Automated Test Generation For Smart Contracts via On-Chain Test Case Augmentation and Migration
Blockchain
Pre-deployment testing has become essential to ensure the functional correctness of smart contracts. However, since smart contracts are stateful programs integrating many different functionalities, manually writing test cases to cover all potential usages requires significant effort from developers, leading to insufficient testing and increasing risks in practice. Although several testing techniques for smart contracts have been proposed, they primarily focus on detecting common low-level vulnerabilities such as re-entrancy, rather than generating expressive and function-relevant test cases that can reduce manual testing efforts. To bridge the gap, we propose SolMigrator, an automated technique designed to generate expressive and representative test cases for smart contracts. To our knowledge, SolMigrator is the first migration-based test generation technique for smart contracts, which extracts test cases from real-world usages of on-chain contracts and migrates them to test newly developed smart contracts with similar functionalities. Given a target smart contract to be tested and an on-chain similar source smart contract, SolMigrator first transforms the on-chain usage of the source contract into off-chain executable test cases based on on-chain transaction replay and dependency analysis. It then employs fine-grained static analysis to migrate the augmented test cases from the source to the target smart contract. We built a prototype of SolMigrator and have evaluated it on real-world smart contracts within the two most popular categories, ERC20 and ERC721. Our evaluation results demonstrate that SolMigrator effectively extracts test cases from existing on-chain smart contracts and accurately migrates them across different smart contracts, achieving an average precision of 96.3% and accuracy of 93.6%. Furthermore, the results indicate that these migrated test cases effectively cover common key functionalities of the target smart contracts. This provides promising evidence that real-world usages of existing smart contracts can be transformed into effective test cases for other newly developed smart contracts.
Fri 2 MayDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:30 | Program Comprehension 3Research Track / Journal-first Papers at 204 Chair(s): Arie van Deursen TU Delft | ||
11:00 15mTalk | Automated Test Generation For Smart Contracts via On-Chain Test Case Augmentation and MigrationBlockchain Research Track Jiashuo Zhang Peking University, China, Jiachi Chen Sun Yat-sen University, John Grundy Monash University, Jianbo Gao Peking University, Yanlin Wang Sun Yat-sen University, Ting Chen University of Electronic Science and Technology of China, Zhi Guan Peking University, Zhong Chen Pre-print | ||
11:15 15mTalk | Boosting Code-line-level Defect Prediction with Spectrum Information and Causality Analysis Research Track Shiyu Sun , Yanhui Li Nanjing University, Lin Chen Nanjing University, Yuming Zhou Nanjing University, Jianhua Zhao Nanjing University, China | ||
11:30 15mTalk | BatFix: Repairing language model-based transpilation Journal-first Papers Daniel Ramos Carnegie Mellon University, Ines Lynce INESC-ID/IST, Universidade de Lisboa, Vasco Manquinho INESC-ID; Universidade de Lisboa, Ruben Martins Carnegie Mellon University, Claire Le Goues Carnegie Mellon University | ||
11:45 15mTalk | Tracking the Evolution of Static Code Warnings: The State-of-the-Art and a Better Approach Journal-first Papers | ||
12:00 15mTalk | PACE: A Program Analysis Framework for Continuous Performance Prediction Journal-first Papers | ||
12:15 15mTalk | Mimicking Production Behavior With Generated Mocks Journal-first Papers Deepika Tiwari KTH Royal Institute of Technology, Martin Monperrus KTH Royal Institute of Technology, Benoit Baudry Université de Montréal | ||