SmartBugs 2.0: An Execution Framework for Weakness Detection in Ethereum Smart Contracts
Smart contracts are blockchain programs that often handle valuable assets. Writing secure smart contracts is far from trivial, and any vulnerability may lead to significant financial losses. To support developers in identifying and eliminating vulnerabilities, methods and tools for the automated analysis have been proposed. However, the lack of commonly accepted benchmark suites and performance metrics makes it difficult to compare and evaluate such tools. Moreover, the tools are heterogeneous in their interfaces and reports as well as their runtime requirements, and installing several tools is time-consuming.
In this paper, we present SmartBugs 2.0, a modular execution framework. It provides a uniform interface to 19 tools aimed at smart contract analysis and accepts both Solidity source code and EVM bytecode as input. After describing its architecture, we highlight the features of the framework. We evaluate the framework via its reception by the community and illustrate its scalability by describing its role in a study involving 3.25 million analyses.
| presentation (talk.pdf) | 808KiB |
Tue 12 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
15:30 - 17:00 | Testing Tools and TechniquesNIER Track / Research Papers / Tool Demonstrations at Room E Chair(s): Tim Menzies North Carolina State University | ||
15:30 12mTalk | Modeling Programmer Attention as Scanpath Prediction NIER Track Aakash Bansal University of Notre Dame, Chia-Yi Su University of Notre Dame, Zachary Karas Vanderbilt University, Yifan Zhang Vanderbilt University, Yu Huang Vanderbilt University, Toby Jia-Jun Li University of Notre Dame, Collin McMillan University of Notre Dame | ||
15:42 12mTalk | On Automated Assistants for Software Development: The Role of LLMs NIER Track Pre-print File Attached | ||
15:54 12mTalk | SmartBugs 2.0: An Execution Framework for Weakness Detection in Ethereum Smart Contracts Tool Demonstrations Monika di Angelo TU Wien, Thomas Durieux TU Delft, João F. Ferreira INESC-ID and IST, University of Lisbon, Gernot Salzer TU Wien Pre-print File Attached | ||
16:06 12mTalk | AutoLog: A Log Sequence Synthesis Framework for Anomaly Detection Research Papers Yintong Huo The Chinese University of Hong Kong, Yichen LI The Chinese University of Hong Kong, Yuxin Su Sun Yat-sen University, Pinjia He Chinese University of Hong Kong, Shenzhen, Zifan Xie Huazhong University of Science and Technology, Michael Lyu The Chinese University of Hong Kong Pre-print | ||
16:18 12mTalk | Aster: Automatic Speech Recognition System Accessibility Testing for Stutterers Research Papers Yi Liu Nanyang Technological University, Yuekang Li University of New South Wales, Gelei Deng Nanyang Technological University, Felix Juefei-Xu Meta AI, Yao Du University of California, Irvine, Cen Zhang Nanyang Technological University, Chengwei Liu Nanyang Technological University, Yeting Li Institute of Information Engineering at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Lei Ma University of Alberta, Yang Liu Nanyang Technological University, Yuekang Li University of New South Wales | ||
16:30 12mTalk | Software Entity Recognition with Noise-Robust LearningRecorded talk Research Papers Tai Nguyen University of Pennsylvania, Yifeng Di Purdue University, Joohan Lee University of Southern California, Muhao Chen University of Southern California, Tianyi Zhang Purdue University Pre-print Media Attached File Attached | ||