23 citations · 37 across the 7 of their papers we have counts for
7 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…
A Systematic Mapping Study of Crowd Knowledge Enhanced Software Engineering Research Using Stack Overflow
Minaoar Tanzil, Shaiful Chowdhury, Somayeh Modaberi +2
Developers continuously interact in crowd-sourced community-based question-answer (Q&A) sites. Reportedly, 30% of all software professionals visit the most popular Q&A site StackOv…
Can ChatGPT Support Developers? An Empirical Evaluation of Large Language Models for Code Generation
Kailun Jin, Chung-Yu Wang, Hung Viet Pham +1
Large language models (LLMs) have demonstrated notable proficiency in code generation, with numerous prior studies showing their promising capabilities in various development scena…
Log-based Anomaly Detection of Enterprise Software: An Empirical Study
Nadun Wijesinghe, Hadi Hemmati
Most enterprise applications use logging as a mechanism to diagnose anomalies, which could help with reducing system downtime. Anomaly detection using software execution logs has b…
Gray-box Adversarial Attack of Deep Reinforcement Learning-based Trading Agents
Foozhan Ataiefard, Hadi Hemmati
In recent years, deep reinforcement learning (Deep RL) has been successfully implemented as a smart agent in many systems such as complex games, self-driving cars, and chat-bots. O…
A Systematic Literature Review of Explainable AI for Software Engineering
Ahmad Haji Mohammadkhani, Nitin Sai Bommi, Mariem Daboussi +3
Context: In recent years, leveraging machine learning (ML) techniques has become one of the main solutions to tackle many software engineering (SE) tasks, in research studies (ML4S…