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Paper on Ontology-based Approach for Software Architecture Recommendations accepted to the 23rd Americas Conference on Information Systems (AMCIS 2017)


The design and development of sustainable software systems require software architects to consider a variety of architectural solutions and their trade-offs. With the frequent introduction of new architectural methods and software solutions, as well as, due to time-to-market constraints faced by software architects, considering even a subset of alternative architectural solutions during the decision-making process is a challenge. In this paper, we propose a recommendation system that automatically annotates architectural elements in software architecture documents and then proposes a) alternative architectural solutions for the annotated elements and b) concrete software solutions to realize an architectural design decision. These annotations and recommendations are derived from the knowledge captured in a publicly available cross-domain ontology. The evaluation of the recommendation system indicates that our approach can effectively support software architects to consider alternative architectural solutions while making architectural design decisions.

Sebis & SocioCortex Workshops Friday, 21st September 2017

The next SocioCortex Workshop will take place in conjunction with the next Sebis workshop on Thursday, 21st March 2017: Sebis Workshop 

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Paper on Informatikforschung für digitale Mobilitätsplattformen is published in Informatik-Spektrum


A joint paper of the TUM Living Lab Connected Mobility (TUM LLCM) research project is published in Informatik-Spektrum which can be accessed here.


The TUM Living Lab Connected Mobility (TUM LLCM) research project was initiated to support the digital transformation in the area of Smart Mobility and Smart City. The project bundles the relevant research, implementation, and innovation capabilities of the Technical University of Munich in informatics and transport research. The research project contributes to the design and implementation of open, provider-independent digital mobility platforms. The actual implementation of these platforms is carried out by commercial providers taking into account the market requirements of customer-oriented mobility solutions. This paper uses the example of the TUM LLCM project to illustrate, how the Technical University of Munich combines competences of several research fields in informatics by means of innovative use cases to achieve timely results relevant for society in close collaboration with stakeholders outside of research.

Short paper on automatic uncertainty detection in software architecture documentation accepted

The short paper on automatic uncertainty detection in software architecture documentation got accepted at IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE 2017 Young Research Forum (Gothenburg, Sweden). In this paper, we motivate the usage of natural language processing techniques to detect the uncertainty cues in the software architecture documents. As an initial step of our study, we analyzed three real-world software architecture documents and manually retrieved examples of different types of uncertainties. Based on those examples, we formulated the hypothesis on how the communication of software architecture to its stakeholders could be positively supported by on-time uncertainty detection in software architecture documents. In the end, we outlined our future work and chosen research methodology.

Paper on automated extraction of semantic information from german legal documents is nominated for LexisNexis Best Paper Award

Accepted for LexisNexis Best Paper Award



Based on a collaborative data science environment, and a large document corpus (> 130.000 documents from German tax law) we demonstrate the extraction of semantic information. This paper shows the potential of rule-based text analysis to automatically extract semantic information, such as the year of dispute in cases. Additionally, it demonstrates the extraction of legal definitions in laws and the usage of terms in a defining context. Based on an iterative and interdisciplinary process, involving legal experts, software engineers, and data scientists, to evaluate and continuously refine the model used for the computer-supported extraction.