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At 2 AM, start by writing down what should have happened and what actually happened. Then try to reproduce the failure. Choose the tool that reveals the missing evidence: diagnostics for problems detectable before runtime, a debugger for live program state and control flow, logs or tracepoints for a record you can inspect later, and a profiler for measured performance problems.
Start with the discrepancy, not a tool
Describe the failure in one or two sentences: what did you expect, and what did the program do instead? Capture the exact error, input, environment, and recent change if you have them. This separates the observable symptom from your first guess about its cause. Microsoft’s beginner debugging guide recommends clarifying expected and actual behavior before investigating.
Next, try to reproduce the problem. Record the smallest sequence of actions and inputs that triggers it, along with any conditions that matter. For browser JavaScript, Microsoft Edge’s debugging guide likewise starts with finding a sequence of actions that consistently reproduces the bug. A repeatable failure gives you a reliable way to compare what changes as you investigate.
Choose the method that answers the unknown
| What you see or don’t know | First method to try | What it can show |
|---|---|---|
| A compile-time error or clear IDE warning | Compiler, IDE diagnostics, or analyzer results | Syntax, type, and other issues the tools can detect before execution. Microsoft describes analyzers and code inspection as part of debugging: What is debugging and a debugger? |
| A wrong value or unexpected branch in a reproducible run | Breakpoint, stepping, variable inspection, and call stack | Where runtime state or control flow stops matching your expectation. See Microsoft’s breakpoint guidance. |
| An intermittent failure, remote process, or situation where pausing is impractical | Structured logs, tracepoints, exception details, or captured traces | A record of events that can be reviewed without relying on an interactive pause. Visual Studio tracepoints can write to the Output window without stopping execution or changing source code; see Use the right type of breakpoint. |
| Browser behavior involving scripts, requests, rendering, or timing | Reproduce in browser developer tools; inspect code, console output, network requests, and relevant performance views | Evidence that helps distinguish script execution from request, rendering, or timing issues. See Chrome’s JavaScript debugging guide and Microsoft Edge’s JavaScript debugging guide. |
| Slow execution or unusually high memory use | Profiler or memory-analysis tool | Which measured operation or resource use merits investigation. Microsoft lists performance profilers among the tools that support debugging: Debugging techniques and tools. |
| Uncertainty about intended behavior or a previously fixed defect | Focused test or assertion | Whether the expected behavior is explicit and whether a correction preserves it. A test can express intent that a tool cannot infer on its own; see Microsoft’s beginner debugging guide. |
These methods work together. A log can narrow the time window, a debugger can expose the state inside it, and a test can preserve the corrected behavior.
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When a debugger is the right first move
Attach a debugger when the key question is what the program is doing at runtime: which branch it takes, what a variable contains, or how execution reached a line. Set a breakpoint near where you suspect behavior diverges, then step through the relevant code and inspect the values and call stack. Microsoft’s overview of debugging distinguishes the broad work of finding and diagnosing defects from an attached debugger, which enables runtime inspection.
Use a conditional breakpoint when you need to stop only for a particular value or condition. If stopping the program would interfere with the behavior, a tracepoint may be a better observation: Visual Studio can emit information to the Output window without pausing execution or modifying source code. Available breakpoint types depend on the debugger and development environment.
When to prefer logs, diagnostics, or a profiler
Logs and tracepoints for evidence over time
Prefer logs or tracepoints when you need a persistent account of events, especially for an intermittent failure or a process you cannot conveniently pause. Include the context that will distinguish one occurrence from another, such as a relevant input, operation, or error detail. Avoid recording sensitive values unless your logging policy permits it.
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Diagnostics for issues detectable before runtime
When a compiler or IDE already points to a syntax, type, or analyzer warning, inspect that evidence before launching a runtime investigation. These tools are useful for defects they can detect, but they do not reveal every behavior that depends on live inputs or execution.
Profilers for measured performance symptoms
When the reported problem is slowness or resource use, profile a representative run instead of guessing which code is expensive. Use the measurements to identify an area for investigation, then verify any change under the same relevant workload. A profiler identifies measured costs; it does not by itself establish that a particular change is the correct fix.
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Test the suspected cause and preserve the fix
- Locate the divergence. Use the selected observation method to find where actual state or behavior first differs from the expected result.
- Form a cause you can check. State what you think is wrong and what observation would support or disprove that explanation.
- Make a focused correction. Change the likely cause rather than adding a workaround that merely hides the symptom.
- Repeat the reproduction. Run the same steps or input that exposed the problem and confirm the expected result.
- Keep a regression check. Add a focused test or assertion when practical, or preserve a minimal reproducer, useful log, or concise root-cause note.
Tests and assertions make expected behavior explicit; tools cannot reliably infer what the program was meant to do unless that intent is expressed. Microsoft’s beginner guide discusses tests as part of a debugging workflow.
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For Python, pdb is part of the standard library. It supports breakpoints, stepping, stack-frame inspection, and post-mortem debugging. The exact way you start it depends on how you run the program; consult the official pdb documentation for current invocation options and commands. Python also documents traceback-dump facilities in its debugging and profiling reference. These examples are specific to Python; other languages and environments have their own tools.
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