Programming Issues 101

A comprehensive series on common programming errors and how to prevent them, based on real-world development experience.

Series Overview

Throughout my years of writing code—from building microservices to developing automation tools—I've encountered (and debugged) nearly every type of programming error imaginable. This series distills those experiences into practical guidance for identifying, fixing, and preventing common programming issues.

Why This Series?

Every developer writes buggy code. What separates experienced developers from beginners isn't the absence of errors, but:

• Recognition: Quickly identifying what type of error you're dealing with

• Prevention: Understanding patterns that lead to errors before they happen

• Resolution: Knowing efficient strategies to fix each error type

Series Structure

This series covers 10 common programming error categories with Python examples:

Part 1: Syntax and Compilation Errors

• Syntax Errors

• Compilation Errors (in interpreted languages context)

Part 2: Logic and Semantic Errors

• Logic Errors

• Semantic Errors

Part 3: Runtime and Arithmetic Errors

• Runtime Errors

• Arithmetic Errors

Part 4: Resource and Performance Errors

• Resource Errors

• Time Limit Exceeded Errors

Part 5: Interface and Integration Errors

• Interface Errors

• Linker Errors (dependency management context)

About the Examples

All examples in this series use Python and are based on:

• Personal projects I've built and maintained

• Real debugging sessions from production systems

• Patterns I've observed in code reviews

No hypothetical scenarios—just practical knowledge from actual development work.

Prerequisites

• Basic Python knowledge

• Familiarity with running Python scripts

• Understanding of basic programming concepts

Tools Mentioned

Throughout this series, I reference tools and practices I use:

• IDEs with built-in linters (VS Code, PyCharm)

• Static analysis tools

• Debugging tools

• Testing frameworks

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This series reflects my personal experience in software development. Your mileage may vary, but the patterns are universal.