OpenTracer: A Dynamic Transaction Trace Analyzer for Smart Contract Invariant Generation and Beyond

Zhiyang Chen, Ye Liu, Sidi Mohamed Beillahi, Yi Li, and Fan Long

In Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2024

Abstract: Smart contracts, self-executing programs on the blockchain, facilitate reliable value exchanges without centralized oversight. Despite the recent focus on dynamic analysis of their transaction histories in both industry and academia, no open-source tool currently offers comprehensive tracking of complete transaction information to extract user-desired data such as invariant-related data. This paper introduces OpenTracer, designed to address this gap. OpenTracer guarantees comprehensive tracking of every execution step, providing complete transaction information. OpenTracer has been employed to analyze 350,800 Ethereum transactions, successfully inferring 23 different types of invariant from predefined templates. The tool is fully open-sourced, serving as a valuable resource for developers and researchers aiming to extract or validate new invariants from transaction traces. A demonstration video of OpenTracer is available at https://youtu.be/vTdmjWdYd30. The source code of OpenTracer is available at https://github.com/jeffchen006/OpenTracer.

Cite:

@inproceedings{Chen2024OAD,
  author = {Chen, Zhiyang and Liu, Ye and Beillahi, Sidi Mohamed and Li, Yi and Long, Fan},
  booktitle = {Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering (ASE)},
  month = oct,
  title = {{OpenTracer}: A Dynamic Transaction Trace Analyzer for Smart Contract Invariant Generation and Beyond},
  year = {2024}
}