Pre-trained models of code have achieved success in many important software engineering
tasks. However, these powerful models are vulnerable to adversarial attacks that slightly …

Pre-trained Generative Language models (eg, PLBART, CodeT5, SPT-Code) for source
code yielded strong results on several tasks in the past few years, including code generation …

Binary reverse engineering is used to understand and analyse programs for which the
source code is unavailable. Decompilers can help, transforming opaque binaries into a …

Static analysis is a powerful tool for detecting security vulnerabilities and other programming
problems. Global taint tracking, in particular, can spot vulnerabilities arising from …

Static analysis tools find defects in code, checking code against rules to reveal potential
defects. Many studies have evaluated these tools by measuring their ability to detect known …

Artificial Intelligence (AI) models have emerged as another important audience for
programming languages alongside humans and machines, as we enter the era of large …

Transformer-based pre-trained models have recently achieved great results in solving many
software engineering tasks including automatic code completion which is a staple in a …

Deep Learning (DL) models to analyze source code have shown immense promise during
the past few years. More recently, self-supervised pre-training has gained traction for …

The expansion of the open source community and the rise of large language models have
raised ethical and security concerns on the distribution of source code, such as misconduct …

The expansion of the open source community and the rise of large language models have
raised ethical and security concerns on the distribution of source code, such as misconduct …