B3: Debugging Distributed Data Analysis Workflows


Like other software, DAWs may show unexpected behavior or even crash due to various reasons. Debugging aims at establishing a cause effect relationship between the observable problem and the actual error. Such error identification serves as an initial step of a reliable problem resolution, and thus debugging of DAWs is an indispensable task to increase the dependability of DAWs. However, debugging DAWs is particularly challenging due to the heterogeneous nature of the involved tasks and the distributed nature of the execution engine. The central research question addressed in this subproject is how to enable domain scientists to efficiently formulate, test, and refine a debugging hypothesis in the context of scientific software engineering. It will primarily work together with A3 on the adaptation of software test technologies to distributed DAWs and with B6 on the distributed monitoring of DAW executions. The subproject will be coordinated by Prof. Kehrer, an expert in model-based software development, and Prof. Markl, an expert in large-scale distributed data analytics.




Jonathan Bader; Joel Witzke; Soeren Becker; Ansgar Lößer; Fabian Lehmann; Leon Doehler; Anh Duc Vu; Odej Kao

Towards Advanced Monitoring for Scientific Workflows Inproceedings

In: 2022 IEEE International Conference on Big Data (IEEE BigData 2022), IEEE, 2022.

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Anh Duc Vu; Timo Kehrer; Christos Tsigkanos

Outcome-Preserving Input Reduction for Scientific Data Analysis Workflows Inproceedings Forthcoming

In: Forthcoming.


Gábor E. Gévay; Tilmann Rabl; Sebastian Breß; Loránd Madai-Tahy; Jorge-Arnulfo Quiané-Ruiz; Volker Markl

Imperative or Functional Control Flow Handling: Why not the Best of Both Worlds? Journal Article

In: ACM SIGMOD Record, vol. 51, no. 1, pp. 1-8, 2022.

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Muhammad Imran; Gábor E. Gévay; Jorge-Arnulfo Quiané-Ruiz; Volker Markl

Fast datalog evaluation for batch and stream graph processing Journal Article

In: World Wide Web, vol. 25, pp. 971-1003, 2022.


Sebastian Müller; Valentin Gogoll; Anh Duc Vu; Timo Kehrer; Lars Grunske

Automatically finding Metamorphic Relations in Computational Material Science Parsers Inproceedings

In: 2022 IEEE 18th International Conference on e-Science (e-Science), pp. 521-528, 2022.

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