News

New Practical Course on Agile Software Development

23.02.2021
During the semester break, our research group will offer a new practical course on agile software development. In this course, students will learn about selected agile software development methods and practices and apply them in dedicated projects with the help of selected tools. The participants will be learning and applying their knowledge on three levels, including processes and practices, project-specific domain knowledge, implementation- and tool-specific aspects.Depending on the specific software projects, the students will get familiar with various state-of-the-art technologies and tools for software engineering and for the realisation of the specific project. The course will offer an insight into real-world software development, as well as other relevant aspects such as self learning, team work, and problem solving.

Three talks at ICSE 2021

11.02.2021
We are happy to announce that we will present and discuss the key results of our recent publications at the International Conference on Software Engineering 2021 (ICSE 2021), the largest international annual conference on software engineering research with a regular attendance of more than 2000 researchers and practioners. The talks are about three journal papers that we recently published and cover a diverse set of topics, i.e., static analysis warnings, issue type prediction, and the costs of defect prediction. You can find the related publications below. 

Five talks at the SE 2021

17.11.2020
We are happy to announce that we will present and discuss the key results of our recent publications at the Software Engineering 2021, the yearly conference on software engineering by the German chapter of the ACM (Gesellschaft für Informatik). The talks are about five journal papers that we published during the last year and cover a diverse set of topics, i.e., static analysis warnings, developer social networks, issue type prediction, differences between unit and integration tests, and defect prediction. You can find the related publications below. 

Best Reviewer Award at the SAM 2020

20.10.2020
Philip Makedonski was presented with a Best Reviewer Award in recognition of his significant contribution to the review process of the 12th System Analysis and Modelling Conference (SAM 2020), which took place in conjunction with the ACM / IEEE 23nd International Conference on Model Driven Engineering Languages and Systems (MODELS 2020).

Distinguished Artifact Award received at the ICSME 2020

01.10.2020
We are happy to announce that our group members Alexander Trautsch, Steffen Herbold and Jens Grabowski received a Distinguished Artifact Award for the artifact supplementing their paper "Static source code metrics and static analysis warnings for fine-grained just-in-time defect prediction" at the 36th International Conference on Software Maintenance and Evolution (ICSME).

Latest TDL specifications published

10.09.2020
The outcomes of our continued work on the Test Description Language (TDL) within STF 577 of the European Telecommunications Standards Institute (ETSI) have been published as updated versions of the specifications:The latest version of the technical report on the reference implementation of TDL is expected to be published soon as well.

Paper accepted at SAM 2020

04.09.2020
We are happy to announce that our paper Facilitating the Co-Evolution of Semantic Descriptions in Standards and Models is accepted for presentation at the 12th System Analysis and Modelling Conference (SAM 2020). The conference will take place on October 19-20th in conjunction with the ACM / IEEE 23nd International Conference on Model Driven Engineering Languages and Systems (MODELS 2020), both of which will be held online due to the current circumstances (originally scheduled to be held in Montreal, Canada).

Two papers accepted at Empirical Software Engineering

26.08.2020

We are happy to announce that two of our papers were recently accepted for publication in the Empirical Software Engineering journal. 


The paper A Longitudinal Study of Static Analysis Warning Evolution and the Effects of PMD on Software Quality in Apache Open Source Projects is joint work by Alexander Trautsch, Steffen Herbold, and Jens Grabowski and addresses research questions regarding the evolution of the internal software code quality with respect to warning of static analysis tools. Our study shows that, on average, the code quality improved in the last two decades, mainly due to better coding guidelines, that, e.g., prohibit if-statements without an explicit if-block with {}. These quality improvements seem to be largely independent from the active use of static analysis tools within the build pipeline the projects. 

The paper On the Feasibility of Automated Prediction of Bug and Non-Bug Issues is joint work by Steffen Herbold, Alexander Trautsch, and Fabian Trautsch and deals with the question if machine learning can help to identify which issue reports describe bugs. We find that state-of-the-art models are almost as accurate as software developers and that such models, especially if trained on huge amounts of data, tend have a very high recall, i.e., hardly miss bugs. 

Paper accepted at the Journal of Systems and Software

26.08.2020
We are happy to announce that our paper A Systematic Mapping Study of Developer Social Networks was accepted for publication of the Journal of Systems and Software. The paper is joint work of Steffen Herbold, Aynur Amirfallah, Fabian Trautsch, and Jens Grawboski and presents the results of our literature survey regarding developer social networks in research that covers research topics, data sources and scope of experiments, influential papers and authors, as well as recent trends. 

Paper accepted at Expert Systems with Application

26.08.2020
We are happy to announce that the article A Multi-Objective Anytime Rule Mining System to Ease Iterative Feedback from Domain Experts was accepted for publication in the Journal Expert Systems with Applications. The article was joint work by Tobias Baum, Steffen Herbold, and Kurt Schneider and discusses a genetic algorithm, that can be used to learn rules in disjunctive normal form, such that experts not only understand the outcome of the learning process, but are directly able to influence the result of the algorithm through the interactive definition of restrictions on the solution space. 

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