# Code smells

arXiv: https://arxiv.org/abs/1802.06063 · HTML: https://mlsanity.com/paper/1802.06063/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Feb 2018.

## Built on by (most cited first, 1 of 1)

- [Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3](https://mlsanity.com/paper/2504.16027/) (2025)

## Abstract (arXiv)

Code smells as symptoms of poor design and implementation choices. Many times they are the result of so called technical debt. Our study showed that the interest in code smells research is increasing. However, most of the publications are appearing in conference proceedings. Most of the research is done in G7 and other highly developed countries. Four main research themes were identified namely code smell detection, bad smell based refactoring, software development and anti patterns. The results show that code smells can also have a positive connotation, we can develop software which smells good and attracts various customers and good smelling code could also serve as a pattern for future software development.