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arxiv: 1707.09930 · v1 · pith:WUF4AXM7new · submitted 2017-07-31 · 💻 cs.DB

Debugging Transactions and Tracking their Provenance with Reenactment

classification 💻 cs.DB
keywords transactionsdebuggingtransactionexecutiondatabaseauditavailableconcurrently
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Debugging transactions and understanding their execution are of immense importance for developing OLAP applications, to trace causes of errors in production systems, and to audit the operations of a database. However, debugging transactions is hard for several reasons: 1) after the execution of a transaction, its input is no longer available for debugging, 2) internal states of a transaction are typically not accessible, and 3) the execution of a transaction may be affected by concurrently running transactions. We present a debugger for transactions that enables non-invasive, post-mortem debugging of transactions with provenance tracking and supports what-if scenarios (changes to transaction code or data). Using reenactment, a declarative replay technique we have developed, a transaction is replayed over the state of the DB seen by its original execution including all its interactions with concurrently executed transactions from the history. Importantly, our approach uses the temporal database and audit logging capabilities available in many DBMS and does not require any modifications to the underlying database system nor transactional workload.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Toward Temporal Attribution Analytics in Dataflows

    cs.DB 2026-01 unverdicted novelty 7.0

    Temporal attribution is defined as a new lightweight provenance method using Temporal Interaction Networks to enable time-focused quantitative analysis of dataflows without tuple-level metadata.