smart contract development

Blockchain decentralization and security critically depend on rigorous formal verification; however, existing approaches lack cross-layer, end-to-end automated reasoning capabilities. To address this, we establish, for the first time, a systematic formal theoretical foundation for automated blockchain reasoning, introducing a novel cross-layer verification paradigm that unifies cryptographic primitives, consensus protocols, and smart contract logic. Methodologically, we integrate interactive theorem proving (Coq/Isabelle), model checking, SMT solving, and lightweight intermediate representation (IR) modeling to achieve full-stack verifiability—from low-level cryptographic assumptions to high-level DApp business logic. Evaluation on PBFT and HotStuff consensus protocols, as well as EVM- and Solana-based smart contracts, demonstrates a 42% improvement in vulnerability detection rate and a 5.8× speedup in verification efficiency. Our framework significantly enhances the reliability and security of blockchain systems in multi-stakeholder domains, including healthcare, supply chain, and IoT.

This study addresses the technical auditing challenges posed by blockchain assets and custody mechanisms, which disrupt traditional financial audit paradigms—particularly concerning asset existence, ownership verification, valuation, and internal control validation. For the first time, autoethnography is introduced into blockchain auditing, drawing on the author’s multifaceted experience as a blockchain engineer, smart contract auditor, and CTO of a crypto-asset firm to uncover nuanced technical details inaccessible to external observers. Focusing on representative scenarios such as airdropped tokens, multi-signature smart contracts, and real-time on-chain reporting, the work constructs an audit analysis framework tailored to emerging on-chain practices and proposes reusable, experimental audit pathways that effectively tackle challenges currently deemed technically insurmountable.

To address the challenges of insufficient transaction security and high compliance costs in corporate contract enforcement, this paper proposes a blockchain-based framework for corporate contract state synchronization and certification. Methodologically, it pioneers modeling contract states as synchronized, verifiable on-chain state machines, integrating consensus mechanisms, verifiable state registration smart contracts, on-chain audit query interfaces, and DID-bound contract invocation protocols—thereby enabling governance rule codification and cross-entity real-time state consistency. The key contributions are: (1) the first comprehensive on-chain state architecture supporting automated registration, verification, and traceability across the entire contract lifecycle; and (2) empirical validation demonstrating an average 2% reduction in contract reconciliation discrepancies, alongside significant decreases in manual verification effort and dispute incidence.

TON smart contracts face unique security challenges—including asynchronous message passing and a multi-layered architecture—yet lack audit methodologies tailored to their execution model. This paper systematically analyzes 233 real-world vulnerabilities extracted from 34 professional audit reports, thereby establishing the first comprehensive, structured auditing framework and standardized checklist specifically designed for the TON ecosystem. The framework is explicitly aligned with TON’s asynchronous execution semantics, bridging the practical gap between mature Ethereum auditing methodologies and the emerging TON platform. Through mixed-method (qualitative and quantitative) case studies, we identify high-risk anti-patterns—such as message reentrancy and cross-contract state inconsistency—and distill actionable, rule-based security checks. Our contributions significantly enhance developers’ and auditors’ ability to detect and remediate prevalent TON-specific vulnerabilities, thereby improving the security and reliability of TON-based applications.

Smart contracts exhibit extremely low fault tolerance due to code immutability, and existing formal verification approaches suffer from limitations in semantic expressiveness and reasoning capability for specification modeling. Method: Through a systematic literature review, this work integrates model checking, theorem proving, and static analysis, and—novelty—introduces description logic (DL) into smart contract formal verification for the first time. It constructs a new verification framework that combines strong semantic expressiveness with decidable reasoning support, and proposes a cross-tool, cross-platform verification methodology. A taxonomy-based evaluation framework for mainstream verification tools is also established. Contribution/Results: Comparative experiments demonstrate that DL significantly improves the accuracy, scalability, and automation potential of specification modeling. The framework establishes a new paradigm for high-assurance smart contract development, enabling more rigorous, interoperable, and practically deployable verification workflows.

Current DevOps infrastructures for blockchain applications are predominantly controlled by single entities, lacking decentralized deployment and governance mechanisms. This work proposes a decentralized deployment architecture decoupled from specific governance and upgrade schemes, integrating DAO-based governance, smart contract upgradability, and DevOps best practices. By adopting an extended registry pattern, the architecture enables deterministic deployments and, for the first time, incorporates version control, testing and validation, and user interface components into a unified decentralized framework. The project provides an open-source reference implementation that substantially lowers the barrier to practical decentralized deployment. Experimental evaluation demonstrates the effectiveness and practicality of the proposed architecture.

This study addresses a critical gap in blockchain research, which has predominantly focused on on-chain transactions while neglecting the comprehensive lifecycle management of cryptographic assets. For the first time, the paper introduces the ISO 15489-1:2016 records management standard into the blockchain domain, leveraging records lifecycle theory to propose a seven-stage data lifecycle framework spanning from creation to disposition. The applicability of this model is demonstrated through case studies involving Bitcoin, fungible tokens, and non-fungible tokens. By elucidating the inherent characteristics of blockchain as a records management system, the framework clarifies the boundaries between on-chain and off-chain data and examines how privacy-enhancing technologies affect lifecycle visibility. This structured perspective offers valuable insights for the governance of crypto-assets, regulatory compliance, and forensic investigations.

This work addresses the challenge of formally modeling and verifying high-level coordination logic in smart contracts within decentralized systems. It proposes a formal method based on coordination models that supports dynamic roles, data-driven state transitions, and external coordination interfaces. For the first time, this approach integrates formal coordination models with automated code generation and test case synthesis for smart contracts, yielding a platform-agnostic toolchain extensible to multiple contract languages. The expressiveness and engineering practicality of the method are demonstrated through the modeling and implementation of several representative coordination patterns.

This study addresses the vulnerability of high-accuracy fraud detection models in enterprise settings, where insiders may tamper with logs or bypass approval workflows, thereby compromising audit integrity. To counter this, the authors propose a tamper-proof AI auditing system that uniquely leverages blockchain as an active enforcement layer. By anchoring explainable machine learning predictions and approval workflows atomically to a Layer-2 chain (e.g., Polygon) via smart contracts, the system ensures end-to-end immutability, verifiability, and compliance with GDPR. Empirical evaluation demonstrates strong performance: an F1 score of 0.895, a PR-AUC of 0.974, inference latency under 25 milliseconds, transaction costs below \$0.01 per operation, and scalability to support tens of thousands of monthly payments.

Existing approaches struggle to effectively audit the complex semantic logic and multi-contract dependencies inherent in cross-chain smart contracts, leading to numerous security vulnerabilities stemming from implementation flaws. This work proposes the Graph of Auditing Thoughts (GAT), which explicitly models expert auditors’ reasoning processes as a graph structure for the first time. By integrating static data-flow analysis with large language model–based semantic reasoning, GAT dynamically explores attack paths within a constrained search space, enabling logic-driven, fine-grained security verification. Evaluated on a standard benchmark, the method achieves a 92% recall rate for audit points and 95% coverage of vulnerable projects, while practically identifying 117 confirmed risks—demonstrating high precision and low computational overhead.