Blockchain technology is increasingly adopted in scenarios requiring trust and data integrity. On the Ethereum blockchain, the proxy pattern has become increasingly popular because it allows smart contract code to evolve while preserving stored data. However, a key challenge remains ensuring that such upgrades do not introduce breaking changes or cause disruptions to other contracts and off-chain systems. In this article, we introduce Catana , a framework that leverages historical transactions for Capture-Replay testing of proxy-based Upgradeable Smart Contracts (USCs). Catana assesses the potential impact of an upgrade by comparing the outcomes of replayed transactions with those from the previous version deployed on the main network. Additionally, it extracts and decodes contract state variables, providing deeper insights into how code changes affect the contract state, and helping developers mitigate issues before deployment. Experiments demonstrate that analyzing storage data accounts for the majority (about 86.5%) of detected disruptive upgrades. We also evaluate different policies for building replay test suites from historical transactions. Results identify a strategy that maximizes effectiveness while requiring a small number of replay test executions. Even a test suite containing just one transaction per each invoked method achieved good effectiveness (about 60%) in detecting disruptive upgrades.

Smart contracts hold the potential to revolutionize various industries, but their implementation requires thorough testing due to the associated financial risks. Mutation testing is a powerful technique that can boost the fault-detection capabilities of a test suite, but it can also foster a deeper understanding of smart contract behavior. This work investigates the productivity of mutants with respect to their capabilities in disclosing Solidity issues. Based on these findings, it proposes an enhanced mutation strategy to better assist smart contract auditors during code inspection activities. 9 novel mutation operators are introduced in this paper and 13 existing operators are improved. The results show a $30 \%$ reduction in the number of generated mutants and time savings of $62 \%$, while increasing the set of productive mutants related to issues by $43 \%$ overall. We note that the most valuable type of mutants that could help disclose an issue as a result of manual mutant inspection was increased by $125 \%$.

Test flakiness is a topmost concern in software test automation. While conducting pre-deployment testing, those tests that are flagged as flaky are put aside for being either repaired or discarded. We hypothesise that some flaky tests could provide useful insights if run in the field, i.e., they could help identify failures that manifest themselves sporadically during In House testing, but are later experienced in operation. We present the first simulation study to investigate the behaviour of flaky tests when moved to the field. The work compares the behaviour of known flaky tests from an open-source library when executed in the development environment vs. when executed in a simulation of the field. Our experimentation over 52 test methods labelled as flaky provides a first confirmation that moving from the development environment to the field, the behaviour of tests changes. In particular, the failure frequency of intermittently failing tests can increase, and we could also identify few cases of field failures that would have been hardly detected during In House testing due to the numerous combinations of inputs and states. In most cases, such flakiness was rooted in the design of the test method itself, however we could also identify an actual bug. The results of our study suggest that the identification of an intermittently failing behaviour could be a valuable hint for a test engineer, and hence flaky tests should not be dismissed right away.

Smart Contracts are software programs that are deployed and executed within a blockchain infrastructure. Due to their immutable nature, directly resulting from the specific characteristics of the deploying infrastructure, smart contracts must be thoroughly tested before their release. Testing is one of the main activities that can help to improve the reliability of a smart contract, so as to possibly prevent considerable loss of valuable assets. It is therefore important to provide the testers with tools that permit them to assess the activity they performed.Mutation testing is a powerful approach for assessing the fault-detection capability of a test suite. In this paper, we propose SuMo, a novel mutation testing tool for Ethereum Smart Contracts. SuMo implements a set of 44 mutation operators that were designed starting from the latest Solidity documentation, and from well-known mutation testing tools. These allow to simulate a wide variety of faults that can be made by smart contract developers. The set of operators was designed to limit the generation of stillborn mutants, which slow down the mutation testing process and limit the usability of the tool. We report a first evaluation of SuMo on open-source projects for which test suites were available. The results we got are encouraging, and they suggest that SuMo can effectively help developers to deliver more reliable smart contracts.