In recent years, Large Language Models (LLMs) have achieved remarkable success and
have been widely used in various downstream tasks, especially in the tasks of the software …

Efficient code search techniques are crucial in accelerating software development by aiding
developers in locating specific code snippets and understanding code functionalities. This …

Given the increasing complexity and volume of Self‐Admitted Technical Debts (SATDs), how
to efficiently detect them becomes critical in software engineering practice for improving …

Automated code completion, aiming at generating subsequent tokens from unfinished code,
has been significantly benefited from recent progress in pre-trained Large Language Models …

Code search plays an important role in enhancing the productivity of software developers.
Throughout the years, numerous code search tools have been developed and widely …

Within the realm of advanced code retrieval, existing methods have primarily relied on
intricate matching and attention-based mechanisms. However, these methods often lead to …

The masked language modeling (MLM) task is widely recognized as one of the most
effective pre-training tasks and currently derives many variants in the software engineering …

Recent studies proposed to leverage large language models (LLMs) with In-Context
Learning (ICL) to handle code intelligence tasks without fine-tuning. ICL employs task …

Automated log analysis is crucial to ensure high availability and reliability of complex
systems. The advent of LLMs in NLP has ushered in a new era of language model-driven …

The deep‐learning based code search model mainly takes accuracy as the only target for
judging the performance of the model, ignoring the efficiency of code search. This article …