Automated Program Repair (APR) for smart contract security promises to automatically mitigate smart contract vulnerabilities responsible for billions in financial losses. However, the true effectiveness of this research in addressing smart contract exploits remains uncharted territory. This paper bridges this critical gap by introducing a novel and systematic experimental framework for evaluating exploit mitigation of program repair tools for smart contracts. We qualitatively and quantitatively analyze 20 state-of-the-art APR tools using a dataset of 143 vulnerable smart contracts, for which we manually craft 91 executable exploits. We are the very first to define and measure the essential "exploit mitigation rate", giving researchers and practitioners and real sense of effectiveness of cutting edge techniques. Our findings reveal substantial disparities in the state of the art, with an exploit mitigation rate ranging from a low of 27% to a high of 73%, a result that nobody would guess from reading the original papers. Our study identifies systemic limitations, such as inconsistent functionality preservation, that must be addressed in future research on program repair for smart contracts.
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