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Large language models (LLMs) have achieved record adoption in a short period of time across many different sectors including high importance areas such as education [4] and healthcare [23]. LLMs are open-ended models trained on diverse data…

密码学与安全 · 计算机科学 2024-12-24 Herve Debar , Sven Dietrich , Pavel Laskov , Emil C. Lupu , Eirini Ntoutsi

This study investigates the reliability of code generation by Large Language Models (LLMs), focusing on identifying and analyzing defects in the generated code. Despite the advanced capabilities of LLMs in automating code generation,…

软件工程 · 计算机科学 2024-08-27 Ali Mohammadi Esfahani , Nafiseh Kahani , Samuel A. Ajila

[Background/Context] AI assistants like GitHub Copilot are transforming software engineering; several studies have highlighted productivity improvements. However, their impact on code quality, particularly in terms of maintainability,…

软件工程 · 计算机科学 2024-08-21 Markus Borg , Dave Hewett , Donald Graham , Noric Couderc , Emma Söderberg , Luke Church , Dave Farley

Artificial Intelligence Generated Content (AIGC) has garnered considerable attention for its impressive performance, with ChatGPT emerging as a leading AIGC model that produces high-quality responses across various applications, including…

软件工程 · 计算机科学 2023-04-12 Jian Wang , Shangqing Liu , Xiaofei Xie , Yi Li

AI coding assistants are now widely used in software development. Software developers increasingly integrate AI-generated code into their codebases to improve productivity. Prior studies have shown that AI-generated code may contain code…

软件工程 · 计算机科学 2026-04-28 Yue Liu , Ratnadira Widyasari , Yanjie Zhao , Ivana Clairine Irsan , Junkai Chen , David Lo

Large Language Models (LLMs) and generative AI (GenAI) systems, such as ChatGPT, Claude, Gemini, LLaMA, and Copilot (by OpenAI, Anthropic, Google, Meta, and Microsoft, respectively), are reshaping digital platforms and app ecosystems while…

密码学与安全 · 计算机科学 2025-07-29 Kiarash Ahi

With the rise of AI-powered coding assistants, firms and programmers are exploring how to optimize their interaction with them. Research has so far mainly focused on evaluating output quality and productivity gains, leaving aside the…

人机交互 · 计算机科学 2025-12-24 Charlotte Brandebusemeyer , Tobias Schimmer , Bert Arnrich

Large language models (LLMs) have undergone rapid evolution and achieved remarkable results in recent times. OpenAI's ChatGPT, backed by GPT-3.5 or GPT-4, has gained instant popularity due to its strong capability across a wide range of…

密码学与安全 · 计算机科学 2023-12-12 Fangzhou Wu , Qingzhao Zhang , Ati Priya Bajaj , Tiffany Bao , Ning Zhang , Ruoyu "Fish" Wang , Chaowei Xiao

LLM-based coding agents are rapidly being deployed in software development, yet their safety implications remain poorly understood. These agents, while capable of accelerating software development, may exhibit unsafe behaviors during normal…

人工智能 · 计算机科学 2025-08-26 Matous Kozak , Roshanak Zilouchian Moghaddam , Siva Sivaraman

The code generation capabilities of large language models(LLMs) have emerged as a critical dimension in evaluating their overall performance. However, prior research has largely overlooked the security risks inherent in the generated code.…

密码学与安全 · 计算机科学 2025-06-23 Xinghang Li , Jingzhe Ding , Chao Peng , Bing Zhao , Xiang Gao , Hongwan Gao , Xinchen Gu

GitHub's Copilot for Pull Requests (PRs) is a promising service aiming to automate various developer tasks related to PRs, such as generating summaries of changes or providing complete walkthroughs with links to the relevant code. As this…

软件工程 · 计算机科学 2024-02-15 Tao Xiao , Hideaki Hata , Christoph Treude , Kenichi Matsumoto

Existing benchmarks for evaluating the security risks and capabilities (e.g., vulnerability detection) of code-generating large language models (LLMs) face several key limitations: (1) limited coverage of risk and capabilities; (2) reliance…

密码学与安全 · 计算机科学 2025-09-22 Yuzhou Nie , Zhun Wang , Yu Yang , Ruizhe Jiang , Yuheng Tang , Xander Davies , Yarin Gal , Bo Li , Wenbo Guo , Dawn Song

Programming students have a widespread access to powerful Generative AI tools like ChatGPT. While this can help understand the learning material and assist with exercises, educators are voicing more and more concerns about an overreliance…

人机交互 · 计算机科学 2025-02-24 Christian Rahe , Walid Maalej

The increasing adoption of large language models (LLMs) in software engineering necessitates rigorous security evaluation of their generated code. However, existing benchmarks often lack relevance to real-world AI-assisted programming…

This study presents a quantitative evaluation of the code quality and security of five prominent Large Language Models (LLMs): Claude Sonnet 4, Claude 3.7 Sonnet, GPT-4o, Llama 3.2 90B, and OpenCoder 8B. While prior research has assessed…

软件工程 · 计算机科学 2025-08-21 Abbas Sabra , Olivier Schmitt , Joseph Tyler

Large Language Models (LLMs) can generate code but often introduce security vulnerabilities, logical inconsistencies, and compilation errors. Prior work demonstrates that LLMs benefit substantially from structured feedback, static analysis,…

密码学与安全 · 计算机科学 2026-01-05 Vidyut Sriram , Sawan Pandita , Achintya Lakshmanan , Aneesh Shamraj , Suman Saha

Model-sharing platforms, such as Hugging Face, ModelScope, and OpenCSG, have become central to modern machine learning development, enabling developers to share, load, and fine-tune pre-trained models with minimal effort. However, the…

Code generation stands as a powerful technique in modern software development, improving development efficiency, reducing errors, and fostering standardization and consistency. Recently, ChatGPT has exhibited immense potential in automatic…

软件工程 · 计算机科学 2023-12-22 Youjia Li , Jianjun Shi , Zheng Zhang

Large Language Models (LLMs) are reshaping knowledge work, yet their impact on voluntary, self-guided open innovation forums (contributors choose tasks without managerial direction) may differ fundamentally from effects observed in…

软件工程 · 计算机科学 2026-05-26 Doron Yeverechyahu , Raveesh Mayya , Gal Oestreicher-Singer

Code generation has largely improved development efficiency in the era of large language models (LLMs). With the ability to follow instructions, current LLMs can be prompted to generate code solutions given detailed descriptions in natural…

软件工程 · 计算机科学 2025-02-06 Yun Peng , Jun Wan , Yichen Li , Xiaoxue Ren
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