From the 1 of 12 linked papers with an AI index.
12 papers
A Low-Cost Human-in-the-Loop Investigation of Toxicity on GitHub at Scale
Rahat Rizvi Rahman, Mia Mohammad Imran, Kostadin Damevski
The paper introduces a human-in-the-loop workflow that combines a small local LLM with a lightweight Random Forest validator to efficiently label toxicity in over 124,000 GitHub is…
AXE: Grey-Box Exploitability Confirmation for Localized Vulnerability Reports
Amirali Sajadi, Tu Nguyen, Kostadin Damevski +1
Vulnerability detection tools are widely adopted in software projects, yet they often overwhelm maintainers with false positives and non-actionable reports. Automated exploitation…
Investigating Conversational Agents to Support Secondary School Students Learning CSP
Matthew Frazier, Kostadin Damevski, Lori Pollock
Secondary school students enrolled in the AP Computer Science Principles (CSP) course commonly utilize web resources (e.g., tutorials, Q\&A sites) to better understand key concepts…
Towards Personalizing Secure Programming Education with LLM-Injected Vulnerabilities
Matthew Frazier, Kostadin Damevski
According to constructivist theory, students learn software security more effectively when examples are grounded in their own code. Generic examples often fail to connect with stud…
A Survey on Large Language Model Impact on Software Evolvability and Maintainability: the Good, the Bad, the Ugly, and the Remedy
Bruno Claudino Matias, Savio Freire, Juliana Freitas +3
Context. Large Language Models (LLMs) are increasingly embedded in software engineering workflows for tasks including code generation, summarization, repair, and testing. Empirical…
How Safe Are AI-Generated Patches? A Large-scale Study on Security Risks in LLM and Agentic Automated Program Repair on SWE-bench
Amirali Sajadi, Kostadin Damevski, Preetha Chatterjee
Large language models (LLMs) and their agentic frameworks are increasingly adopted to perform development tasks such as automated program repair (APR). While prior work has identif…