AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
It was found that most participants wrote inse-cure code, regardless of their levels of experience, when using an AI tool (GitHub Copilot), and the two groups differed in how they use the AI tool when writing code.
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.
This research investigates the possibility of replacing junior and intermediate programmers with artificial intelligence (AI)-based tools in the code generation process. To inspect the capabilities of these tools, the Qwen Coder tool was used to conduct the tests. The methodology used in the study is based on 10 tests,...
Large language models (LLMs) are increasingly integrated into software development workflows, yet a growing body of evidence shows that the code they generate often contains security vulnerabilities. Prior work has primarily focused on measuring the prevalence of such issues, providing useful evidence of risk but limit...
Security by design asks that security requirements are defined before code is written. Secure-code benchmarks typically measure the opposite situation: the agent receives the task without requirements and is scored with security tests it has not seen. We measured what changes when security requirements, selected from a...
It is concluded that developers should use LLMs at the source-code level to counter adversaries applying the same techniques on decompiled code and research should advance decompilation support for the growing language diversity in the iOS ecosystem.
Recent advances in large language models (LLMs) have led to widespread adoption of AI-coding tools and increasing deployment of AI-assisted code. While AI’s potential for programming productivity is becoming evident, the security of AI-attributed code is still poorly understood. In this work, we collect the largest set...
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