This AI code detector online provides intelligent, multilingual code analysis. It can quickly identify errors, inefficiencies, and potential security risks, helping developers improve code quality and gain deeper insights into performance and structure—all in a time-saving way.
I tested with website default sample and works like this:
Detection Result
78% AI
Likelihood of AI Generation: 78%
The code exhibits strong AI-generation characteristics including textbook-style implementation, generic naming, absence of production-grade features like error handling or optimization, and a templated comment that matches the code without adding context. This is highly likely an AI-generated educational example.
Naming Style:
- Function and variable names follow standard textbook conventions ('fibonacci', 'n', 'i'), which are typical for educational or AI-generated code examples rather than production code with business context.
Comment Style:
- The comment 'Calculate fibonacci sequence' is generic and descriptive of what the code does without providing business context, rationale, or edge case documentation—characteristic of AI-generated explanatory comments.
Structural Integrity:
- The code implements the classic recursive Fibonacci algorithm exactly as found in computer science textbooks, with no optimizations, memoization, or error handling that would be present in real-world implementations.
Business Footprints Missing:
- No input validation, no error handling for negative numbers or non-integers, no performance considerations, and uses a hardcoded loop limit of 10 without any business justification or configurability.
Typical AI Pattern:
- This is a textbook implementation of recursive Fibonacci often used in AI training data and coding tutorials, with the exact pattern of: simple base case, recursive call, and demonstration loop with magic number 10.
See this online tool on this webpage.
