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Start with the shared state and the invariant
In Go, the official documentation defines a data race as: “A data race occurs when two goroutines access the same variable concurrently and at least one of the accesses is a write.” (The Go Programming Language documentation, “Data Race Detector”.) That definition is specific to Go’s goroutines; other languages have their own concurrency models and tools.
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Before comparing fixes, identify the exact variable or object that can be accessed concurrently. Then state what must remain true after the competing operations finish. For example, if multiple goroutines try to initialize a shared value, the invariant might be that only one initialization wins and every caller sees the same published value. A patch that removes a reported race but allows duplicate initialization may still be incorrect.
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- Invariant: What must hold across every possible ordering of those operations?
- Required behavior: What should each caller observe, including when another operation happens at the same time?
Check whether the whole operation is atomic
A common source of misleading fixes is treating a sequence of individually safe operations as though the sequence were indivisible. Consider this Go example:
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if _, ok := values.Load(key); !ok {
values.Store(key, value)
}With concurrent callers, both can observe that the key is absent before either stores a value. The individual Load and Store operations do not make the combined check-and-store atomic. Go’s concurrency review guidance points to LoadOrStore for this pattern; consult its sync.Map example in context. The important review question is not just whether each method is safe to call concurrently, but whether the full multi-step operation preserves the invariant.
For other code, look for the same shape: check then update, read then act, or update several related fields. A mutex or a channel can establish synchronization in Go, but only if it covers the relevant accesses and the program uses it consistently. See the Go race-detector documentation for typical synchronization approaches.
Distinguish synchronization from a timing change
A delay, retry, reordered statement, or extra work may make an intermittent failure harder to reproduce. That does not by itself establish that the shared access is safe. A synchronization fix changes what concurrent executions are allowed to do: for example, it orders conflicting access or makes a compound operation atomic.
For each proposed change, ask what it guarantees rather than what it appears to improve:
- Does it protect every conflicting read and write, or only one access?
- Does it make a check-and-update sequence indivisible when the invariant requires that?
- Does it preserve the intended result under either ordering of the competing operations?
- Does it affect unrelated behavior, such as allowing duplicate work or changing which value wins?
Use the race detector as evidence, not a proof
Go’s race detector finds races that occur while the instrumented program runs. A clean run therefore says only that the executed workload did not reveal a race; it cannot rule out a race on an unexecuted path or interleaving. The Go documentation describes the detector, and the ThreadSanitizer Go manual likewise explains the limits of dynamic detection and test coverage.
Tests are most useful when they exercise the actual competing operations, not just each operation in isolation. Run relevant concurrent workloads under the detector where available, and investigate any report by tracing the accesses it identifies. A detector report is evidence of a race on that execution; no report is not evidence that every possible execution is safe.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A practical way to compare two candidate fixes
- Mark the shared state. List every read and write that can occur concurrently, including accesses reached through helper functions.
- Write down the invariant. Make the required outcome precise enough to test, such as “exactly one value is installed” or “these fields always describe the same version.”
- Trace each patch. Identify which accesses it orders or protects, and whether it covers the entire operation needed to maintain the invariant.
- Consider competing schedules. Walk through what happens if each goroutine pauses after every relevant read or write. Check whether the bad outcome remains possible.
- Exercise the path concurrently. Add or run tests that invoke the competing operations together, then use the language’s race-detection tooling where available.
- Check behavior beyond the detector. Verify that the patch also preserves the intended result; a race-free program can still violate its logical invariant.
This method can show why a particular patch is or is not a fix. Without the two code changes and the behavior they are intended to preserve, no reliable verdict about which one is “real” follows from the title alone.
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