Let the Code Speak: Incorporating Program Dynamic State for Better Method-Level Fault Localization
This program is tentative and subject to change.
Fault localization (FL) is a critical but time-consuming part of software debugging. With the continuous improvement of the Large Language Models (LLMs) in their code capabilities, the increasing demand for automated software development and maintenance has encouraged more researchers to focus on building LLM-based Fault Localization (LLMFL) systems. However, existing LLMFL techniques are typically restricted to predicting bug locations by analyzing static code, while overlooking crucial dynamic program state of the software. This lack of context makes LLMs prone to generating “hallucinations”, incorrectly identifying bug-free code as suspicious. To address this, this paper introduces PingFL, the first LLMFL system that incorporates print debugging techniques for more accurate fault localization. PingFL comprises a Fault Localization (FL) agent and a Print Debugging (PD) agent. The FL agent is tasked with understanding the root cause through a set of callable tools. When the FL agent nominates a location as suspicious, it would entrust the PD agent to verify the suspected issue through multiple rounds of print debugging. In particular, these two agents communicate and collaborate efficiently by conveying the textual thought generated by the LLM. The evaluation on 812 real-world bugs from the Defects4J benchmark shows that PingFL can localize 450 bugs within Top-1, which significantly outperforms other LLM-based approaches by 41% to 122%. It also consistently surpasses traditional FL techniques in cross-project scenarios. A deeper dive into PingFL’s performance reveals that it exhibits specific FL strategies and tool usage patterns even without explicit instructions. Finally, PingFL proves to be cost-effective, spending an average of $0.22 and 104.62 seconds per bug, with the print debugging mechanism accounting for only $0.07 and 51.62 seconds.
This program is tentative and subject to change.
Tue 18 NovDisplayed time zone: Seoul change
11:00 - 12:30 | |||
11:00 10mTalk | FaultSeeker: LLM-Empowered Framework for Blockchain Transaction Fault Localization Research Papers Kairan Sun Nanyang Technological University, Zhengzi Xu Imperial Global Singapore, Kaixuan Li Nanyang Technological University, Lyuye Zhang Nanyang Technological University, Yuqiang Sun Nanyang Technological University, Liwei Tan MetaTrust Labs, Yang Liu Nanyang Technological University | ||
11:10 10mTalk | FlexFL: Flexible and Effective Fault Localization With Open-Source Large Language Models Journal-First Track Chuyang Xu Zhejiang University, Zhongxin Liu Zhejiang University, Xiaoxue Ren Zhejiang University, Gehao Zhang Ant Group, Ming Liang Ant Group, David Lo Singapore Management University | ||
11:20 10mTalk | LLM-Based Identification of Null Pointer Exception Patches Research Papers Tahir Ullah Beijing Institute of Technology, Waseem Akram Beijing Institute of Technology, Fiza Khaliq Beijing Institute of Technology, Hui Liu Beijing Institute of Technology | ||
11:30 10mTalk | SpectAcle: Fault Localisation of AI-Enabled CPS by Exploiting Sequences of DNN Controller Inferences Journal-First Track Deyun Lyu National Institute of Informatics, Zhenya Zhang Kyushu University, Japan, Paolo Arcaini National Institute of Informatics
, Xiao-Yi Zhang University of Science and Technology Beijing, Fuyuki Ishikawa National Institute of Informatics, Jianjun Zhao Kyushu University | ||
11:40 10mTalk | Sifting Truth from Coincidences: A Two-Stage Positive and Unlabeled Learning Model for Coincidental Correctness Detection Research Papers Chunyan Liu Chongqing University, Huan Xie Chongqing University, Yan Lei Chongqing University, Zhenyu Wu School of Big Data & Software Engineering, Chongqing University, Jinping Wang Chonqing University | ||
11:50 10mTalk | Let the Code Speak: Incorporating Program Dynamic State for Better Method-Level Fault Localization Research Papers Yihao Qin , Shangwen Wang National University of Defense Technology, Bo Lin National University of Defense Technology, Xin Peng , Sheng Ouyang National University of Defense Technology, Liqian Chen National University of Defense Technology, Xiaoguang Mao National University of Defense Technology | ||
12:00 10mTalk | Issue Localization via LLM-Driven Iterative Code Graph Searching Research Papers Zhonghao Jiang Zhejiang University, Xiaoxue Ren Zhejiang University, Meng Yan Chongqing University, Wei Jiang Ant Group, Yong Li Ant Group, Zhongxin Liu Zhejiang University | ||
12:10 10mTalk | Hypergraph Neural Network-based Multi-Granular Root Cause Localization for Microservice Systems Research Papers Yaxiao Li Xidian University, Lu Wang Xidian University, Chenxi Zhang Xidian University, Qingshan Li Xidian University, Siming Rong Xidian University, Baiyang Wen Xidian University, Xuyang Li Purdue University, Kun Ma Xidian University, Quanwei Du Xidian University, KeYang Li Xidian University, Lingfeng Pan Xidian University, Xinyue Li Peking University, MingXuan Hui Xidian University | ||
12:20 10mTalk | Explainable Fault Localization for Programming Assignments via LLM-Guided Annotation Research Papers Fang Liu Beihang University, Tianze Wang Beihang University, Li Zhang Beihang University, Zheyu Yang Beihang University, Jing Jiang Beihang University, Zian Sun Beihang University Pre-print | ||