Deep learning for android malware defenses: a systematic literature review
Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …
threat to developers and end-users. Numerous research efforts have been devoted to …
Linevul: A transformer-based line-level vulnerability prediction
Software vulnerabilities are prevalent in software systems, causing a variety of problems
including deadlock, information loss, or system failures. Thus, early predictions of software …
including deadlock, information loss, or system failures. Thus, early predictions of software …
Refining chatgpt-generated code: Characterizing and mitigating code quality issues
Since its introduction in November 2022, ChatGPT has rapidly gained popularity due to its
remarkable ability in language understanding and human-like responses. ChatGPT, based …
remarkable ability in language understanding and human-like responses. ChatGPT, based …
LineVD: statement-level vulnerability detection using graph neural networks
Current machine-learning based software vulnerability detection methods are primarily
conducted at the function-level. However, a key limitation of these methods is that they do …
conducted at the function-level. However, a key limitation of these methods is that they do …
VulRepair: a T5-based automated software vulnerability repair
As software vulnerabilities grow in volume and complexity, researchers proposed various
Artificial Intelligence (AI)-based approaches to help under-resourced security analysts to …
Artificial Intelligence (AI)-based approaches to help under-resourced security analysts to …
Semi-supervised log-based anomaly detection via probabilistic label estimation
With the growth of software systems, logs have become an important data to aid system
maintenance. Log-based anomaly detection is one of the most important methods for such …
maintenance. Log-based anomaly detection is one of the most important methods for such …
Using pre-trained models to boost code review automation
Code review is a practice widely adopted in open source and industrial projects. Given the
non-negligible cost of such a process, researchers started investigating the possibility of …
non-negligible cost of such a process, researchers started investigating the possibility of …
Code prediction by feeding trees to transformers
Code prediction, more specifically autocomplete, has become an essential feature in
modern IDEs. Autocomplete is more effective when the desired next token is at (or close to) …
modern IDEs. Autocomplete is more effective when the desired next token is at (or close to) …
Jitline: A simpler, better, faster, finer-grained just-in-time defect prediction
C Pornprasit… - 2021 IEEE/ACM 18th …, 2021 - ieeexplore.ieee.org
A Just-In-Time (JIT) defect prediction model is a classifier to predict if a commit is defect-
introducing. Recently, CC2Vec-a deep learning approach for Just-In-Time defect prediction …
introducing. Recently, CC2Vec-a deep learning approach for Just-In-Time defect prediction …
A systematic literature review of explainable AI for software engineering
AH Mohammadkhani, NS Bommi, M Daboussi… - arxiv preprint arxiv …, 2023 - arxiv.org
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 …
the main solutions to tackle many software engineering (SE) tasks, in research studies …