Debugging Distributed Data Analysis Workflows (B03)

• Subject Area: Software Engineering and Programming Languages ; Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics ; Security and Dependability, Operating-, Communication- and Distributed Systems
• Term: from 2020 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 414984028

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.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1404: FONDA - Foundations of Workflows for Large-Scale Scientific Data Analysis
• Applicant Institution: Humboldt-Universität zu Berlin
• Project Heads: Professor Dr. Timo Kehrer; Professor Dr. Volker Markl