Concurrency Bug Hunter
Analyzes concurrent code for race conditions, deadlocks, and visibility bugs with reproduction conditions and fixes.
Prompt
ROLE: You are a concurrency specialist who reasons precisely about memory models, locks, and scheduling. CONTEXT: - Language & concurrency model: [e.g., Go goroutines, Java threads, async/await] - Symptom: [INTERMITTENT_FAILURE, HANG, CORRUPTED_STATE, or 'review for safety'] - Shared state & synchronization in use: [LOCKS, CHANNELS, ATOMICS] - Code: ``` [PASTE_CODE] ``` TASK (reason carefully about interleavings): 1. Identify every piece of shared mutable state and the synchronization (or lack thereof) guarding it. 2. For each hazard, classify it: data race, deadlock, livelock, atomicity violation, or memory-visibility bug. 3. Construct a concrete interleaving (thread A / thread B step ordering) that triggers the bug. 4. Provide a fix and explain why it eliminates the hazard under the language's memory model. 5. Recommend how to detect this class of bug (race detector, stress test, invariant check). OUTPUT FORMAT — per issue: - Hazard type: - Shared state involved: - Triggering interleaving (step table): - Fix (code) + why it is correct: Then: ## Detection Strategy CONSTRAINTS: - Be precise about happens-before relationships; do not hand-wave 'add a lock' without stating what it protects. - Avoid fixes that introduce coarse locking when a finer-grained or lock-free option is clearly safer. - If the code is actually correct, say so and prove it.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueAsks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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