Aug 2026· INFORMACIONNYE TEHNOLOGII· 0 citations· 4 references
Abstract
This systematic review presents an analysis of the "Vibe Coding" methodology — a contemporary approach to the iterative software development process using Large Language Models (LLMs). Code generation tools are transforming software development by enabling programmers to formulate tasks and describe the desired behavior of software in natural language, while LLMs generate source code corresponding to these requests. The review systematizes current methodologies for the use of LLMs, highlights application examples, evaluates the effectiveness of generated code, discusses emerging challenges, and outlines future development trends of the technology. The aim of this work is to provide a comprehensive understanding of the capabilities and limitations of Vibe Coding as a transformational methodology in software engineering.
This study compares the structural quality of code produced by three widely adopted vibe coding tools --- Lovable, v0, and Replit --- starting from a single generation prompt and suggests that choosing between vibe coding tools involves structural trade-offs that go beyond perceived productivity.
It is observed that generated code often omits basic input validation or memory-safety checks, which can lead to overflows, resource exhaustion, or other reliability/security issues, and even the largest models frequently make simple mistakes.
Rodrigo Pato Nogueira, Marco Vieira, João R. Campos· 0 citations
This Systematic Literature Review examines prompt engineering in automatic code generation using large language models (LLMs) and shows that prompt engineering has been established as a key discipline for optimizing interaction with LLMs and improve the accuracy, robustness, and applicability of the generated code.
E. Camacho, Y. Gutierrez, César Pardo· 0 citations
Fundamental concepts of generative artificial intelligence, the importance of prompt engineering, prompting techniques and strategies for improving the quality of responses generated by large language models, and the potential applications of these tools in programming education are presented.
Branislava Radu, Ljubica Kazi· 16th International Symposium...· 0 citations
The proposed approach considers code review not merely as a process of generating comments, but as a context-aware multi-stage process that includes code change assessment, risk identification, problem localization, and generation of explainable recommendations.
T. Todua, Giorgi Tsitlidze· Computational and Applied Sc...· 0 citations
Recently, Developers have been relying on AI tools to support them in their daily work by generating code. While the use of large language model-based AI tools has improved productivity, the quality of the generated code wasn't always optimal. In a lot of cases, the code includes design issues known as code smells, whi...
Y. Younes, Yousef Elsheikh· IEEE Jordan Conference on Ap...· 0 citations
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