Database configuration tuning has two traditional sources of knowledge: documentation and data. The manual tells you what each setting does. Workload-driven tuning tries thousands of configurations and learns what works. Both are expensive — the manual is incomplete, and the search is slow.
Zhang et al. (arXiv:2603.22708) identified a third source: the source code. Every configuration parameter controls an execution path. The if-statements, thresholds, and branch conditions that use configuration values are written explicitly in the DBMS implementation. The control logic is right there, governing which code path executes for which setting value.
SysInsight uses LLM agents to extract this logic via static analysis: which settings control which execution paths, what value ranges trigger which behaviors, which settings interact through shared code paths. The extracted knowledge is converted into association rules — if setting A is in range X and workload characteristic is Y, then setting B should be Z.
The result: 7.11x faster convergence to optimal configurations compared to state-of-the-art tuners, with 19.9% better final performance. The source code contains more tuning knowledge than the manual that describes it, because the manual abstracts away the control flow that determines actual behavior.
The through-claim: documentation is a lossy summary of implementation. For configuration tuning, the implementation itself — the branching logic, the thresholds, the parameter interactions — is the authoritative source. Reading the code isn't a workaround for missing documentation. It's a higher-fidelity signal than documentation can be.