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Understanding the behavior of an operations process and capturing it as an abstract process model has been shown to improve dependability significantly [1]. In particular, process context can be used for error detection, diagnosis, and even automated recovery. Creating the process model is an essential step in determining process context and, consequently, improving dependability. This paper describes two systems. The first, POD-Discovery, simplifies the creation of such an abstract process model from operations logs. An activity that previously required many manual steps can now be done largely automatically and in minutes. Using the discovered model, the second system, POD-Viz, provides operators with the ability to visualize the current state of an operations process in near-real-time and to replay a set of events to understand how the process context changed over time. This allows operators to trace the progress of an operations process easily, and helps in analyzing encountered errors.
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Stored only when both papers are in the corpus — 16 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.