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Test a trading contract in layers: first verify individual trades and intentional reverts from a known state, then explore input ranges and randomized call sequences, and finally use fork tests when correctness depends on deployed contracts or live chain state. Foundry’s Forge discovers tests by the test prefix; the invariants you assert must come from your own protocol’s specification, not from a generic trading template.
Start with isolated unit tests
Unit tests are the fastest way to check a specific operation against a controlled precondition. Forge discovers Solidity test functions by their test prefix. Use setup to establish the state each case needs, then assert both the call’s outputs and the resulting contract state. Unit and fuzz tests run as single transactions against setup state, so a test should make its starting assumptions clear.
For a trade, assert the behavior the specification promises: for example, the relevant position, balances, fees, or emitted effects after execution. Do not assume that balance conservation or any other accounting rule is universal; the correct checks depend on how the system handles fees, custody, rounding, and external assets.
Cover successful execution and meaningful boundaries
Give each important behavior a descriptive test. In addition to an ordinary successful trade, consider boundaries and rejected states that the implementation actually defines:
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- Unauthorized caller or missing permission
- Zero, excessive, or otherwise out-of-range quantity
- Insufficient balance or collateral
- Stale or invalid price data
- Expired deadline or authorization
- Slippage limit exceeded
- Paused market
- Failure from an external call
These are candidate branches to tailor to the contract, not a checklist every trading system must implement. A test for a branch should establish the conditions that reach that branch and assert the intended outcome.
Test failure paths as deliberate behavior
A revert is not a useful test result merely because the transaction failed. Assert the expected revert data or custom-error selector so a revert from an unrelated line cannot make the test pass. Foundry’s expectRevert helpers support this kind of targeted check; consult the official expectRevert documentation for the behavior supported by your toolchain.
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There is a same-call-depth footgun: expectRevert* normally applies to a call at a greater depth than the test. If the test needs same-depth checking, the documentation says to explicitly enable allow_internal_expect_revert for that test. Make the assertion’s intended semantics clear, and verify the configuration against the project’s Foundry version.
Use fuzz tests for input ranges
Fuzz tests vary inputs to a single test scenario. They are useful for externally controlled values such as trade size, price, fees, deadlines, and account addresses. Bound or otherwise shape inputs when testing valid-call behavior; unconstrained values may exercise only invalid paths and obscure the property you meant to test.
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Use focused fuzz properties: for each generated input, check the output and state rules promised by the contract. Keep explicit boundary tests as well, since they document particular expected branches more clearly than a broad input search.
Use invariants for randomized sequences of actions
Foundry invariant testing differs from fuzzing a single call: it runs randomized sequences of configured calls and checks invariants after each call. This is suited to bugs that depend on the history of trades, deposits, withdrawals, or other actions rather than one isolated input. The Foundry invariant-testing guide documents the mechanism and its configuration.
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Write invariants from the protocol’s own rules
Define invariants from the system’s accounting and safety specification. Possible prompts include whether aggregate positions reconcile with per-user positions, whether token liabilities reconcile with balances under the design’s custody rules, or whether a rejected trade leaves relevant state unchanged. These are examples to adapt, not guarantees that apply to every protocol.
Shape calls with handlers
Invariant campaigns default to fail_on_revert = false, so arbitrary invalid generated calls can revert without failing the campaign. A handler can constrain calls to useful domains, set up actors and assets, and track ghost variables—values that are awkward to derive directly from protocol state. Decide whether reverts are expected in the campaign, then configure the handler and campaign accordingly rather than interpreting a passing run as proof that every generated action succeeded.
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Foundry also documents that each invariant_* function uses a different EVM executor. If several assertions must inspect the same evolving state, group them in one invariant function.
Use fork tests when external code or chain state matters
A fork test brings live chain state into the test environment. Use one when correctness depends on actual external contract code or on chain state, rather than substituting a local mock for the integration in question. Foundry’s fork-testing guide describes testing against live chain state and points to impersonation and time-sensitive logic.
Make the integration assumptions explicit: target chain, deployed addresses, external protocol versions, and relevant state conditions. The appropriate network, RPC provider, and state-selection policy depend on the integration; there is no single choice established for every trading contract. Keep local unit tests as the focused diagnostic layer, and treat fork results as evidence about the particular external deployment and state tested—not as a substitute for all unit coverage.
Choose the test style that answers the question
| Test style | What it examines | Best use | Main trade-off |
|---|---|---|---|
| Unit test | A selected call from controlled setup state | Expected outputs, state changes, and specific branches | Isolated and repeatable, but does not by itself exercise broad input or sequence spaces |
| Fuzz test | One scenario with varied inputs | Input ranges and properties across generated values | Requires useful input domains and clear properties |
| Invariant campaign | Randomized sequences of configured calls, checking properties after each call | Stateful accounting and safety properties | Reverts and call domains need deliberate handler and configuration design |
| Fork test | Integration behavior against external code and chain state | Dependencies on deployed contracts or live state | More realistic for that integration, but dependent on external-state assumptions |
Diagnose failures and preserve regressions
When a test fails, first make the failing call and state transition visible. Forge’s trace options show nested calls and reverts; use the debugger for a focused test; and replay persisted failures rather than relying on memory of a one-off run. The official references are the trace guide, debugger guide, and test-running guide.
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forge test -vvvto obtain traces for failing tests; useforge test -vvvvto trace all tests. - For a focused investigation, run
forge test --debug --match-test "<REGEX>"to open the matching test. A matching fuzz test can open a failing or successful scenario. - Use Foundry’s persisted fuzz or invariant counterexamples and
forge test --rerunto replay failures from the prior run. - Turn a useful counterexample into a regression case, and record any seed, configuration, or fork-state dependency needed to reproduce it.
Commands and configuration can vary with the project toolchain. The official documentation cited here does not pin a Foundry or forge-std version; check behavior against the version and lockfile used by your project.
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