27 citations · 69 across the 11 of their papers we have counts for
11 papers
Agent-Based Test Assertion Generation via Diverse Perspective Aggregation
Dong Wang, Qiaoyu Han, Lin Yang +3
Test assertions are critical elements of unit tests, serving as checkpoints to validate expected behavior and ensure software correctness. Numerous techniques have been proposed to…
CodeV: Issue Resolving with Visual Data
Linhao Zhang, Daoguang Zan, Quanshun Yang +10
Large Language Models (LLMs) have advanced rapidly in recent years, with their applications in software engineering expanding to more complex repository-level tasks. GitHub issue r…
SWE-bench-java: A GitHub Issue Resolving Benchmark for Java
Daoguang Zan, Zhirong Huang, Ailun Yu +17
GitHub issue resolving is a critical task in software engineering, recently gaining significant attention in both industry and academia. Within this task, SWE-bench has been releas…
CodeR: Issue Resolving with Multi-Agent and Task Graphs
Dong Chen, Shaoxin Lin, Muhan Zeng +14
GitHub issue resolving recently has attracted significant attention from academia and industry. SWE-bench is proposed to measure the performance in resolving issues. In this paper,…
On the Evaluation of Large Language Models in Unit Test Generation
Lin Yang, Chen Yang, Shutao Gao +8
Unit testing is an essential activity in software development for verifying the correctness of software components. However, manually writing unit tests is challenging and time-con…
CompVPD: Iteratively Identifying Vulnerability Patches Based on Human Validation Results with a Precise Context
Tianyu Chen, Lin Li, Taotao Qian +6
Applying security patches in open source software timely is critical for ensuring the security of downstream applications. However, it is challenging to apply these patches promptl…
VulLibGen: Generating Names of Vulnerability-Affected Packages via a Large Language Model
Tianyu Chen, Lin Li, Liuchuan Zhu +5
Security practitioners maintain vulnerability reports (e.g., GitHub Advisory) to help developers mitigate security risks. An important task for these databases is automatically ext…
Identifying Vulnerable Third-Party Java Libraries from Textual Descriptions of Vulnerabilities and Libraries
Tianyu Chen, Lin Li, Bingjie Shan +4
To address security vulnerabilities arising from third-party libraries, security researchers maintain databases monitoring and curating vulnerability reports. Application developer…
Eunomia: Enabling User-specified Fine-Grained Search in Symbolically Executing WebAssembly Binaries
Ningyu He, Zhehao Zhao, Jikai Wang +7
Although existing techniques have proposed automated approaches to alleviate the path explosion problem of symbolic execution, users still need to optimize symbolic execution by ap…
CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models
Hao Yu, Bo Shen, Dezhi Ran +7
Code generation models based on the pre-training and fine-tuning paradigm have been increasingly attempted by both academia and industry, resulting in well-known industrial models…
PanGu-Coder: Program Synthesis with Function-Level Language Modeling
Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta +19
We present PanGu-Coder, a pretrained decoder-only language model adopting the PanGu-Alpha architecture for text-to-code generation, i.e. the synthesis of programming language solut…