Large language models for software engineering: A systematic literature review
Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …
Software Engineering (SE). Many recent publications have explored LLMs applied to …
A survey on large language models for software engineering
Software Engineering (SE) is the systematic design, development, and maintenance of
software applications, underpinning the digital infrastructure of our modern mainworld. Very …
software applications, underpinning the digital infrastructure of our modern mainworld. Very …
Chain-of-thought in neural code generation: From and for lightweight language models
Large Language Models (LLMs) have demonstrated remarkable potential in code
generation. The integration of Chain of Thought (CoT) reasoning can further boost their …
generation. The integration of Chain of Thought (CoT) reasoning can further boost their …
Towards prompt tuning-based software vulnerability assessment with continual learning
J Xue, X Chen, J Wang, Z Cui - Computers & Security, 2024 - Elsevier
Software vulnerability assessment (SVA) has become increasingly important due to the
growing reliance on various software systems and the rising complexity of cyber threats …
growing reliance on various software systems and the rising complexity of cyber threats …
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 …
Context-aware code generation with synchronous bidirectional decoder
Code generation aims to map natural language descriptions to code snippets. Recent
approaches using sequence-to-tree models have shown promising results. However, they …
approaches using sequence-to-tree models have shown promising results. However, they …
SABER: Model-agnostic Backdoor Attack on Chain-of-Thought in Neural Code Generation
N Jin, Z Li, Y Guo, C Su, T Zhang, Q Zeng - arXiv preprint arXiv …, 2024 - arxiv.org
Recent studies have proposed integrating Chain-of-Thought (CoT) reasoning to further
enhance the reliability of Code Language Models (CLMs) in generating code, a step-by-step …
enhance the reliability of Code Language Models (CLMs) in generating code, a step-by-step …
Example-Based Automatic Migration of Continuous Integration Systems
Continuous Integration (CI) is a widely adopted practice for faster code change integration
and testing. Developers often migrate between CI systems in pursuit of features like matrix …
and testing. Developers often migrate between CI systems in pursuit of features like matrix …
[PDF][PDF] The Journal of Systems & Software
X Zhang, H Pham - 2022 - wssun.github.io
abstract Test case prioritization (TCP) aims to reorder the regression test suite with a goal of
increasing the fault detection rate. Various TCP techniques have been proposed based on …
increasing the fault detection rate. Various TCP techniques have been proposed based on …
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding
PRETVIAO GROUNDING - openreview.net
Language models (LMs) have become a staple of the code-writing toolbox. Their pre-
training recipe has, however, remained stagnant over recent years, barring the occasional …
training recipe has, however, remained stagnant over recent years, barring the occasional …