| Title | Characterizing and Detecting WebAssembly Runtime Bugs |
| Authors | Zhang, Yixuan Cao, Shangtong Wang, Haoyu Chen, Zhenpeng Luo, Xiapu Mu, Dongliang Ma, Yun Huang, Gang Liu, Xuanzhe |
| Affiliation | Peking Univ, Minist Educ, Key Lab High Confidence Software Technol Peking U, Sch Comp Sci, Beijing, Peoples R China Beijing Univ Posts & Telecommun, Beijing, Peoples R China Huazhong Univ Sci & Technol, Wuhan, Peoples R China UCL, London, England Hong Kong Polytecn Univ, Hong Kong, Peoples R China Peking Univ, Sch Comp Sci, Beijing, Peoples R China Natl Key Lab Data Space Technol & Syst, Beijing, Peoples R China Peking Univ, 5 Yiheyuan Rd, Beijing, Peoples R China |
| Issue Date | Feb-2024 |
| Publisher | ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY |
| Abstract | WebAssembly (abbreviated WASM) has emerged as a promising language of the Web and also been used for a wide spectrum of software applications such as mobile applications and desktop applications. These applications, named WASM applications, commonly run in WASM runtimes. Bugs in WASM runtimes are frequently reported by developers and cause the crash of WASM applications. However, these bugs have not been well studied. To fill in the knowledge gap, we present a systematic study to characterize and detect bugs in WASM runtimes. We first harvest a dataset of 311 real-world bugs from hundreds of related posts on GitHub. Based on the collected high-quality bug reports, we distill 31 bug categories of WASM runtimes and summarize their common fix strategies. Furthermore, we develop a pattern-based bug detection framework to automatically detect bugs inWASM runtimes. We apply the detection framework to seven popular WASM runtimes and successfully uncover 60 bugs that have never been reported previously, among which 13 have been confirmed and 9 have been fixed by runtime developers. |
| URI | http://hdl.handle.net/20.500.11897/710964 |
| ISSN | 1049-331X |
| DOI | 10.1145/3624743 |
| Indexed | SCI(E) |
| Appears in Collections: | 信息科学技术学院 高可信软件技术教育部重点实验室 |
