The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

As the role of information and communication technologies gradually increases in our lives,
software security becomes a major issue to provide protection against malicious attempts …

Background: Software vulnerabilities are weaknesses in source code that might be exploited
to cause harm or loss. Previous work has proposed a number of automated machine …

Thousands of security vulnerabilities are discovered in production software each year, either
reported publicly to the Common Vulnerabilities and Exposures database or discovered …

Recent years have seen the successful application of deep learning to software engineering
(SE). In particular, the development and use of pre-trained models of source code has …

Artificial Intelligence (AI) and Machine Learning (ML) are pervasive in the current computer
science landscape. Yet, there still exists a lack of software engineering experience and best …

Automated source code generation is currently a popular machine-learning-based task. It
can be helpful for software developers to write functionally correct code from a given context …

Current statistical language modeling techniques, including deep-learning based models,
have proven to be quite effective for source code. We argue here that the special properties …

Source code static analysis has been widely used to detect vulnerabilities in the
development of software products. The vulnerability patterns purely based on human …

Several advances in deep learning have been successfully applied to the software
development process. Of recent interest is the use of neural language models to build tools …