89 citations · 156 across the 19 of their papers we have counts for
19 papers · 1 filter
ContraFix: Skill-Enhanced Contrastive Runtime Analysis for Vulnerability Repair
Simiao Liu, Fang Liu, Peiding Wang +4
As software systems grow increasingly complex, automated vulnerability repair (AVR) remains difficult because the materials available to a repair system are usually failure artifac…
MemRepair: Hierarchical Memory for Agentic Repository-Level Vulnerability Repair
Simiao Liu, Li Zhang, Fang Liu +3
Modern software ecosystems face a rapidly growing number of disclosed vulnerabilities, increasing the need for automated repair techniques that can operate reliably at repository s…
Aligning Academia with Industry: An Empirical Study of Industrial Needs and Academic Capabilities in AI-Driven Software Engineering
Hang Yu, Yuzhou Lai, Li Zhang +6
The rapid advancement of large language models (LLMs) is fundamentally reshaping software engineering (SE), driving a paradigm shift in both academic research and industrial practi…
Towards Realistic Project-Level Code Generation via Multi-Agent Collaboration and Semantic Architecture Modeling
Qianhui Zhao, Li Zhang, Fang Liu +8
In recent years, Large Language Models (LLMs) have achieved remarkable progress in automated code generation. In real-world software engineering, the growing demand for rapid itera…
SecureReviewer: Enhancing Large Language Models for Secure Code Review through Secure-aware Fine-tuning
Fang Liu, Simiao Liu, Yinghao Zhu +2
Identifying and addressing security issues during the early phase of the development lifecycle is critical for mitigating the long-term negative impacts on software systems. Code r…
An Empirical Study on Failures in Automated Issue Solving
Simiao Liu, Fang Liu, Liehao Li +4
Automated issue solving seeks to autonomously identify and repair defective code snippets across an entire codebase. SWE-Bench has emerged as the most widely adopted benchmark for…
EfficientEdit: Accelerating Code Editing via Edit-Oriented Speculative Decoding
Peiding Wang, Li Zhang, Fang Liu +7
Large Language Models (LLMs) have demonstrated remarkable capabilities in code editing, substantially enhancing software development productivity. However, the inherent complexity…
Vision to Specification: Automating the Transition from Conceptual Features to Functional Requirements
Xiaoli Lian, Jiajun Wu, Xiaoyun Gao +2
The translation of high-level abstract features into clear, and testable functional requirements (FRs) is a crucial step in software development, bridging the gap between user need…
Incorporating Verification Standards for Security Requirements Generation from Functional Specifications
Xiaoli Lian, Shuaisong Wang, Hanyu Zou +3
In the current software driven era, ensuring privacy and security is critical. Despite this, the specification of security requirements for software is still largely a manual and l…
Revolutionizing Newcomers' Onboarding Process in OSS Communities: The Future AI Mentor
Xin Tan, Xiao Long, Yinghao Zhu +3
Onboarding newcomers is vital for the sustainability of open-source software (OSS) projects. To lower barriers and increase engagement, OSS projects have dedicated experts who prov…
AutoPLC: Generating Vendor-Aware Structured Text for Programmable Logic Controllers
Donghao Yang, Aolang Wu, Tianyi Zhang +6
Among the programming languages for Programmable Logic Controllers (PLCs), Structured Text (ST) is widely adopted for industrial automation due to its expressiveness and flexibilit…
Deep Learning-based Software Engineering: Progress, Challenges, and Opportunities
Xiangping Chen, Xing Hu, Yuan Huang +23
Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language p…
Enhancing Automated Program Repair with Solution Design
Jiuang Zhao, Donghao Yang, Li Zhang +3
Automatic Program Repair (APR) endeavors to autonomously rectify issues within specific projects, which generally encompasses three categories of tasks: bug resolution, new feature…
Uncovering Weaknesses in Neural Code Generation
Xiaoli Lian, Shuaisong Wang, Jieping Ma +5
Code generation, the task of producing source code from prompts, has seen significant advancements with the advent of pre-trained large language models (PLMs). Despite these achiev…
A Novel Approach for Automated Design Information Mining from Issue Logs
Jiuang Zhao, Zitian Yang, Li Zhang +2
Software architectures are usually meticulously designed to address multiple quality concerns and support long-term maintenance. However, due to the imbalance between the cost and…
Beyond Functional Correctness: Exploring Hallucinations in LLM-Generated Code
Fang Liu, Yang Liu, Lin Shi +5
The rise of Large Language Models (LLMs) has significantly advanced various applications on software engineering tasks, particularly in code generation. Despite the promising perfo…
Automated Generating Natural Language Requirements based on Domain Ontology
Ziyan Zhao, Li Zhang, Xiaoyun Gao +3
Software requirements specification is undoubtedly critical for the whole software life-cycle. Nowadays, writing software requirements specifications primarily depends on human wor…
A Preliminary Study on the Potential Usefulness of Open Domain Model for Missing Software Requirements Recommendation
Ziyan Zhao, Li Zhang, Xiaoli Lian
Completeness is one of the most important attributes of software requirement specifications. Unfortunately, incompleteness is meanwhile one of the most difficult problems to detect…
Automatically detecting the conflicts between software requirements based on finer semantic analysis
Weize Guo, Li Zhang, Xiaoli Lian
Context: Conflicts between software requirements bring uncertainties to product development. Some great approaches have been proposed to identify these conflicts. However, they usu…