Abstract
This paper discusses diagnosis of industrial data processing pipelines using action languages. Solving the problem requires reasoning about actions, effects of the actions and mechanisms for accessing outside data sources. To satisfy these requirements, we introduce an action language, Hybrid ALE that combines elements of the action language Hybrid AL[6] and the action language CTAID [8]. We discuss some of the practical aspects of implementing Hybrid ALE and describe an example of its use.
Cite
CITATION STYLE
Bomanson, J., & Brik, A. (2019). Diagnosing Data Pipeline Failures Using Action Languages. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11481 LNAI, pp. 181–194). Springer Verlag. https://doi.org/10.1007/978-3-030-20528-7_14
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