pith:QF4TRV3L
Uncovering Business Logic Bugs via Semantics-Driven Unit Test Generation
SeGa builds semantic knowledge bases from requirement documents to guide unit test generation toward business logic bugs.
arxiv:2604.23509 v2 · 2026-04-26 · cs.SE
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Claims
SeGa detects 22-25 more bugs than four state-of-the-art LLM-based techniques and improves precision by 26.9%-34.3%. Deployment across 6 production repositories further uncovers 16 previously unknown business logic bugs that were confirmed and fixed by developers.
The technique assumes that product requirement documents provide complete and accurate representations of intended business semantics that can be reliably grouped into functionality entries and translated into effective test scenarios without significant loss or misinterpretation.
SeGa extracts business semantics from requirements to generate unit tests that detect 22-25 more real-world business logic bugs than prior LLM-based methods in industrial Go projects.
Receipt and verification
| First computed | 2026-08-04T02:00:15.944608Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QF4TRV3L3SYOXTW4XOBEMYDCJJ \
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# expect: 817938d76bdcb0ebcedcbb824660624a6548ebe699ada1214416cee14c6ccc3d
Canonical record JSON
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