AUTOMATED METHOD FOR VERIFYING THE CORRECTNESS OF THE EXECUTION OF SMART CONTRACTS IN THE BLOCKCHAIN NETWORK

DOI: 10.31673/2409-7292.2025.041204

Abstract

The article examines an automated method for verifying the correctness of smart contracts in the Solana blockchain
network. The relevance of the research is driven by the growing popularity of Web3 applications and the need to ensure
their security, as even minor errors in smart contract code can lead to significant financial losses. The primary goal is to
develop an automated verification methodology for smart contracts that can detect vulnerabilities such as the absence of
founder rights verification, arithmetic operation errors, and missing transaction check signatures. Using static analysis
techniques in the Rust programming language, the authors propose an approach that enables rapid analysis-taking less
than three minutes per contract-and automatic generation of reports on identified vulnerabilities. The methodology is
based on analyzing external data flows through smart contracts, allowing for the early detection of potential threats. To
automate the process, Python and Bash scripts are employed, integrating with cloud services such as Amazon Web
Services to scale the analysis. Testing results on real Web3 applications demonstrate the effectiveness of the methodology,
particularly in reducing analysis time and improving the accuracy of error detection. An important aspect of the research
is the continuous updating of knowledge bases and analysis tools, enabling the consideration of new types of attacks and
vulnerabilities. The article also highlights the importance of interoperability between different blockchain networks,
which remains a challenging task but is a key element for the future development of Web3. The research results show
that the proposed methodology is promising for scaling and adapting to new challenges in blockchain ecosystems such
as Solana. Thus, the developed approach to automated smart contract verification not only enhances the security of Web3
applications but also contributes to their further development, ensuring stability and reliability in the dynamic evolution
of blockchain technologies.
Keywords: blockchain, smart contract, Solana, information system, Rust, automated verification, optimization,
security, decentralization.

References
1. Tao, Bishenghui, Ivan Wang-Hei Ho, and Hong-Ning Dai. Complex network analysis of the bitcoin blockchain
network. In: 2021 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2021. p. 1-5.
https://ira.lib.polyu.edu.hk/bitstream/10397/107099/1/Ho_Complex_Network_Analysis.pdf.
2. Cho, Seong-Hwan. (2018). A study on analysis of the trend of blockchain by key words network analysis. The
Journal of Korea Institute of Information, Electronics, and Communication Technology, 11(5), 550-555.
https://arxiv.org/pdf/2011.09318.
3. Wu, J., Liu, J., Zhao, Y., & Zheng, Z. (2021). Analysis of cryptocurrency transactions from a network
perspective: An overview. Journal of Network and Computer Applications, 190, 103139.
4. Scherer, Mattias. "Performance and scalability of blockchain networks and smart contracts." (2017).
https://www.diva-portal.org/smash/get/diva2:1111497/fulltext01.pdf.
5. Gervais, A., Karame, G. O., Wüst, K., Glykantzis, V., Ritzdorf, H., & Capkun, S. (2016, October). On the
security and performance of proof of work blockchains. In Proceedings of the 2016 ACM SIGSAC conference on
computer and communications security (pp. 3-16). https://eprint.iacr.org/2016/555.pdf.
6. Sriman, B., Ganesh Kumar, S., Shamili, P. (2021). Blockchain technology: Consensus protocol proof of work
and proof of stake. In Intelligent Computing and Applications: Proceedings of ICICA 2019 (pp. 395-406). Springer
Singapore. https://doi.org/10.1007/978-981-15-5566-4_34.
7. R. P. George, B. L. Peterson, O. Yaros, D. L. Beam, J. M. Dibbell, and R. C. Moore, “Blockchain for business,”
Journal of Investment Compliance, vol. 20, no. 1, pp. 17–21, 2019, doi: 10.1108/joic-01-2019-0001.
8. S. Hemang, “Security tokens: architecture, smart contract applications and illustrations using SAFE,”
Managerial Finance, vol. ahead-of-p, no. ahead-of-print. Jan. 01, 2019, doi: 10.1108/MF-09-2018-0467.
9. Pierro, G. A., & Tonelli, R. (2022, March). Can solana be the solution to the blockchain scalability problem?.
In 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) (pp. 1219-1226).
IEEE. DOI: 10.1109/SANER53432.2022.00144.
10. T. Feng, X. Yu, Y. Chai, and Y. Liu, “Smart contract model for complex reality transaction,” International
Journal of Crowd Science, vol. 3, no. 2, pp. 184–197, 2019, doi: 10.1108/ijcs-03-2019-0010.
11. Yakovenko, A. (2018). Solana: A new architecture for a high performance blockchain v0. 8.13.
https://coincode-live.github.io/static/whitepaper/source001/10608577.pdf.
12. GAN, Chian Min, et al. ConfMan Web 3.0: Decentralized Academic Conference Management System with
Rust and Web 3.0. In: 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE,
2025. p. 1746-1751. doi: 10.1109/COMPSAC65507.2025.00237.
13. Kolyda, Y., Poznyak, S., Babii, N., & Zhurakovskyi, B. (2025). Adaptive Model of Economic Development
with an Open Market.28-50 рр. https://ceur-ws.org/Vol-4029/paper3.pdf.
14. Huang, Renke, et al. "An overview of Web3 technology: Infrastructure, applications, and
popularity." Blockchain: Research and Applications 5.1 (2024): 100173. https://doi.org/10.1016/j.bcra.2023.100173.