Does AI-Assisted Development Homogenize Software? An Empirical Study of Code Similarity, Quality, and Evolution
AI-assisted software development is evolving from interactive LLM assistance toward agentic systems that autonomously perform software engineering tasks, yet the effects of this shift remain insufficiently understood. We present an empirical study of 50 long-lived Java and Python open-source projects across three eras: pre-LLM, potentially LLM-assisted, and detected agentic development. Using snapshots from Software Heritage, we examine code similarity, software quality, and software evolution. Similarity is measured semantically through embedding-based cosine similarity and syntactically through CodeBLEU*. Quality is assessed with SonarQube metrics covering maintainability, complexity, r...
| Authors | Luciano Marchezan, Romain Lefeuvre, Kevin Delcourt et al. |
|---|---|
| Primary category | cs.SE |
| Published | 16 October 2026 |
| Last updated at source | 16 October 2026 |
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