Large Language Models (LLMs), built upon Transformer-based architectures with massive
pretraining on diverse data, have not only revolutionized natural language processing but …

Measuring and evaluating source code similarity is a fundamental software engineering
activity that embraces a broad range of applications, including but not limited to code …

Search-based software testing (SBST) generates high-coverage test cases for programs
under test with a combination of test case generation and mutation. SBST's performance …

Benchmark datasets have a significant impact on accelerating research in programming
language tasks. In this paper, we introduce CodeXGLUE, a benchmark dataset to foster …

The task of generating code solutions for a given programming problem can benefit from the
use of pre-trained language models such as Codex, which can produce multiple diverse …

Deep Learning (DL) systems have received exponential growth in popularity and have
become ubiquitous in our everyday life. Such systems are built on top of popular DL …

Unit tests play a key role in ensuring the correctness of software. However, manually
creating unit tests is a laborious task, motivating the need for automation. Large Language …

Unit testing is essential in detecting bugs in functionally-discrete program units. Manually
writing high-quality unit tests is time-consuming and laborious. Although traditional …

Deep learning (DL) techniques are gaining more and more attention in the software
engineering community. They have been used to support several code-related tasks, such …

A transcompiler, also known as source-to-source translator, is a system that converts source
code from a high-level programming language (such as C++ or Python) to another …