A systematic literature review on explainability for machine/deep learning-based software engineering research
The remarkable achievements of Artificial Intelligence (AI) algorithms, particularly in
Machine Learning (ML) and Deep Learning (DL), have fueled their extensive deployment …
Machine Learning (ML) and Deep Learning (DL), have fueled their extensive deployment …
Top score on the wrong exam: On benchmarking in machine learning for vulnerability detection
According to our survey of the machine learning for vulnerability detection (ML4VD)
literature published in the top Software Engineering conferences, every paper in the past 5 …
literature published in the top Software Engineering conferences, every paper in the past 5 …
Attention is all you need for llm-based code vulnerability localization
The rapid expansion of software systems and the growing number of reported vulnerabilities
have emphasized the importance of accurately identifying vulnerable code segments …
have emphasized the importance of accurately identifying vulnerable code segments …
Large Language Models and Code Security: A Systematic Literature Review
Large Language Models (LLMs) have emerged as powerful tools for automating various
programming tasks, including security-related ones, such as detecting and fixing …
programming tasks, including security-related ones, such as detecting and fixing …
VulAdvisor: Natural Language Suggestion Generation for Software Vulnerability Repair
Software vulnerabilities pose serious threats to the security of modern software systems.
Deep Learning-based Automated Vulnerability Repair (AVR) has gained attention as a …
Deep Learning-based Automated Vulnerability Repair (AVR) has gained attention as a …
Towards Effectively Detecting and Explaining Vulnerabilities Using Large Language Models
Software vulnerabilities pose significant risks to the security and integrity of software
systems. Prior studies have proposed a series of approaches to vulnerability detection using …
systems. Prior studies have proposed a series of approaches to vulnerability detection using …
An Empirical Study of Automated Vulnerability Localization with Large Language Models
Recently, Automated Vulnerability Localization (AVL) has attracted much attention, aiming to
facilitate diagnosis by pinpointing the lines of code responsible for discovered …
facilitate diagnosis by pinpointing the lines of code responsible for discovered …
An Empirical Study of Vulnerability Detection using Federated Learning
Although Deep Learning (DL) methods becoming increasingly popular in vulnerability
detection, their performance is seriously limited by insufficient training data. This is mainly …
detection, their performance is seriously limited by insufficient training data. This is mainly …
Detecting Vulnerabilities via Explicitly Leveraging Vulnerability Features on Program Slices
As the size and complexity of software continue to increase, detecting software
vulnerabilities becomes increasingly challenging. Traditional static and dynamic analysis …
vulnerabilities becomes increasingly challenging. Traditional static and dynamic analysis …
Building trustworthy AI from small DNNs to large language models: a software engineering perspective
T Li - 2025 - dr.ntu.edu.sg
As Artificial Intelligence (AI) software becomes increasingly prevalent across various
industries, concerns about its trustworthiness and reliability have come to the forefront …
industries, concerns about its trustworthiness and reliability have come to the forefront …