2 citations · 4 across the 4 of their papers we have counts for
4 papers
Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach
Melika Sepidband, Hamed Taherkhani, Song Wang +1
Automatic code generation has gained significant momentum with the advent of Large Language Models (LLMs) such as GPT-4. Although many studies focus on improving the effectiveness…
SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection
Md Basim Uddin Ahmed, Nima Shiri Harzevili, Jiho Shin +2
Large Language Models (LLMs) have shown promise in software engineering tasks, but evaluating their effectiveness in vulnerability detection is challenging due to the lack of high-…
A Survey on Query-based API Recommendation
Moshi Wei, Nima Shiri Harzevili, Alvine Boaye Belle +6
Application Programming Interfaces (APIs) are designed to help developers build software more effectively. Recommending the right APIs for specific tasks has gained increasing atte…
Developer-Intent Driven Code Comment Generation
Fangwen Mu, Xiao Chen, Lin Shi +2
Existing automatic code comment generators mainly focus on producing a general description of functionality for a given code snippet without considering developer intentions. Howev…