The article examines how the surge of AI coding assistants is boosting short‑term productivity while sharply reducing refactoring efforts, leading to a surge in duplicated code and raising serious long‑term maintenance and technical‑debt concerns for software projects.
The article argues that in early development stages, a small amount of code duplication should be tolerated, warning against premature DRY abstractions that can lead to over‑engineered designs, and advises waiting for genuine common patterns before introducing shared abstractions.
This article introduces four widely‑accepted code‑quality indicators—cyclomatic complexity, function length, file duplication rate, and class fan‑in/fan‑out ratio—explains how to set thresholds, compare error density across codebases, and apply practical management strategies without degrading quality.
The article explains why copy‑pasting code (CV) creates maintenance nightmares, shows how to identify structural and conditional duplication, and provides concrete refactoring steps—extracting methods, using common interfaces, and applying functional techniques—to achieve DRY and improve code readability.
