Guenter Hesse

Research Assistant, PhD Candidate

	Phone	+49 (331) 5509 - 1381
	Fax	+49 (331) 97992 - 579
	E-Mail	guenter.hesse(at)hpi.de
	Room	Hasso-Plattner-Villa, V 2.03
	Profiles	LinkedIn, XING, ResearchGate

Research Topics

Data Stream Processing
Performance Benchmarking
Industry 4.0 and Internet of Things

Teaching Activities

Summer Term 2018 - Trends and Concepts in Software Industry I
Winter Term 2017/2018 - Application of Causal Inference in Automotive Production
Summer Term 2017 - Trends and Concepts in Software Industry I
Summer Term 2016 - Unternehmensanwendungen: Prozesse, Modelle und Implementierung
Winter Term 2015/2016 - Developing Applications for the Internet of Things

Publications

Matthies, C., Teusner, R., Hesse, G.: Beyond Surveys: Analyzing Software Development Artifacts to Assess Teaching Efforts. 2018 IEEE Frontiers in Education Conference (FIE) (2018).

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@inproceedings{matthies2018fie, abstract = {This Innovative Practice Full Paper presents an approach of using software development artifacts to gauge student behavior and the effectiveness of changes to curriculum design. There is an ongoing need to adapt university courses to changing requirements and shifts in industry. As an educator it is therefore vital to have access to methods, with which to ascertain the effects of curriculum design changes. In this paper, we present our approach of analyzing software repositories in order to gauge student behavior during project work. We evaluate this approach in a case study of a university undergraduate software development course teaching agile development methodologies. Surveys revealed positive attitudes towards the course and the change of employed development methodology from Scrum to Kanban. However, surveys were not usable to ascertain the degree to which students had adapted their workflows and whether they had done so in accordance with course goals. Therefore, we analyzed students' software repository data, which represents information that can be collected by educators to reveal insights into learning successes and detailed student behavior. We analyze the software repositories created during the last five courses, and evaluate differences in workflows between Kanban and Scrum usage.}, author = {Matthies, Christoph and Teusner, Ralf and Hesse, Guenter}, booktitle = {2018 IEEE Frontiers in Education Conference (FIE)}, keywords = {development_artifacts software_engineering Kanban Scrum Education}, note = {(accepted)}, title = {Beyond Surveys: Analyzing Software Development Artifacts to Assess Teaching Efforts}, year = 2018 }
Hesse, G., Reissaus, B., Matthies, C., Lorenz, M., Kraus, M., Uflacker, M.: Senska - Towards an Enterprise Streaming Benchmark. In: Raghunath, N. and Meikel, P. (eds.) Performance Evaluation and Benchmarking for the Analytics Era. pp. 25-40. Springer International Publishing, Cham (2018).

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@inproceedings{hesse2018senska, abstract = {In the light of growing data volumes and continuing digitization in fields such as Industry 4.0 or Internet of Things, data stream processing have gained popularity and importance. Especially enterprises can benefit from this development by augmenting their vital, core business data with up-to-date streaming information. Enriching this transactional data with detailed information from high-frequency data streams allows answering new analytical questions as well as improving current analyses, e.g., regarding predictive maintenance. Comparing such data stream processing architectures for use in an enterprise context, i.e., when combining streaming and business data, is currently a challenging task as there is no suitable benchmark.}, address = {Cham}, author = {Hesse, Guenter and Reissaus, Benjamin and Matthies, Christoph and Lorenz, Martin and Kraus, Milena and Uflacker, Matthias}, booktitle = {Performance Evaluation and Benchmarking for the Analytics Era}, editor = {Raghunath, Nambiar and Meikel, Poess}, keywords = {benchmarking data_stream_processing senska}, pages = {25-40}, publisher = {Springer International Publishing}, title = {Senska - Towards an Enterprise Streaming Benchmark}, type = {Publication}, year = 2018 }
Lorenz, M., Rudolph, J.-P., Hesse, G., Uflacker, M., Plattner, H.: Object-Relational Mapping Revisited-A Quantitative Study on the Impact of Database Technology on O/R Mapping Strategies. Proceedings of the 50th Hawaii International Conference on System Sciences (2017).

[ BibTeX ]

@inproceedings{lorenz2017objectrelational, author = {Lorenz, Martin and Rudolph, Jan-Peer and Hesse, Guenter and Uflacker, Matthias and Plattner, Hasso}, booktitle = {Proceedings of the 50th Hawaii International Conference on System Sciences}, keywords = {in-memory_database}, title = {Object-Relational Mapping Revisited-A Quantitative Study on the Impact of Database Technology on O/R Mapping Strategies}, year = 2017 }
Hesse, G., Matthies, C., Reissaus, B., Uflacker, M.: A New Application Benchmark for Data Stream Processing Architectures in an Enterprise Context: Doctoral Symposium. Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems. pp. 359-362. ACM, New York, NY, USA (2017).

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@inproceedings{Guenter2017a, abstract = {Against the backdrop of ever-growing data volumes and trends like the Internet of Things (IoT) or Industry 4.0, Data Stream Processing Systems (DSPSs) or data stream processing architectures in general receive a greater interest. Continuously analyzing streams of data allows immediate responses to environmental changes. A challenging task in that context is assessing and comparing data stream processing architectures in order to identify the most suitable one for certain settings. The present paper provides an overview about performance benchmarks that can be used for analyzing data stream processing applications. By describing shortcomings of these benchmarks, the need for a new application benchmark in this area, especially for a benchmark covering enterprise architectures, is highlighted. A key role in such an enterprise context is the combination of streaming data and business data, which is barely covered in current data stream processing benchmarks. Furthermore, first ideas towards the development of a solution, i.e., a new application benchmark that is able to fill the existing gap, are depicted.}, address = {New York, NY, USA}, author = {Hesse, Guenter and Matthies, Christoph and Reissaus, Benjamin and Uflacker, Matthias}, booktitle = {Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems}, keywords = {Internet_of_Things Performance_Benchmarking Stream_Processing Benchmark_Development Data_Stream_Processing}, pages = {359-362}, publisher = {ACM}, series = {DEBS '17}, title = {A New Application Benchmark for Data Stream Processing Architectures in an Enterprise Context: Doctoral Symposium}, year = 2017 }
Lorenz, M., Hesse, G., Rudolph, J.-P.: Object-relational Mapping Revised - Guideline Review and Consolidation. Proceedings of the 11th International Joint Conference on Software Technologies (ICSOFT 2016) - Volume 1: ICSOFT-EA, Lisbon, Portugal, July 24 - 26, 2016. pp. 157-168 (2016).

[ BibTeX ]

@inproceedings{Martin2016a, author = {Lorenz, Martin and Hesse, Guenter and Rudolph, Jan-Peer}, booktitle = {Proceedings of the 11th International Joint Conference on Software Technologies {(ICSOFT} 2016) - Volume 1: ICSOFT-EA, Lisbon, Portugal, July 24 - 26, 2016.}, keywords = {imported}, pages = {157-168}, title = {Object-relational Mapping Revised - Guideline Review and Consolidation}, year = 2016 }
Hesse, G., Lorenz, M.: Conceptual Survey on Data Stream Processing Systems. Parallel and Distributed Systems (ICPADS), 2015 IEEE 21st International Conference on. 797-802 (2015).

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@article{Guenter2015a, author = {Hesse, Guenter and Lorenz, Martin}, journal = {Parallel and Distributed Systems (ICPADS), 2015 IEEE 21st International Conference on}, keywords = {Storm Flink Stream_Processing Samza Spark}, pages = {797-802}, title = {Conceptual Survey on Data Stream Processing Systems}, year = 2015 }