An important aspect of DAW dependability is the systematic detection and avoidance of misguided executions. Subproject A1 will approach this problem as query discovery problem: Given a set of execution traces of a DAW or a family of DAWs, find a set of concise queries over the log stream that separate runs that succeeded from those that fail. Query discovery, in contrast to statistical methods for failure prediction, has the advantage that queries can be understood more easily by the DAW developer, which makes adaptation of DAWs to avoid problematic situations possible. An important cooperation will be with B6, which focuses on detecting abnormal behavior at runtime. The project is carried out in cooperation between Prof. Schweikardt, an expert in logic and database theory, and Prof. Weidlich, an expert in event stream processing.
In: Olteanu, Dan; Vortmeier, Nils (Ed.): 25th International Conference on Database Theory, ICDT 2022, March 29 to April 1, 2022, Edinburgh, UK (Virtual Conference), pp. 18:1–18:21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.
In: Zhou, Yongluan; Chrysanthis, Panos K.; Gulisano, Vincenzo; Zacharatou, Eleni Tzirita (Ed.): 16th ACM International Conference on Distributed and Event-based Systems, DEBS 2022, Copenhagen, Denmark, June 27 - 30, 2022, pp. 31–42, ACM, 2022.
Scalable Discovery of Queries over Event Streams Inproceedings
In: Bao, Zhifeng; Sellis, Timos (Ed.): Proceedings of the VLDB 2022 PhD Workshop co-located with the 48th International Conference on Very Large Databases (VLDB 2022), Sydney, Australia, September 5, 2022, CEUR-WS.org, 2022.