Enhancing Smart Contract Reliability: Dynamic Approaches for Quality Assurance

Blockchain technologies had a significant impact on many sectors of contemporary society, with virtual currencies being the most prominent example. The introduction of the Ethereum blockchain and its native support for smart contracts, self-enforcing programs that enable trustworthy digital interactions, has broadened the possible adoption contexts. These programs possess unique characteristics, such as code immutability and autonomous execution, which necessitate innovative testing methodologies. Despite their growing adoption, current testing practices and tools for smart contracts lag behind those available for traditional software systems, raising concerns about the reliability of decentralized applications. This dissertation addresses these challenges through three core research objectives. First, it advances mutation testing for Ethereum smart contracts by introducing a practical framework and tool that support Solidity-specific test adequacy assessment and incremental mutation analysis during development. This enables developers to systematically evaluate and improve the fault-detection capabilities of their test suites based on metrics that go beyond simple code coverage. Second, it explores how smart contract auditing practices can benefit from mutation testing by integrating live mutant inspection into code reviews and automating the generation of missing test cases. This contribution enhances the auditors’ ability to identify weaknesses in the test suite and provide actionable feedback to clients. Third, it supports smart contract maintenance activities by proposing a novel capture-replay testing framework and tool for upgradeable contracts. The approach harnesses historical blockchain transactions as tests, allowing developers to detect behavioral inconsistencies introduced by upgrades without the need to manually reconstruct testing scenarios. Through these contributions, the thesis aims to advance the state of smart contract quality assurance, offering both practical frameworks and theoretical insights that enhance the reliability of blockchain-based systems.