Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …

Software vulnerabilities are prevalent in software systems, causing a variety of problems
including deadlock, information loss, or system failures. Thus, early predictions of software …

As software vulnerabilities grow in volume and complexity, researchers proposed various
Artificial Intelligence (AI)-based approaches to help under-resourced security analysts to …

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 …

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 …

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 …

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 …

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) …

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 …

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 …