Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …

Context: Coding is an incremental activity where a developer may need to understand a
code before making suitable changes in the code. Code documentation is considered one of …

Data scientists often have to use other presentation tools (eg, Microsoft PowerPoint) to
create slides to communicate their analysis obtained using computational notebooks. Much …

Computational notebooks allow data scientists to express their ideas through a combination
of code and documentation. However, data scientists often pay attention only to the code …

Creating presentation slides is a critical but time-consuming task for data scientists. While
researchers have proposed many AI techniques to lift data scientists' burden on data …

Code generation models can benefit data scientists' productivity by automatically generating
code from context and text descriptions. An important measure of the modeling progress is …

Existing automatic code comment generators mainly focus on producing a general
description of functionality for a given code snippet without considering developer intentions …

Jupyter notebooks have become indispensable tools for data analysis and processing in
various domains. However, despite their widespread use, there is a notable research gap in …

Software documentation is often neglected, impacting maintenance and reuse and leading
to technical issues. In particular, when working with scientific software, such issues in the …

In recent years, the rise of deep learning and automation requirements in the software
industry has elevated Intelligent Software Engineering to new heights. The number of …