12 papers · ranked by Valyu relevance
Man-Fai Wong, Shangxin Guo, Ching-Nam Hang, Siu-Wai Ho + 2 more
'Chee-Wei Tan' 'Lei Wang'] This paper provides a comprehensive review of the literature concerning the utilization of Natural Language Processing (NLP) techniques, with a particular focus on transformer-based large language models (LLMs) trained using Big Code, within the domain of AI-assisted programming tasks. LLMs…
Kehao Mao, Baokun Hu, Ruixin Lin, Zewen Li + 2 more
Automated programming has become a powerful tool for solving real-world problems. Code generation, in particular, plays a key role in improving developer productivity and reducing the entry barrier to software development. Recent advances in large language models (LLMs) have significantly improved program synthesis…
Ekaterina Trofimova, Emil Sataev, Andrey Ustyuzhanin, Xiangjie Kong
In the ever-evolving landscape of machine learning, seamless translation of natural language descriptions into executable code remains a formidable challenge. This article introduces Linguacodus, an innovative framework designed to tackle this challenge by deploying a dynamic pipeline that iteratively transforms…
Claudia Negri-Ribalta, Rémi Geraud-Stewart, Anastasia Sergeeva, Gabriele Lenzini
Introduction Artificial Intelligence (AI) is increasingly used as a helper to develop computing programs. While it can boost software development and improve coding proficiency, this practice offers no guarantee of security. On the contrary, recent research shows that some AI models produce software with…
Bo Cai, Jian Luo, Zhen Feng
Graphical user interfaces (GUIs) are widely used in human-computer interaction, providing a convenient interface for operation. Automating the conversion of GUI design images into source code can significantly reduce the coding workload for front-end developers. Detecting elements in GUI images is a key challenge in…
Pavel Kodytek, Alexandra Bodzas, Jan Zidek, Govind Vashishtha
Continual technological advances associated with the recent automation revolution have tremendously increased the impact of computer technology in the industry. Software development and testing are time-consuming processes, and the current market faces a lack of specialized experts. Introducing automation to this field…
Zi Wang, Xiaoyu Zhu, Hongqiang Wang, Yichun Yu + 2 more
Formal verification ensures software correctness but faces challenges in kernel specification writing, which is labor-intensive, expertise-dependent, and limited to specific targets. For complex microkernels like seL4, these issues significantly reduce the practicality of formal methods. To address this, we propose…
Cristian Robledo, Francesca Sallicati, Gaël de Chalendar, Marcos Fernández + 4 more
'Marcos Fernández' 'Pablo de Castro' 'Eduardo Martín' 'Javier Gutiérrez' 'Yannis Bouachera'] This paper aims to introduce the innovative work carried out in the Horizon 2020 DECODER project - acronym for “DEveloper COmpanion for Documented and annotatEd code Reference” - (Grant Agreement no. 824231) by linking the…
Mohammadreza Nehzati
AI-powered code generation systems available today are ill-suited for deployment in agile software development contexts due to various limitations. The paper proposes a self-healing counterpart framework based on quantum-inspired optimization, biomimetic, and fractal principles to solve these fundamental issues. Our…
Jianhui Zeng, Zhiheng Qu, Bo Cai, Boris Ryabko
Source code summarization focuses on generating qualified natural language descriptions of a code snippet (e.g., functionality, usage and version). In an actual development environment, descriptions of the code are missing or not consistent with the code due to human factors, which makes it difficult for developers to…
Ran He, Jie Cao, Tieniu Tan
Generative artificial intelligence (GAI) has recently achieved significant success, enabling anyone to create texts, images, videos and even computer codes while providing insights that might not be possible with traditional tools. To stimulate future research, this work provides a brief summary of the ongoing and…
Nico Willert, Jonathan Thiemann
Manual composition of tasks and exams is a challenging and time-consuming task. Especially when exams are taken remotely without the personal monitoring by examiners, most exams can easily lose their integrity with the use of previously done exercises or student communication. This research introduces an approach that…