9 citations · 23 across the 11 of their papers we have counts for
11 papers
From Metrics to Improvement: A Lifecycle-Aware LLM Feedback Framework for Research Software Quality
Nafis Tanveer Islam, Nafiseh Soveizi, Yutong Li +1
Research software is increasingly central to scientific workflows, yet it is often developed by researchers with limited software engineering expertise. This can lead to quality is…
How good are LLMs at Retrieving Documents in a Specific Domain?
Nafis Tanveer Islam, Zhiming Zhao
Classical search engines using indexing methods in data infrastructures primarily allow keyword-based queries to retrieve content. While these indexing-based methods are highly sca…
How Reliable are LLMs for Reasoning on the Re-ranking task?
Nafis Tanveer Islam, Zhiming Zhao
With the improving semantic understanding capability of Large Language Models (LLMs), they exhibit a greater awareness and alignment with human values, but this comes at the cost o…
Enhancing Reverse Engineering: Investigating and Benchmarking Large Language Models for Vulnerability Analysis in Decompiled Binaries
Dylan Manuel, Nafis Tanveer Islam, Joseph Khoury +3
Security experts reverse engineer (decompile) binary code to identify critical security vulnerabilities. The limited access to source code in vital systems - such as firmware, driv…
AutoSafeCoder: A Multi-Agent Framework for Securing LLM Code Generation through Static Analysis and Fuzz Testing
Ana Nunez, Nafis Tanveer Islam, Sumit Kumar Jha +1
Recent advancements in automatic code generation using large language models (LLMs) have brought us closer to fully automated secure software development. However, existing approac…
Enhancing Source Code Security with LLMs: Demystifying The Challenges and Generating Reliable Repairs
Nafis Tanveer Islam, Joseph Khoury, Andrew Seong +2
With the recent unprecedented advancements in Artificial Intelligence (AI) computing, progress in Large Language Models (LLMs) is accelerating rapidly, presenting challenges in est…
Unintentional Security Flaws in Code: Automated Defense via Root Cause Analysis
Nafis Tanveer Islam, Mazal Bethany, Dylan Manuel +2
Software security remains a critical concern, particularly as junior developers, often lacking comprehensive knowledge of security practices, contribute to codebases. While there a…
LLM-Powered Code Vulnerability Repair with Reinforcement Learning and Semantic Reward
Nafis Tanveer Islam, Joseph Khoury, Andrew Seong +4
In software development, the predominant emphasis on functionality often supersedes security concerns, a trend gaining momentum with AI-driven automation tools like GitHub Copilot.…
Code Security Vulnerability Repair Using Reinforcement Learning with Large Language Models
Nafis Tanveer Islam, Mohammad Bahrami Karkevandi, Peyman Najafirad
With the recent advancement of Large Language Models (LLMs), generating functionally correct code has become less complicated for a wide array of developers. While using LLMs has s…
Causative Insights into Open Source Software Security using Large Language Code Embeddings and Semantic Vulnerability Graph
Nafis Tanveer Islam, Gonzalo De La Torre Parra, Dylan Manual +2
Open Source Software (OSS) security and resilience are worldwide phenomena hampering economic and technological innovation. OSS vulnerabilities can cause unauthorized access, data…
An Unbiased Transformer Source Code Learning with Semantic Vulnerability Graph
Nafis Tanveer Islam, Gonzalo De La Torre Parra, Dylan Manuel +2
Over the years, open-source software systems have become prey to threat actors. Even as open-source communities act quickly to patch the breach, code vulnerability screening should…