Methods for Smart Contract Testing

Automated and manual testing approaches for Ethereum smart contracts can be coupled to develop a strong framework for contract analysis.

1. Automated Testing

Automated testing is a technology that automatically checks a smart contract’s code for execution issues. It is more efficient than manual testing methods due to scripts (i.e. writing different test cases) being used to evaluate contract features. Automated testing is particularly useful when tests are repetitive and time-consuming; difficult to carry out manually; susceptible to human error; or involve evaluating critical contract functions. However, automated testing can have downsides such as missing specific vulnerabilities and producing false positives, so it is important to combine automated and human testing for smart contracts.

2. Unit Testing

Unit testing examines contract functions independently and ensures that each component performs properly. If unit tests fail, they should be simple, quick to execute, and offer a clear indication of what went wrong. They may be used to ensure that functions return anticipated values, and that contract storage is appropriately updated after function execution. Running unit tests after making modifications to a contract’s codebase also guarantees that no errors are introduced.

Guidelines for unit testing smart contracts:

• Understand your contracts’ business logic and workflow: Understanding a smart contract’s functionalities, user interactions, and operational workflow is crucial before writing unit tests. This knowledge enables the creation of effective tests, including happy path tests, to verify correct outputs for valid inputs. Additionally, it helps ensure that unit tests assess the contract’s execution against the defined requirements.
• Evaluate all assumptions related to contract execution: Documenting assumptions, writing unit tests, and using assertions are essential for ensuring the reliability and security of smart contracts. Unit testing helps validate assumptions, protects against unexpected execution, and encourages consideration of potential security vulnerabilities. It is advised to go beyond positive tests and includes negative tests to check for failure with incorrect inputs. Unit testing frameworks provide the means to create and validate assertions, enabling thorough testing of smart contract capabilities and limitations.
• Measure code coverage: Code coverage is a metric used in testing to measure the extent to which branches, lines, and statements of code are executed during test scenarios. It is crucial to aim for good code coverage to avoid “false negatives” where a contract passes all tests but still contains vulnerabilities. Achieving high code coverage provides confidence that all statements and functions in a smart contract have been adequately tested for accuracy and correctness.
• Use well-developed testing frameworks: The choice of unit testing tools plays a vital role in ensuring the quality of your smart contract testing. An optimal testing framework is characterized by regular maintenance, valuable features such as logging and reporting capabilities, and a track record of extensive usage and auditing by fellow developers.
  Unit testing frameworks for Solidity smart contracts are available in various languages, with JavaScript, Python, and Rust being prominent examples. Some well-known unit testing frameworks for smart contracts include Truffle, Hardhat, and Ape, among others.

3. Integration Testing

While unit testing debugs contract operations in isolation, integration testing evaluates a smart contract’s components as a whole. Integration testing can identify problems caused by cross-contract calls or interactions between various functions inside the same smart contract. Integration tests, for example, can aid in determining if inheritance and dependency injection are functioning effectively.

• If your contract has a modular design or interacts with other on-chain contracts during execution, integration testing is beneficial. To perform integration tests, fork the blockchain at a certain level (using a tool like Ganache or Hardhat) and simulate interactions between your contract and deployed contracts.
• The split blockchain will function similarly to Mainnet, with accounts that have related statuses and balances. But it only acts as a sandboxed local development environment, meaning you won’t need real ETH for transactions, for example, nor will your changes affect the real Ethereum protocol.

4. Manual Testing

When it comes to smart contract testing, manual testing typically takes place in the later stages of the development cycle, following automated tests. This form of testing examines the smart contract as a fully integrated product, ensuring that it performs according to the specified technical requirements.

• To assess how your smart contract behaves in a production environment, testing it on a local blockchain is a recommended approach. While automated testing in a local development environment can provide useful debugging insights, deploying on the main Ethereum chain can be costly in terms of gas fees and potential financial risks.
• Utilizing a local blockchain, such as Ganache, Local Beacon Chains, or Hardhat, allows for interaction with the contract without significant overhead. Running contracts on a local blockchain is particularly beneficial for manual integration testing. Smart contracts offer composability, enabling integration with existing protocols. However, it is crucial to verify that these complex on-chain interactions yield accurate outcomes.
• Another method of manual testing is deploying the contract on testnets. Testnets function similarly to the Ethereum Mainnet but utilize Ether with no real-world value. Deploying on a testnet enables users, including beta testers, to interact with the contract without risking actual funds. This form of testing evaluates the end-to-end flow of the application from a user’s perspective and allows testers to identify any issues related to the contract’s business logic and overall functionality.
  • After conducting tests on a local blockchain, deploying on a testnet is advantageous as it closely mimics the behaviour` of the Ethereum Virtual Machine. Many Ethereum-native projects choose to deploy dapps on testnets to evaluate the operation of smart contracts under real-world conditions. Some Examples of testnet are Goerli, Sepolia, etc.

Public Blockchains like Ethereum are immutable, it is difficult to update the code of a smart contract once it has been deployed. To guarantee security, smart contracts must be tested before they are deployed to Mainnet. There are several strategies for testing contracts, but a test suite comprised of various tools and approaches is suitable for detecting both minor and significant security issues in contract code.