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Aktuelle Version vom 14. Januar 2022, 14:21 Uhr

Termin (Alle Termine)
Datum Fr 29. Mai 2020, 11:30 Uhr
Dauer 75 min
Webkonferenz Teams
Vorheriger Termin Fr 22. Mai 2020
Nächster Termin Fr 5. Juni 2020


Vortragende(r) Hannes Kuchelmeister
Titel Decision Support for Group-Based Configuration using Recommender Systems
Vortragstyp Bachelorarbeit
Betreuer(in) Robert Heinrich
Kurzfassung A group of people with diferent personal preferences wants to fnd a solution to a problem with high variability. Making decisions in the group comes with problems as a lack of communication leads to worse decision outcomes. Group dynamics and biases can lead to suboptimal decisions. Generally group decisions are complex and often the process that yields the

decision result is unstructured, thereby not providing any reproducibility of the success. Groups have different power structures and usually individuals have diferent interests. Moreover finding solutions is a rather complex task and group decisions can sufer intransparency. To support groups in their decision making product confguration can be used. It allows to accurately map constraints and dependencies in complex problems and to map the solution space. Using a group recommender a group is supported in their confguration decisions. The goal is to show that these approaches can help a group with the confguration task presented by the usage of a configurator and to better process individual preferences than a human can. The benefts of this approach are, that the need for a group to communicate directly is reduced. Each user gives their own preferences and the group will get a recommendation based on that. This allows to reduce problems arising in groups decisions like lack of communication and bias in groups. Additionally this shows the viability of combining group recommendations and configuration approaches.

Vortragende(r) Larissa Schmid
Titel Modeling and Simulation of Message-Driven Self-Adaptive Systems
Vortragstyp Masterarbeit
Betreuer(in) Jörg Henß
Kurzfassung Dynamic systems that reconfigure themselves use message queues as a common method to achieve decoupling between senders and receivers. Predicting the quality of systems at design time is crucial as changes in later phases of development get way more costly. At the moment, there is no method to represent message queues on an architectural level and predict their quality impact on systems. This work proposes a meta-model for enabling such representation and a simulation interface between a simulation of a component-based architecture description language and a messaging simulation. The interface is implemented for the Palladio simulator SimuLizar and an AMQP simulation. This enables architectural representation of messaging and predicting quality attributes of message-driven self-adaptive systems. The evaluation with a case study shows the applicability of the approach and its prediction accuracy for Point-To-Point communication.
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