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Distilled GPT for source code summarization
A code summary is a brief natural language description of source code. Summaries are
usually only a single sentence long, and yet form the backbone of developer documentation …
usually only a single sentence long, and yet form the backbone of developer documentation …
A closer look into transformer-based code intelligence through code transformation: Challenges and opportunities
Transformer-based models have demonstrated state-of-the-art performance in many
intelligent coding tasks such as code comment generation and code completion. Previous …
intelligent coding tasks such as code comment generation and code completion. Previous …
Automatic smart contract comment generation via large language models and in-context learning
Context: Designing effective automatic smart contract comment generation approaches can
facilitate developers' comprehension, boosting smart contract development and improving …
facilitate developers' comprehension, boosting smart contract development and improving …
Where Are Large Language Models for Code Generation on GitHub?
The increasing use of Large Language Models (LLMs) in software development has
garnered significant attention from researchers assessing the quality of the code they …
garnered significant attention from researchers assessing the quality of the code they …
Bashexplainer: Retrieval-augmented bash code comment generation based on fine-tuned codebert
Developers use shell commands for many tasks, such as file system management, network
control, and process management. Bash is one of the most commonly used shells and plays …
control, and process management. Bash is one of the most commonly used shells and plays …
Automatic bi-modal question title generation for Stack Overflow with prompt learning
When drafting question posts for Stack Overflow, developers may not accurately summarize
the core problems in the question titles, which can cause these questions to not get timely …
the core problems in the question titles, which can cause these questions to not get timely …
Deep representation learning: Fundamentals, technologies, applications, and open challenges
Machine learning algorithms have had a profound impact on the field of computer science
over the past few decades. The performance of these algorithms heavily depends on the …
over the past few decades. The performance of these algorithms heavily depends on the …
Understanding the Robustness of Transformer-Based Code Intelligence via Code Transformation: Challenges and Opportunities
Transformer-based models have demonstrated state-of-the-art performance in various
intelligent coding tasks such as code comment generation and code completion. Previous …
intelligent coding tasks such as code comment generation and code completion. Previous …
Learning to parallelize in a shared-memory environment with transformers
In past years, the world has switched to multi and many core shared memory architectures.
As a result, there is a growing need to utilize these architectures by introducing shared …
As a result, there is a growing need to utilize these architectures by introducing shared …
Automated question title reformulation by mining modification logs from stack overflow
In Stack Overflow, developers may not clarify and summarize the critical problems in the
question titles due to a lack of domain knowledge or poor writing skills. Previous studies …
question titles due to a lack of domain knowledge or poor writing skills. Previous studies …