Seminar Software Engineering
Der Lehrstuhl SEDA betreut im Wintersemester 2019/20 das gemeinsame Software Engineering Seminar für Bachelor- und Masterstudenten. Das Ziel des Seminars ist die Einführung in das kritische Lesen, Verstehen, Zusammenfassen und Präsentieren von wissenschaftlichen Arbeiten. Inhalte sind ausgewählte Themen aus dem Bereich Software und Systems Engineering, insbesondere:
- Systems Engineering for Cyber-Physical Systems
- Safety, Security, Reliability and Availability
- Risk-Assessment and -Minimization
- Model-Based Safety Analysis
Aktuelles und Mitteilungen
21.02.2020 | Die Termine für die Präsentationen wurden bekannt gegeben. Meldet uns etwaige Probleme bitte möglichst bald. |
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25.10.2019 | Die Folien vom Kick-Off Treffen können unten beim Zeitplan heruntergeladen werden. |
23.10.2019 | Die Themenzuweisung wurde vorgenommen und per E-Mail bekannt gegeben. |
16.10.2019 | Wir haben das Thema T5 entfernt, weil es ein Duplikat von T15 war. Eure bereits eingereichten Präferenzen wurden automatisch aktualisiert, indem T5 durch T15 ersetzt wurde (gleiches Thema). |
15.10.2019 | Die verfügbaren Seminarthemen wurden veröffentlicht. Um euch für Seminarthemen zu bewerben, befolgt bitte die unten beschriebenen Schritte. |
14.10.2019 | Die Sammlung der Seminarthemen hat dieses Semester etwas länger gedauert. Wir werden die Themen voraussichtlich morgen veröffentlichen und das Kick-off Treffen um eine Woche verschieben. Näheres dazu werden wir morgen in einer Rundmail ankündigen. |
18.09.2019 | Die Anmeldung ist absofort möglich. Weitere Informationen sind unten im Abschnitt Anmeldung zu finden. |
Präsentationen
Block 1
Datum: | Mo, 02.03.2020 |
Beginn: | 13:00 Uhr |
Raum: | 46-267 |
Uhrzeit | Thema | Dauer | Student(en) | Titel | Betreuer |
---|---|---|---|---|---|
13:00 | T10 | 15 min | Katarina Zejnulovic | Application of Explainable Artificial Intelligence (XAI) concepts to Generative Adversarial Networks (GAN) | Christian |
T12 | 20 min | Jacques Dörner | Overview of Importance Measures for Basic Events in Fault Trees | Felix | |
Sevilay Akkus | |||||
T18 | 25 min | Bavithira Gnanasegaram | Adaptation of Service-oriented Architectures to different domains | Frank | |
Rohit Jain | |||||
Priom Biswas | |||||
14:00 | Puffer + Pause | ||||
14:20 | T21 | 15 min | Jiradet Ounjai | A Systematic Literature Review on using High-Performance Computing in the automotive domain | Emilia |
T6 | 25 min | Christoph Zwick | Survey of hardware platforms for automotive model demonstrators in a research context | Tewanima | |
Martin Böh | |||||
Fahia Nasnin | |||||
T15 | 20 min | Tayyaba Seher | Why autonomous driving? A non-technical use-case analysis | Tewanima | |
Clement John Shaji | |||||
15:45 | Ende |
Block 2
Datum: | Mi, 11.03.2020 |
Beginn: | 9:00 Uhr |
Raum: | 46-267 |
Uhrzeit | Thema | Dauer | Student(en) | Titel | Betreuer |
---|---|---|---|---|---|
9:00 | T1 | 25 min | Frank Eric Mbouga | Software Engineering of Self-adaptive Systems | Rasha |
Daniel Mamat | |||||
Kevin Kaißling | |||||
T2 | 15 min | Vlad-Cristian Constantin | Testing of Self-adaptive Systems | Rasha | |
T3 | 15 min | Florian Wirschem | Self-adaptive Systems Design Using Control Engineering Approaches | Rasha | |
10:00 | Puffer + Pause | ||||
10:15 | T7 | 15 min | Raghad Matar | Security threats caused by compiler optimizations | Jasmin |
T8 | 20 min | Poorvi Sahai | Computing use cases for edge computing | Jasmin | |
Sushmitha Kalluri | |||||
T9 | 20 min | Junhan Sui | Performance in microservice-based systems | Jasmin | |
Talant Asankozhoev | |||||
11:30 | Ende |
Block 3
Datum: | Do, 12.03.2020 |
Beginn: | 12:00 Uhr |
Raum: | 46-267 |
Uhrzeit | Thema | Dauer | Student(en) | Titel | Betreuer |
---|---|---|---|---|---|
12:00 | T4 | 15 min | Marvin Caspar | Automatic Derivation of Fault Tree Models from SysML Models for Safety Analysis | Tewanima |
T13 | 20 min | Jonas Brozeit | Openness - A Vital facet of Industry 4.0? | Nishanth | |
Nathalie Hippchen | |||||
T14 | 15 min | Florian Weick | Co-operative adaptive Cruise control (CACC) in real world traffic scenarios | Nishanth | |
12:50 | Puffer + Pause | ||||
13:10 | T16 | 15 min | Theogene Urimubenshi | A Survey on research challenges and engineering practices for Smart Embedded System | Anil |
T22 | 15 min | Rudolf Wagner | Writing of successful research paper in the Dependability Community | Emilia | |
14:00 | Ende |
Themenübersicht
Hinweis: Durch Klicken auf ein Thema wird die Detailansicht geöffnet.
Abhängig von den Betreuern können nicht alle Themen in allen Sprachen bearbeitet werden. Bei einigen Themen ist Gruppenarbeit möglich.
Beschreibung :
Self-adaptation has become a hot topic within the system engineering community. It has introduced several challenges to the traditional software engineering activities. The goal of this work is to identify these challenges in the different software development steps and to analyse the so far proposed solutions for them.
Literatur :
- M. Bellare and P. Rogaway, Software Engineering for Self-Adapting Systems, vol. 1070. 2009.
- Betty H.C. Cheng, Rogerio de Lemos, Holger Giese, Paola Inverardi, Software Engineering for Self-Adaptive Systems: A Research Roadmap, 2009.
Betreuer:
Rasha Abu Qasem
Beschreibung :
The provision of assurances for self-adaptive systems is challenging since runtime changes introduce a high degree of uncertainty. The goal of this work is to address the challenge of self-adaptive systems testing and to classify the solutions provided until now for it, then to argue about their feasibility.
Literatur :
- P. Helle, W. Schamai, and C. Strobel, “Testing of Autonomous Systems - Challenges and Current State-of-the-Art,” INCOSE Int. Symp., vol. 26, no. 1, pp. 571–584, 2016.
- R. de Lemos et al., “Software engineering for self-adaptive systems: research challenges in the provision of assurances,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 9640 LNCS, no. December 2013, pp. 3–30, 2017.
Betreuer:
Rasha Abu Qasem
Beschreibung :
Control engineering approaches have been identified as a promising tool to integrate self-adaptive capabilities into software systems. The goal of this work is to compare the different control engineering approaches. Then to show how they are elaborated in the design process of self-adaptive software systems.
Literatur :
- T. Patikirikorala, A. Colman, J. Han, and L. Wang, “A systematic survey on the design of self-adaptive software systems using control engineering approaches,” ICSE Work. Softw. Eng. Adapt. Self-Managing Syst., pp. 33–42, 2012.
Betreuer:
Rasha Abu Qasem
Beschreibung :
Fault Tree models are a necessity for the state of the art Fault Tree Safety Analysis. This paper proposes an approach for integrating safety analysis of safety critical systems into the model-driven engineering workflow. To that end SysML system models are automatically transformed into Fault Tree models.
Literatur :
Beschreibung :
Compare 5 automotive model kits with respect to their feasibility of use as hardware demonstrators in a scientific reasearch context. Every demonstrator is to be analyzed and compared according to at least these parametes:
- Hardware
- hardware capability & features
- extensibility
- robustness
- performance
- Software
- existing toolkits
- API features
- supported development environments
- size and quality of documentation
- Scientific community
- existing research projects
- known problems
Betreuer:
Brian Tewanima Löwe
Beschreibung :
Compilers today apply extremely powerful and complex optimization algorithms. While these optimizations significantly improve execution performance (e.g., by re-ordering instructions), they might impose new vulnerabilities in software (e.g., some redundancies are irrelevant for functionality, but they might be relevant for other properties). Functionality of the optimized binary might be proper, but the optimizations can affect quality properties. Lately, security breaches due to compiler optimizations are becoming increasingly important topic in research and industry. This seminar will gather detected examples of security breaches caused by compiler optimizations, approaches and notations for specifying security-related properties that should not be violated (i.e., testing criteria) by compiler optimizations, and approaches for finding compiler optimizations-caused security bugs.
Literatur :
- The Correctness-Security Gap in Compiler Optimization, D'Silva et al., 2015 - https://ieeexplore.ieee.org/document/7163211
- What You Get is What You C: Controlling Side Effects in Mainstream C Compilers, L. Simon, 2018 - https://ieeexplore.ieee.org/document/8406587
- Secure Compilation and Hyperproperty Preservation, M. Patrignani, 2017 - https://ieeexplore.ieee.org/document/8049734
Betreuer:
Jasmin Jahić
Beschreibung :
With the increase in the computing requirements, computing industry responded with multicore and manycore processors and cloud computing. However, lately industry is facing problems with the lack of computing resources on devices and latencies caused by the need to communicate with cloud. As the answer, we have lately seen rise of the edge computing. This seminar aims to investigate: Concepts of the edge computing, Industrial use cases suitable for edge computing, Performance advantages of the edge computing over cloud and many-core on device computing.
Literatur :
- Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing, K. Dolui, 2017 - https://ieeexplore.ieee.org/document/8016213
- Fog at the Edge: Experiences Building an Edge Computing Platform, Nam Ky Giang, 2018 - https://ieeexplore.ieee.org/document/8473371
- Edge Computing Perspectives: Architectures, Technologies, and Open Security Issues, M. Caprolu, 2019 - https://ieeexplore.ieee.org/document/8812214
- Embedded Deep Learning for Vehicular Edge Computing, J. Hochstelter, 2018 - https://ieeexplore.ieee.org/document/8567683
- MVR: An Architecture for Computation Offloading in Mobile Edge Computing, X. Wei, 2017 - https://ieeexplore.ieee.org/document/8029283
Betreuer:
Jasmin Jahić
Beschreibung :
In today’s industry, rising architectural style is based on microservices. The idea of this style is to distribute and partition a software system to small services with clearly separated functionalities and fixed interfaces. While developers and architects have recognized great benefits from this separation of concerns, the remaining question is: how does the microservice style influence performance of software systems? This seminar aims to research about existing case studies in the area of performance of microservices with the focus on performance. Besides explaining microservices with examples (code and models), it will focus on identifying architectural properties that affect performance of software systems and that are directly affected by the microservices pattern.
Literatur :
- Performance evaluation in the migration process from a monolithic application to microservices, D. Guaman et al., 2018 - https://ieeexplore.ieee.org/document/8399148
- Microservices: The Journey So Far and Challenges Ahead, P. Jamshidi, 2018 - https://ieeexplore.ieee.org/abstract/document/8354433
Betreuer:
Jasmin Jahić
Beschreibung :
The advent of deep neural networks pushed many fields in automatic recognition, i.e. voice recognition and picture/video analysis. Nevertheless, the trained models give no direct insight why they produce for certain input the corresponding output. The student give an overview of existing explanation approaches and their goals.
Literatur :
- Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models. Wojciech Samek, Thomas Wiegand, Klaus-Robert Müller. 2017. https://arxiv.org/abs/1708.08296
- F. K. Došilović, M. Brčić and N. Hlupić, "Explainable artificial intelligence: A survey," 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, 2018, pp. 0210-0215. doi: 10.23919/MIPRO.2018.8400040 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8400040&isnumber=8399814
- A. Adadi and M. Berrada, "Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)," in IEEE Access, vol. 6, pp. 52138-52160, 2018. doi: 10.1109/ACCESS.2018.2870052 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8466590&isnumber=8274985
Betreuer:
Christian Wolschke
Beschreibung :
The analysis of Deep neural networks (DNN) is crucial to ensure the quality of the trained model. In order to find different and test different input classes, multiple methods exists. The student should investigate, how the methods described in the reference list work and how they are interrelated. Beyond the given papers, further work should also be examined.
Literatur :
- Investigating Layer Activation Patterns in Neural Networks for Classification Error Detection. Victor DEMUYSERE. 2018. https://dial.uclouvain.be/memoire/ucl/en/object/thesis%3A17232/datastream/PDF_01/view
- Runtime Monitoring Neuron Activation Patterns. Chih-Hong Cheng, Georg Nührenberg, Hirotoshi Yasuoka. 2018. https://arxiv.org/abs/1809.06573
- Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV). Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viegas, Rory Sayres. 2018. https://arxiv.org/abs/1711.11279
- Testing Deep Neural Networks. 2019. Youcheng Sun, Xiaowei Huang, Daniel Kroening, James Sharp, Matthew Hill, Rob Ashmore. https://arxiv.org/abs/1803.04792
- Samarasinghe S. (2016) Order in the Black Box: Consistency and Robustness of Hidden Neuron Activation of Feed Forward Neural Networks and Its Use in Efficient Optimization of Network Structure. In: Shanmuganathan S., Samarasinghe S. (eds) Artificial Neural Network Modelling. Studies in Computational Intelligence, vol 628. Springer, Cham
- Not Just a Black Box: Learning Important Features Through Propagating Activation Differences. Avanti Shrikumar, Peyton Greenside, Anna Shcherbina, Anshul Kundaje. 2017. https://arxiv.org/abs/1605.01713
- M. Kahng, P. Y. Andrews, A. Kalro and D. H. Chau, "ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models," in IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 1, pp. 88-97, Jan. 2018. doi: 10.1109/TVCG.2017.2744718 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8022871&isnumber=8165924
- Youcheng Sun, Min Wu, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska, and Daniel Kroening. 2018. Concolic testing for deep neural networks. In Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE 2018). ACM, New York, NY, USA, 109-119. DOI: https://doi.org/10.1145/3238147.3238172
Betreuer:
Christian Wolschke
Beschreibung :
Fault trees are a widely used modeling technique for system failures and their causes. System failures (top events) are modeled as a logical concatenation of events at a lower level in the system (basic events). On the basis of a fault tree model, various analyses can be carried out, e.g. in order to evaluate the safety or reliability of the system. Thereby, the influence of individual basic events on the top event can vary considerably, as some system parts are more critical than others. The aim of this work is to give an overview of various metrics that can be used to evaluate the importance of basic events.
Literatur :
- Borgonovo, Emanuele. "Differential, criticality and Birnbaum importance measures: An application to basic event, groups and SSCs in event trees and binary decision diagrams." Reliability Engineering & System Safety 92.10 (2007): 1458-1467 - https://www.sciencedirect.com/science/article/pii/S095183200600216X
Betreuer:
Felix Möhrle
Beschreibung :
Openness is defined in several ways in various fields. Openness with respect to systems engineering, is a scenario where in different systems can integrate with each other during operation to share information or exchange important certificates to achieve a common goal. Similarly, openness is defined in different way in case of industrial production. The ever changing market trends, customer specific requirements for various products have triggered the need of new production systems which are flexible and adaptable to these. But openness is another step further, in Production systems. Openness can be a solution to handle this ever changing market needs and make manufacturer a competent player in today’s economy. Flexible and adaptable production systems are of prime focus in Germany led vision of “Industry 4.0”, but can openness also be a vital facet of this vision?
Literatur :
- Redlich, Tobias, et al. "The Strategy of Openness in industrial production." Management of Engineering and Technology (PICMET), 2015 Portland International Conference on. IEEE, 2015.
- Wulfsberg, Jens Peter, Tobias Redlich, and Franz-Ludwig Bruhns. "Open production: scientific foundation for co-creative product realization." Production Engineering 5.2 (2011): 127-139.
- Propris, Lisa De, Stefano Menghinello, and Roger Sugden. "The internationalisation of production systems: embeddedness, openness and governance." Entrepreneurship and regional development 20.6 (2008): 493-515.
- https://news.sap.com/2018/01/industrie-4-0-why-openness-and-collaboration-make-all-the-difference/
- Anderl, R., et al. "Aspects of the research roadmap in application scenarios." Federal Ministry for Economic Affairs and Energy, Tech. Rep. (2016)
Betreuer:
Nishanth Laxman
Beschreibung :
CACC is extended version of Adaptive cruise control in cars. Systems / Vehicles with CACC are being used to form platoons on highways and claim to improve Performance, fuel efficiency while considering the safety of own and other vehicles, and humans involved as well. It will be interesting to know, exactly to what extent is it advantageous and feasible in actual traffic scenarios, which are highly dynamic in nature and also see if such systems can be reliable.
Literatur :
- Naus, Gerrit, et al. "Cooperative adaptive cruise control." IEEE automotive engineering symposium Eindhoven, The Netherlands. Vol. 6. 2009.
- Van Arem, Bart, Cornelie JG Van Driel, and Ruben Visser. "The impact of cooperative adaptive cruise control on traffic-flow characteristics." IEEE Transactions on Intelligent Transportation Systems 7.4 (2006): 429-436.
- Milanés, Vicente, et al. "Cooperative Adaptive Cruise Control in Real Traffic Situations." IEEE Trans. Intelligent Transportation Systems 15.1 (2014): 296-305.
- Shladover, Steven, Dongyan Su, and Xiao-Yun Lu. "Impacts of cooperative adaptive cruise control on freeway traffic flow." Transportation Research Record: Journal of the Transportation Research Board 2324 (2012): 63-70.
Betreuer:
Nishanth Laxman
Beschreibung :
In modern times everyone is pushing towards autonomous vehicles and driving. But before the very challenging technical questions should be addressed, many hard questions w.r.t. the use-case must be answered:
- What is to be gained from autonomous driving?
- Why are advanced driving assistence systems (ADAS) not sufficient?
- Do these two approaches (autonomous vs. ADAS) complement or contradict each other?
- Is autonomous driving a successor of ADAS or a parallel development?
- How feasible are both approaches?
- Where do we stop w.r.t. both approaches?
The topic has a stronger focus on economic than on technical aspects and is particularly suitable for students of Wirtschaftsingenieurswesen.
Betreuer:
Nishanth Laxman
Beschreibung :
A smart embedded system has gained popularity in recent years and increasingly work in safety-critical dynamic environment with complex System of Systems architecture. To address this, an approach to find out the hidden challenges associated with the intelligent systems, as well as state of the art engineering practices that support the development of smart embedded systems, needs to be identified.
Goal: A literature survey must be conducted to address the associated challenges with the development of Smart Embedded System. In addition, a survey also includes the current state of the art engineering practices that increases intelligence in the Embedded systems. (Tip: Engineering practices can be in any application domain, e.g., Automotive, Railways, Medical etc.)
Keywords:- Embedded Systems, Intelligence for Embedded Systems, Smart Embedded Systems, Self-Aware/Context-Aware Embedded System, Embedded Intelligence.
Literatur :
- Dutt, N., Jantsch, A., and Sarma, S. (2016). Toward smart embedded systems: A self-aware system-on-chip (soc) perspective. ACM Transactions on Embedded Computing Systems (TECS), 15(2), 22.
- Baunach, M., Gomes, R. M., Malenko, M., Mauroner, F., Ribeiro, L. B., and Scheipel, T. (2018). Smart mobility of the future–a challenge for embedded automotive systems. e & i Elektrotechnik und Informationstechnik, 135(4-5), 304-308.
- Krupitzer, C., Breitbach, M., Roth, F. M., VanSyckel, S., Schiele, G., and Becker, C. (2018). A survey on engineering approaches for self-adaptive systems (extended version).
Betreuer:
Anil Patel
Beschreibung :
The development progress of autonomous vehicles is limited due to the increased level of uncertainty resulting from the enormous number of possible scenarios. Even artificial neural networks are not sufficient to reliably classify situations. Therefore, an approach is required to identify the edge case and corner case for autonomous vehicles is required with respect to the boundary case and base case.
Goal: - Different types of the edge case, corner case, boundary case and base case with respect to Autonomous Vehicles have to be collected and discussed it in detail. (Tip: - Edge case is a problem that happens very rarely while corner case occurs only outside the operational domain)
Keywords: - Autonomous Vehicle, Edge case, Corner Case, Boundary Case, Base Case, Use cases for Autonomous Driving, Scenarios for Autonomous Vehicles.
Literatur :
- Wachenfeld, W., Winner, H., Gerdes, J. C., Lenz, B., Maurer, M., Beiker, S., ... and Winkle, T. (2016). Use cases for autonomous driving. In Autonomous driving (pp. 9-37). Springer, Berlin, Heidelberg.
- Fridman, L., Jenik, B., and Reimer, B. (2017). Arguing machines: Perception control system redundancy and edge case discovery in real-world autonomous driving. arXiv preprint arXiv:1710.04459.
- Zhao, D. (2016). Accelerated Evaluation of Automated Vehicles.
Betreuer:
Anil Patel
Beschreibung :
SOA (or microservices) is used to decouple static connections between service providers and service consumers. This enables quick introduction of new service providers or exchange of existing service implementations. However, is it applicable to different domains like Industrie 4.0 or Smart Grinds without adaptation efforts or introduction of new aspects like simulation models?
Expectations:
- Detailed description of SOA (What are the core parts?)
- Overview over different domains in which SOA was applied
- Literature Research for each domain, showcasing the application and possible tailoring needed
Literatur :
- Rosen, Michael, et al. Applied SOA: service-oriented architecture and design strategies. John Wiley & Sons, 2012.
- Karnouskos, Stamatis, et al. "A SOA-based architecture for empowering future collaborative cloud-based industrial automation." IECON 2012-38th Annual Conference on IEEE Industrial Electronics Society. IEEE, 2012.
Betreuer:
Frank Schnicke
Themenauswahl
Um euch für Seminarthemen zu bewerben, geht bitte wie folgt vor:
Wählt in der obigen Liste Themen aus, die ihr gerne bearbeiten möchtet. Wir empfehlen euch, mehr als ein Thema zu wählen, da nicht jeder sein Wunschthema bearbeiten kann. Die Auswahl mehrerer Themen erhöht eure Chance, ein Thema zu erhalten.
Ordnet eure Auswahl absteigend nach Priorität, wie im folgenden Beispiel gezeigt:
T5 > T8 > T14Hier ist das Thema T5 die erste Wahl, T8 die zweite Wahl und T14 die dritte Wahl. Ihr könnt beliebig viele Themen auflisten.
Optional: Wenn bei einem oder mehreren eurer Themen Gruppenarbeit möglich ist und ihr bereits Kommilitonen kennt, mit denen ihr gerne zusammenarbeiten möchtet, dann teilt uns das bitte mit.
Listet dazu in einer zweiten Zeile die Namen eurer Kommilitonen auf, wie im folgenden Beispiel gezeigt:
Name1, Name2Diese Information ist unabhängig von eurer Themenwahl aus Schritt 1. Es genügt, wenn sich eure genannten Kommilitonen auf ein gleiches Thema bewerben wie ihr. Unser Algorithmus formt Gruppen bevorzugt aus Studierenden, die sich untereinander kennen. Ihr könnt euch aber auch allein für Themen mit Gruppenarbeit bewerben und werdet dann ggf. zufällig mit anderen Studierenden zusammengewürfelt.
Teilt uns bitte mit, ob ihr für das Seminar eine Note braucht. Klärt diese Frage im Zweifelsfall mit eurem zuständigen Prüfungsamt. Die meisten Studierenden erhalten in der Regel nur einen unbenoteten Schein.
Note: nein
Schickt uns diese Informationen in einer kurzen E-Mail bis Di, 22.10.2019 um 14 Uhr. Wir werden unser Bestes tun, um so viele von euch unterzubringen wie möglich.
Anmeldung
Die Anmeldung erfolgt mit einer kurzen E-Mail mit nachfolgenden Angaben.
- Name, Matrikelnummer
- Studiengang
- Bachelor oder Master
Die Anmeldefrist ist der 20.09.2019. Eine endgültige Zusage, wer am Seminar teilnehmen kann, können wir erst im Anschluss an die Anmeldefrist geben. In der Regel gibt es mehr Anmeldungen als verfügbare Themen, weshalb die freien Plätze ggf. ausgelost werden müsse
Zeitplan
Beim Kick-Off Treffen wird die Organisation des Seminars besprochen und der Kontakt zu den Betreuern aufgenommen. Nach einigen Wochen Einarbeitungszeit ist von den Teilnehmern ein Inhaltsverzeichnis mit einigen Stichpunkten zu den geplanten Inhalten der Arbeit zu erstellen. Im Folgenden erstellen alle Teilnehmer eine schriftliche Ausarbeitung zu ihrem Thema. Die Arbeiten sollten in regelmäßigen Treffen mit den Betreuern besprochen werden. Die erste Version der schriftlichen Ausarbeitung soll bis Mitte Januar fertiggestellt sein und dient als Grundlage für abschließendes Feedback durch die Betreuer. Die endgültige Fassung der Arbeit ist bis Anfang Februar fertigzustellen. Zuletzt werden die Arbeiten bei einem abschließenden Treffen präsentiert.
Kick-Off Treffen | 25.10.2019, 10:00 Uhr in Raum 46-267 (Folien) |
Annotiertes Inhaltsverzeichnis | 22.11.2019 |
Erste Version der Ausarbeitung | 17.01.2020 |
Finale Version der Ausarbeitung | 07.02.2020 |
Abschlusspräsentationen | Termin wird noch bekanntgegeben |
Material
Das Seminar wird auf Englisch angeboten. Bachelor-Studenten können zwischen Deutsch und Englisch wählen.
Schriftliche Ausarbeitung
Für die schriftliche Ausarbeitung ist die angepasste LNCS-Vorlage zu verwenden. Der Umfang sollte ca. 10 Seiten für Bachelor-Studenten bzw. ca. 15 Seiten für Master-Studenten betragen (exkl. Abbildungen).
Abschlusspräsentation
Für die Präsentationen stellen wir Vorlagen für PowerPoint, LibreOffice und LaTeX bereit. Die Vortragsdauer darf 15 Minuten (Bachelor) bzw. 20 Minuten (Master) nicht überschreiten.
Organisatoren
- Dozent: Prof. Dr.-Ing. Peter Liggesmeyer
- Betreuung und Ansprechpartner: Felix Möhrle