Yesterday and today we hosted the 2nd GI AK workshop on microservices and DevOps at SUSE, in Nuremberg. We had 37 registrations, 26 people showed up, and about half of them were from industry. Thank you SUSE, for having us!
Sivantos (former Siemens audiology) is looking for a Werkstudent to continue the AMOS SS17 project, in which it developed software for a Raspberry Pi as a user agent for testing hearing aids. Please see Sivantos career opportunities at Werkstudent (m/w) im Bereich Softwareentwicklung / Single Board Computer / Raspberry Pi (486).
Abstract: Inner source (IS) is the use of open source software development practices and the establishment of an open source-like culture within organizations. To create metrics about the usage of IS within a speciﬁc corporation, data about the software development need to be extracted from source code management (SCM) systems. A developed crawl process retrieves the data over specially implemented adapters. To date adapters for git and manually exported CSV ﬁles from Microsoft Team Foundation Server (TFS) are in use. To automate data extraction from TFS a new adapter must be developed. Furthermore, the poor performance of the existing git adapter along with the crawl process needs to be improved. To validate the performance increase execution time and resource metrics are measured and compared. The result of this work is a newly developed TFS adapter and a performance-optimized git adapter and crawl process.
Keywords: Engineering thesis, inner source metrics, performance optimization
Reference: Constantin Hasler. Implementierung und Performance-Optimierung von SCM-Adaptern. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2017.
Abstract: Many software companies use open source development practices inside the company‘s boundaries, which is called inner source. The Collaboration Management Suite (CMSuite), developed by the Open Source Research Group at the Friedrich-Alexander- University Erlangen-Nuernberg, is a software tool for extraction, analysis, and visualization of data and metrics regarding inner source. Prior to this thesis, CMSuite lacked features to visualize metrics and let stakeholders deﬁne their own metrics and visualizations. A programmer had to write code from scratch, where he deﬁnes a metric and then visualizes the result. Furthermore is not fully researched, which metrics will be important in the future, so adding new ones without wasting much time is desirable. This thesis discusses a new Java-based REST-service, which makes it possible to easily add and deﬁne new metrics, using the data integration tool Pentaho Kettle. The result is then visualized in an AngularJS 2.0 client component for a metric dashboard. Now the user does not have to write any code, but only has to deﬁne a metric with the help of Kettle and can see the results of his metric, immediately. Thus, this addition to CMSuite will enable him to save time and test new metrics much more eﬃciently.
Keywords: Engineering thesis, inner source metrics, adaptable dashboard
Reference: Achim Däubler. Design and Implementation of an Adaptable Metric Dashboard. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2017.
We are organizing a meeting of the GI AK on microservices and devops on October 19-20th in Nuremberg. Suse has generously offered their event space for the workshop. The workshop is free and open to the professional public. The agenda has been finalized. It is still possible to register for the workshop. Despite this English-language announcement, the workshop is likely to be held in German.
Abstract: The cloud-based QDAcity platform allows to conduct collaborative research projects applying Qualitative Data Analysis methods and research validation through crowdsourcing. When using Qualitative Data Analysis as a research method, expressive measurements of the quality and maturity of the results are essential to prove the validity of the research Findings. Common measures for validity of ratings are inter-coder agreement metrics, and for measuring the maturity of a qualitative research project, a prevalent approach is to calculate saturation. However, with a high number of raters, inter-coder agreement metrics become inconvenient to evaluate and the calculation of saturation requires a clean documentation of many project variables. The cloud environment of QDAcity can solve both of these problems, because it can efficiently store all ratings and project variables, and thus integrate both metrics more conveniently for the researcher. This thesis presents the implementation of the two inter-coder agreement metrics Krippendorff’s Alpha and Fleiss’ Kappa in QDAcity and a new approach with its implementation of theoretical saturation.
Keywords: Intercoder Agreement, Theoretical Saturation, Qualitative Data Analysis, QDA
Reference: Matthias Schöpe. QDAcity Quality Metrics. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2017.