相关论文: Bugdar: AI-Augmented Secure Code Review for GitHub…

The automated program repair field has attracted substantial interest over the years, but despite significant research efforts, creating a system that works well for complex semantic bugs such as security vulnerabilities has proven…

With the rapid development of AI technologies, thousands of AI papers are being published each year. Many of these papers have released sample code to facilitate follow-up researchers. This paper presents an explorative study of over 1700…

Following the recent release of AI assistants, such as OpenAI's ChatGPT and GitHub Copilot, the software industry quickly utilized these tools for software development tasks, e.g., generating code or consulting AI for advice. While recent…

Code reviews are an integral part of software development and have been recognized as a crucial practice for minimizing bugs and favouring higher code quality. They serve as an important checkpoint before committing code and play an…

Large language models (LLMs) have demonstrated impressive capabilities in code generation, achieving high scores on benchmarks such as HumanEval and MBPP. However, these benchmarks primarily assess functional correctness and neglect broader…

This paper presents a comprehensive empirical analysis of security vulnerabilities in AI-generated code across public GitHub repositories. We collected and analyzed 7,703 files explicitly attributed to four major AI tools: ChatGPT…

AI coding agents are increasingly acting as autonomous contributors by generating and submitting pull requests (PRs). However, we lack empirical evidence on how these agent-generated PRs differ from human contributions, particularly in how…

Code review is a key development practice that contributes to improve software quality and to foster knowledge sharing among developers. However, code review usually takes time and demands detailed and time-consuming analysis of textual…

Peer review serves as the gatekeeper of science, yet the surge in submissions and widespread adoption of large language models (LLMs) in scholarly evaluation present unprecedented challenges. While recent work has focused on using LLMs to…

Security vulnerabilities present in a code that has been written in diverse programming languages are among the most critical yet complicated aspects of source code to detect. Static analysis tools based on rule-based patterns usually do…

Context: Smart contract vulnerabilities pose significant security risks for the Ethereum ecosystem, driving the development of automated tools for detection and mitigation. Smart contracts are written in Solidity, a programming language…

Manual code reviews are an essential but time-consuming part of software development, often leading reviewers to prioritize technical issues while skipping valuable assessments. This paper presents an algorithmic model that automates…

Currently, while software engineers write code for various modules, quite often, various types of errors - coding, logic, semantic, and others (most of which are not caught by compilation and other tools) get introduced. Some of these bugs…

Code velocity, or the speed with which code changes are integrated into a production environment, plays a crucial role in Continuous Integration and Continuous Deployment. Many studies report factors influencing code velocity. However,…

Traditional bug-tracking systems rely heavily on manual reporting, reproduction, classification, and resolution, involving multiple stakeholders such as end users, customer support, developers, and testers. This division of responsibilities…

The demand for quick and reliable DevOps operations pushed distributors of repository platforms to implement workflows. Workflows allow automating code management operations directly on the repository hosting the software. However, this…

There is a growing interest in the development of lidar-based autonomous mobility and Intelligent Transportation Systems (ITS). To operate and research on lidar data, researchers often develop code specific to application niche. This…

Many software systems originate as prototypes or minimum viable products (MVPs), developed with an emphasis on delivery speed and responsiveness to changing requirements rather than long-term code maintainability. While effective for rapid…

Large Language Model (LLM) - based Automated Program Repair (APR) systems are increasingly integrated into modern software development workflows, offering automated patches in response to natural language bug reports. However, this reliance…

Code review remains a critical yet resource-intensive process in software development, particularly challenging in large-scale industrial environments. While Large Language Models (LLMs) show promise for automating code review, existing…