Predicting function names in stripped binaries is an extremely useful but challenging task, as
it requires summarizing the execution behavior and semantics of the function in human …

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 …

Code representation, which transforms programs into vectors with semantics, is essential for
source code processing. We have witnessed the effectiveness of incorporating structural …

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 …

In programming, the names for the program entities, especially for the methods, are the
intuitive characteristic for understanding the functionality of the code. To ensure the …

Pre-trained Large Language Models (LLM) have achieved remarkable successes in several
domains. However, code-oriented LLMs are often heavy in computational complexity, and …

The quality of method names is critical for the readability and maintainability of source code.
However, it is often challenging to construct concise method names. To alleviate this …

In this paper we consider the research and development of classifiers that are trained to
predict the task solved by source code. Possible applications of such task detection …

This paper presents a dataset containing automatically collected source codes solving
unique programming exercises of different types. The programming exercises were …

Research into automated grading has increased as Computer Science courses grow.
Dynamic and static approaches are typically used to implement these graders, the most …