LeakPair: Proactive Repairing of Memory Leaks in Single Page Web Applications
Modern web applications often resort to application development frameworks such as React, Vue.js, and Angular. While the frameworks facilitate the development of web applications with several useful components, they are inevitably vulnerable to unmanaged memory consumption since the frameworks often produce Single Page Applications (SPAs). Web applications can be alive for hours and days with behavior loops, in such cases, even a single memory leak in a SPA app can cause performance degradation on the client side. However, recent debugging techniques for web applications still focus on memory leak detection, which requires manual tasks and produces imprecise results.
We propose LeakPair, a technique to repair memory leaks in single page applications. Given the insight that memory leaks are mostly non-functional bugs and fixing them might not change the behavior of an application, the technique is designed to proactively generate patches to fix memory leaks, without leak detection, which is often heavy and tedious. To generate effective patches, LeakPair follows the idea of pattern-based program repair since the automated repair strategy shows successful results in many recent studies. We evaluate the technique on more than 20 open-source projects without using explicit leak detection. The patches generated by our technique are also submitted to the projects as pull requests. The results show that LeakPair can generate effective patches to reduce memory consumption that are acceptable to developers. In addition, we execute the test suites given by the projects after applying the patches, and it turns out that the patches do not cause any functionality breakage; this might imply that LeakPair can generate non-intrusive patches for memory leaks.
Thu 14 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
10:30 - 12:00 | Program Repair 2Research Papers / Journal-first Papers / NIER Track at Plenary Room 2 Chair(s): Shin Yoo KAIST | ||
10:30 12mTalk | An Empirical Study on Fine-tuning Large Language Models of Code for Automated Program Repair Research Papers Kai Huang , Xiangxin Meng Beihang University, Beijing, China, Jian Zhang Nanyang Technological University, Yang Liu Nanyang Technological University, Wenjie Wang University of Chinese Academy of Sciences, Shuhao Li Zhongguancun Laboratory, Yuqing Zhang University of Chinese Academy of Sciences; Zhongguancun Laboratory File Attached | ||
10:42 12mTalk | Estimating the Potential of Program Repair Search Spaces with Commit Analysis Journal-first Papers Khashayar Etemadi KTH Royal Institute of Technology, Niloofar Tarighat Sharif University of Technology, Siddharth Yadav IIIT-Delhi, Matias Martinez Universitat Politècnica de Catalunya (UPC), Martin Monperrus KTH Royal Institute of Technology Link to publication File Attached | ||
10:54 12mTalk | LeakPair: Proactive Repairing of Memory Leaks in Single Page Web Applications Research Papers Arooba Shahoor Kyungpook National University, Askar Yeltayuly Khamit Ulsan National Institute of Science and Technology, Jooyong Yi UNIST (Ulsan National Institute of Science and Technology), Dongsun Kim Kyungpook National University Pre-print Media Attached | ||
11:06 12mTalk | Automated Fixing of Web UI Tests via Iterative Element Matching Research Papers Yuanzhang Lin Beihang University, Guoyao Wen Huawei Technologies Co., Ltd., Xiang Gao Beihang University Pre-print Media Attached | ||
11:18 12mTalk | OrdinalFix: Fixing Compilation Errors via Shortest-Path CFL Reachability with Attribute Checking Research Papers Wenjie Zhang Peking University, Guancheng Wang Peking University, China, Junjie Chen Tianjin University, Yingfei Xiong Peking University, Yong Liu Beijing University of Chemical Technology, Lu Zhang Peking University Pre-print File Attached | ||
11:30 12mTalk | Hot Patching Hot Fixes: Reflection and Perspectives NIER Track Pre-print File Attached |