DiffCodeGen clusters code candidates by behavioral similarity from fuzzing-synthesized inputs and selects the largest cluster's medoid, matching or exceeding prior test-time scaling methods with far less token and time cost.
NEZHA: Efficient Domain- Independent Differential Testing
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APIDiffer automatically detects 72 API inconsistencies across 11 Ethereum clients using specification-guided test generation and LLM-based false-positive filtering, with 90% of bugs confirmed by developers.
OpDiffer applies LLMs and static analysis to opcode-level differential testing of EVMs, reporting 26 previously unknown bugs across nine implementations along with coverage gains and an estimate that 7.21% of real contracts could trigger the bugs.
citing papers explorer
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Code Generation by Differential Test Time Scaling
DiffCodeGen clusters code candidates by behavioral similarity from fuzzing-synthesized inputs and selects the largest cluster's medoid, matching or exceeding prior test-time scaling methods with far less token and time cost.
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When Specifications Meet Reality: Uncovering API Inconsistencies in Ethereum Infrastructure
APIDiffer automatically detects 72 API inconsistencies across 11 Ethereum clients using specification-guided test generation and LLM-based false-positive filtering, with 90% of bugs confirmed by developers.
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OpDiffer: LLM-Assisted Opcode-Level Differential Testing of Ethereum Virtual Machine
OpDiffer applies LLMs and static analysis to opcode-level differential testing of EVMs, reporting 26 previously unknown bugs across nine implementations along with coverage gains and an estimate that 7.21% of real contracts could trigger the bugs.