern discovery, the process of discovering previously unrecognized patterns, is usually 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, has rarely gone beyond 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. The result is an approach to pattern discovery and validation that can provide the same certainty that traditional scientific research methods can provide for the theories they are used to validate. This article describes our approach and explores its usefulness for pattern discovery and evaluation in a series of studies.
Keywords: Patterns, pattern discovery, pattern validation, theory codification, theory building and evaluation, research design
Reference: Riehle, D., Harutyunyan, N., & Barcomb, A. (2020). Pattern Discovery and Validation Using Scientific Research Methods. Friedrich-Alexander-Universität Erlangen-Nürnberg, Dept. of Computer Science, Technical Reports, CS-2020-01, February 2020.
The article is available as a PDF file and on FAU’s OPUS server.
This winter semester, students of TU Berlin completed four AMOS projects. Each section below describes the final result of one of the projects: