Ethereum reentry defect detection tool evaluation method based on variation test

The invention relates to an Ethereum reentry defect detection tool evaluation method based on a variation test. The method comprises the following steps: firstly, identifying a potential re-entry path in the smart contract by utilizing symbolic execution so as to determine a re-entry defect type which can be generated by variation of the smart contract; secondly, all statements to be mutated in the path are positioned through pattern matching, so that the effectiveness of defect variation generation can be improved; on the basis, a re-entry mutation operator is used for the statement to be mutated, and a re-entry defect variant set is generated; and finally, the reentry defect variant set is detected by using a reentry defect detection tool, a variation score is calculated according to a detection result, and the higher the variation score is, the stronger the defect detection capability of the tool is. According to the method, a large-scale and classification-balanced reentry defect data set can be generated