Exploiting machine learning techniques for analyzing programs has attracted much
attention. One key problem is how to represent code fragments well for follow-up analysis …

Predictive models are one of the most important techniques that are widely applied in many
areas of software engineering. There have been a large number of primary studies that …

Cyber attacks cost the global economy approximately $445 billion per year. To mitigate
attacks, many companies rely on cyber threat intelligence (CTI), or threat intelligence related …

Code search aims to retrieve accurate code snippets based on a natural language query to
improve software productivity and quality. With the massive amount of available programs …

In empirical studies on processes, practices, and techniques of software engineering,
automation and machine learning are gaining popularity. In order to extract knowledge from …

Code summarization aims at generating a code comment given a block of source code and
it is normally performed by training machine learning algorithms on existing code block …

Word representation plays a key role in natural language processing (NLP). Various
representation methods have been developed, among which pre-trained word embeddings …

Context: Categorising software systems according to their functionality yields many benefits
to both users and developers. Goal: In order to uncover the latent clustering of mobile apps …

Code retrieval is a common practice for programmers to reuse existing code snippets in the
open-source repositories. Given a user query (ie, a natural language description), code …

Many large companies today face the risk of data breaches via malicious software,
compromising their business. These types of attacks are usually executed using hacker …