FlowLog: Re-thinking Datalog for Fast and Extensible Static Analysis

• URL: http://arxiv.org/abs/2607.23971v1
• Date: Mon, 27 Jul 2026 03:42:34 GMT
• Title: FlowLog: Re-thinking Datalog for Fast and Extensible Static Analysis
• Abstract summary: We demonstrate FlowLog, a Datalog compiler that turns Soufflé-style programs into Differential Dataflow executables for efficient and static analysis.<n>FlowLog consistently outperforms state-of-the-art engines in runtime while remaining memory-efficient and scaling better.
• Score: 2.5899040911480182
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Datalog is widely used to build static analyzers, yet existing engines often force a tradeoff between efficiency and extensibility. In practice, static analyses are not run once and forgotten: users edit facts, tune rules, diagnose bottlenecks, and often need semantics beyond standard Datalog, leaving these tasks to ad hoc tooling or invasive engine rewrites. We demonstrate FlowLog, a Datalog compiler that turns Soufflé-style programs into Differential Dataflow executables for efficient and extensible static analysis. Across 24 benchmarks derived from real-world workloads, FlowLog consistently outperforms state-of-the-art engines in runtime while remaining memory-efficient and scaling better. The demonstration walks attendees through a DOOP points-to analysis. Attendees run it, switching the same program from one-shot to incremental evaluation that retracts a fact and updates results in milliseconds; tune it, inspecting per-operator costs in a browser-based profiler and repairing a bad join order; and extend it with a k-core example that uses semantics beyond Datalog.

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