Metamorphic Testing for Smart Contract Validation:A Case Study of Ethereum-Based Crowdfunding Contracts

• URL: http://arxiv.org/abs/2501.09955v1
• Date: Fri, 17 Jan 2025 05:04:23 GMT
• Title: Metamorphic Testing for Smart Contract Validation:A Case Study of Ethereum-Based Crowdfunding Contracts
• Authors: Irving Jared Villanueva, Madhusudan Srinivasan, Faqeer Ur Rehman,
• Abstract summary: A key challenge in the testing of smart contracts is the oracle problem, where the exact expected outcomes are not well defined. We use Metamorphic Relations (MRs) to validate smart contracts. MRs define how output should change relative to specific input, determining whether the tests pass or fail. Our results show that our MRs detected 25.65% of the total mutants generated, with the most effective MRs achieving a mutant-killing rate of 89%.
• Score: 0.11470070927586014
• License:
• Abstract: Blockchain smart contracts play a crucial role in automating and securing agreements in diverse domains such as finance, healthcare, and supply chains. Despite their critical applications, testing these contracts often receives less attention than their development, leaving significant risks due to the immutability of smart contracts post-deployment. A key challenge in the testing of smart contracts is the oracle problem, where the exact expected outcomes are not well defined, complicating systematic testing efforts. Metamorphic Testing (MT) addresses the oracle problem by using Metamorphic Relations (MRs) to validate smart contracts. MRs define how output should change relative to specific input modifications, determining whether the tests pass or fail. In this work, we apply MT to test an Ethereum-based crowdfunding smart contract, focusing on core functionalities such as state transitions and donation tracking. We identify a set of MRs tailored for smart contract testing and generate test cases for these MRs. To assess the effectiveness of this approach, we use the Vertigo mutation testing tool to create faulty versions of the smart contract. The experimental results show that our MRs detected 25.65% of the total mutants generated, with the most effective MRs achieving a mutant-killing rate of 89%. These results highlight the utility of MT to ensure the reliability and quality of blockchain-based smart contracts.

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