Related papers: Abductive Vibe Coding (Extended Abstract)
We examine "vibe coding": an emerging programming paradigm where developers primarily write code by interacting with code-generating large language models rather than writing code directly. We present the first empirical study of vibe…
``Vibe coding'' -- the practice of developing software through iteratively conversing with a large language model (LLM) -- has exploded in popularity within the last year. However, developers report key limitations including the…
AI code generation tools are transforming software development, especially for novice and non-software developers, by enabling them to write code and build applications faster and with little to no human intervention. Vibe coding is the…
AI code generation tools have expanded software creation beyond professional developers, giving rise to vibe coding, a practice in which users generate software via natural-language prompts, evaluate outputs primarily by execution. Prior…
Vibe coding, the much-touted use of AI techniques for programming, faces two overwhelming obstacles: the difficulty of specifying goals ("prompt engineering" is a form of requirements engineering, one of the toughest disciplines of software…
Recent advances in large language models have enabled developers to generate software by conversing with artificial intelligence systems rather than writing code directly. This paper introduces vibe coding, an emerging AI-native programming…
Vibe Coding (VC) is a form of software development assisted by generative AI, in which developers describe the intended functionality or logic via natural language prompts, and the AI system generates the corresponding source code. VC can…
This exploratory study examined the consistency of human-AI collaboration by analyzing three extensive "vibe coding" sessions between a human product lead and an AI software engineer. We investigated similarities and differences in team…
Generative AI enables rapid ``vibe coding," where natural language prompts yield working software systems. While this lowers barriers to software creation, it also collapses the boundary between prototypes and engineered software, leading…
Generative AI is reshaping product design practices through "vibe coding," where product team members express intent in natural language and AI translates it into functional prototypes and code. Despite rapid adoption, little research has…
Recent advances in large language models (LLMs) have given rise to vibe coding, a style of software development where developers rely on AI coding assistants to generate, modify, and refactor code using natural language instructions. While…
Agentic AI systems can now generate code with remarkable fluency, but a fundamental question remains: \emph{does the generated code actually do what the user intended?} The gap between informal natural language requirements and precise…
Software development is undergoing a fundamental transformation as vibe coding becomes widespread, with large portions of contemporary codebases now being generated by Artificial Intelligence (AI). The disconnect between rapid adoption and…
Mandating public availability of computer code underlying computational simulation modeling research ends up doing a disservice to the cause of model verification when inconsistencies between the specifications in the publication text and…
When automatically generating programming exercise tasks one often also needs to automatically generate programs. At the very least when providing sample solutions is part of automated feedback. But programs can also be used as part of the…
Code-generating tools are increasingly used in software development, yet experience reports on conversational "vibe coding" under production constraints remain limited. This paper presents an experience report from a small full-stack team…
"Vibe coding" and "vibe analytics" have been framed as a democratization of technical capability. This paper argues that AI-assisted methodology more broadly, or what I call "vibe methodology," also democratizes the failure modes specific…
Intelligent coding systems are transforming software development by enabling users to specify code behavior in natural language. However, the opaque decision-making of AI-driven coders raises trust and usability concerns, particularly for…
Despite significant progress, evaluation of explainable artificial intelligence remains elusive and challenging. In this paper we propose a fine-grained validation framework that is not overly reliant on any one facet of these…
Agentic AI coding systems can inspect repositories, plan implementation steps, edit files, call tools, run tests, and submit pull requests. These capabilities make software and hardware development faster in some settings, but current…