Use explicit error types: Instead of returning null or a magic number, define clear error types. For example, in Rust, the Result<T, E> type forces callers to handle errors. In Python, you can define custom exception classes with meaningful attributes. This makes the code self-documenting and helps static analysis tools catch unhandled errors.

Implement a global error handler: Most frameworks allow you to set a top-level error handler. Use this as a safety net to log unexpected errors, show a user-friendly page, and possibly restart or degrade gracefully. For example, in Flask you can register error handlers for specific HTTP codes, and in Express.js, middleware can catch errors.

Log with context: When logging an error, include enough information to diagnose the issue: timestamp, user ID, request parameters, and stack trace. Consider using structured logging (e.g., JSON format) so that logging systems can parse and search efficiently.

Use circuit breakers and retries: For interactions with external services, implement circuit breaker patterns to avoid cascading failures. If a service is down, fail fast rather than timing out repeatedly. Use retries with exponential backoff for transient errors. Libraries like Polly (for .NET) or resilience4j (for Java) provide this out of the box.

Validate input early: At the boundary of your system (e.g., web request, command line), validate all input. This prevents bad data from entering deeper layers. Use schema validators like JSON Schema or Pydantic.

Test error paths: Write unit tests that simulate errors and verify that your code handles them correctly. Use tools like mock objects to simulate failures from dependencies. Integration tests should also cover error scenarios.

Consider the user: Different error types call for different responses. For a validation error, show the user a clear message indicating what went wrong and how to fix it. For a temporary server error, suggest retrying later. For an irrecoverable error, apologize and provide contact information for support.

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Use explicit error types: Instead of returning null or a magic number, define clear error types. For example, in Rust, the Result<T, E> type forces callers to handle errors. In Python, you can define custom exception classes with meaningful attributes. This makes the code self-documenting and helps static analysis tools catch unhandled errors.

Implement a global error handler: Most frameworks allow you to set a top-level error handler. Use this as a safety net to log unexpected errors, show a user-friendly page, and possibly restart or degrade gracefully. For example, in Flask you can register error handlers for specific HTTP codes, and in Express.js, middleware can catch errors.

Log with context: When logging an error, include enough information to diagnose the issue: timestamp, user ID, request parameters, and stack trace. Consider using structured logging (e.g., JSON format) so that logging systems can parse and search efficiently.

Use circuit breakers and retries: For interactions with external services, implement circuit breaker patterns to avoid cascading failures. If a service is down, fail fast rather than timing out repeatedly. Use retries with exponential backoff for transient errors. Libraries like Polly (for .NET) or resilience4j (for Java) provide this out of the box.

Validate input early: At the boundary of your system (e.g., web request, command line), validate all input. This prevents bad data from entering deeper layers. Use schema validators like JSON Schema or Pydantic.

Test error paths: Write unit tests that simulate errors and verify that your code handles them correctly. Use tools like mock objects to simulate failures from dependencies. Integration tests should also cover error scenarios.

Consider the user: Different error types call for different responses. For a validation error, show the user a clear message indicating what went wrong and how to fix it. For a temporary server error, suggest retrying later. For an irrecoverable error, apologize and provide contact information for support.