🤖 AI Summary
To address the challenges of immutability post-deployment and the oracle problem in conventional testing of Ethereum crowdfunding smart contracts, this paper proposes a domain-specific metamorphic testing (MT) approach. First, it systematically constructs the first curated set of metamorphic relations (MRs) tailored to crowdfunding contracts, covering core behaviors such as state transitions and donation tracking. Second, it innovatively integrates MT with mutation testing in a deep synergy, implemented atop the Vertigo framework for automated defect detection. Experimental evaluation demonstrates that the method detects 25.65% of injected mutants, with the best-performing MR achieving an 89% mutant-killing rate. This significantly enhances both the capability to identify logical defects in immutable smart contracts and the efficacy of reliability verification.
📝 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.