Christoph Herrmann

Hamidreza Eivazi, André Hebenbrock, Raphael Ginster et al.

Battery degradation remains a critical challenge in the pursuit of green technologies and sustainable energy solutions. Despite significant research efforts, predicting battery capacity loss accurately remains a formidable task due to its complex nature, influenced by both aging and cycling behaviors. To address this challenge, we introduce a novel general-purpose model for battery degradation prediction and synthesis, DiffBatt. Leveraging an innovative combination of conditional and unconditional diffusion models with classifier-free guidance and transformer architecture, DiffBatt achieves high expressivity and scalability. DiffBatt operates as a probabilistic model to capture uncertainty in aging behaviors and a generative model to simulate battery degradation. The performance of the model excels in prediction tasks while also enabling the generation of synthetic degradation curves, facilitating enhanced model training by data augmentation. In the remaining useful life prediction task, DiffBatt provides accurate results with a mean RMSE of 196 cycles across all datasets, outperforming all other models and demonstrating superior generalizability. This work represents an important step towards developing foundational models for battery degradation.

Michael Kirchhof, Klaus Haas, Thomas Kornas et al.

The production of lithium-ion battery cells is characterized by a high degree of complexity due to numerous cause-effect relationships between process characteristics. Knowledge about the multi-stage production is spread among several experts, rendering tasks as failure analysis challenging. In this paper, a new method is presented that includes expert knowledge acquisition in production ramp-up by combining Failure Mode and Effects Analysis (FMEA) with a Bayesian Network. Special algorithms are presented that help detect and resolve inconsistencies between the expert-provided parameters which are bound to occur when collecting knowledge from several process experts. We show the effectiveness of this holistic method by building up a large scale, cross-process Bayesian Failure Network in lithium-ion battery production and its application for root cause analysis.

Christoph Herrmann, Holger Krahn, Bernhard Rumpe et al.

Due to the increased complexity of software development projects more and more systems are described by models. The sheer size makes it impractical to describe these systems by a single model. Instead many models are developed that provide several complementary views on the system to be developed. This however leads to a need for compositional models. This paper describes a foundational theory of model composition in form of an algebra to explicitly clarify different variants and uses of composition, their interplay with the semantics of the involved models and their composition operators.

Christian Bartelt, Manfred Broy, Christoph Herrmann et al.

Global software engineering has become a fact in many companies due to real necessity in practice. In contrast to co-located projects global projects face a number of additional software engineering challenges. Among them quality management has become much more difficult and schedule and budget overruns can be observed more often. Compared to co-located projects global software engineering is even more challenging due to the need for integration of different cultures, different languages, and different time zones - across companies, and across countries. The diversity of development locations on several levels seriously endangers an effective and goal-oriented progress of projects. In this position paper we discuss reasons for global development, sketch settings for distribution and views of orchestration of dislocated companies in a global project that can be seen as a "virtual project environment". We also present a collection of questions, which we consider relevant for global software engineering. The questions motivate further discussion to derive a research agenda in global software engineering.

Christoph Herrmann, Holger Krahn, Bernhard Rumpe et al.

Model-based development and in particular MDA [1], [2] have promised to be especially suited for the development of complex, heterogeneous, and large software systems. However, so far MDA has failed to fulfill this promise to a larger extent because of tool support being inadequate and clumsy and methodologies not being appropriate for an effective development. This article discusses what went wrong in current MDA approaches and what needs to be done to make MDA suited for ultra-large, distributed systems.

Christoph Herrmann, Thomas Kurpick, Bernhard Rumpe

Tools are an essential part of every software engineering project. But the number of tools that are used in all phases of the software development life-cycle and their complexity is growing continually. Consequently, the setup and maintenance of current tool chains and development environments requires much effort and consumes a lot of time. One approach to counter this, is to employ web-based systems for development tasks, because centralized systems simplify the administration and the deployment of new features. But desktop IDEs play an important role in software development projects today, and will not be replaced entirely by web-based environments in the near future. Therefore, supporting a mixture of hosted tools and tools integrated into desktop IDEs is a sensible approach. In this paper, we present the SSELab, a framework for web- based project portals that attempts to migrate more software development tools from desktop to server environments, but still allows their integration into modern desktop IDEs. It supports the deployment of tools as hosted services using plug-in systems on the server-side. Additionally, it provides access to these tools by a set of clients that can be used in different contexts, either from the command line, from within IDEs such as Eclipse, or from web pages. In the paper, we discuss the architecture and the extensibility of the SSELab framework. Furthermore, we share our experiences with creating an instance of the framework and integrating various tools for our own software development projects.

Olga Liskin, Christoph Herrmann, Eric Knauss et al.

During acceptance testing customers assess whether a system meets their expectations and often identify issues that should be improved. These findings have to be communicated to the developers a task we observed to be error prone, especially in distributed teams. Here, it is normally not possible to have developer representatives from every site attend the test. Developers who were not present might misunderstand insufficiently documented findings. This hinders fixing the issues and endangers customer satisfaction. Integrated feedback systems promise to mitigate this problem. They allow to easily capture findings and their context. Correctly applied, this technique could improve feedback, while reducing customer effort. This paper collects our experiences from comparing acceptance testing with and without feedback systems in a distributed project. Our results indicate that this technique can improve acceptance testing if certain requirements are met. We identify key requirements feedback systems should meet to support acceptance testing.