Auto-generation of Smart Contracts from a Domain-Specific XML-Based Language

Dwivedi, Vimal; Norta, Alex

doi:10.1007/978-981-16-6624-7_54

Cited by 9 publications

(3 citation statements)

References 23 publications

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“…In addition to the proposed structured approaches, numerous less broad proposals exist that do not cover the entirety of SDLC but try to incorporate different existing notations for modeling the smart contract structure and behavior. The proposals encompass the usage of UML class diagrams [31], [32], UML sequence diagrams [29], UML state diagrams [20], UML deployment diagram [33], finite state machines (FSM) [28], BPMN [30], [34], [35], and even custom domain specific languages (DSL) [36]- [38] in smart contract development. In our research, we focus on transformation from models to smart contract code, and for this reason, we have analyzed in more detail several of the aforementioned proposals [30], [34], [35], [37], [39] that place a heavier focus on the usage of models for smart contract code generation purposes.…”

Section: Related Workmentioning

confidence: 99%

Solidity Code Generation From UML State Machines in Model-Driven Smart Contract Development

2022

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For the development of blockchain smart contracts, a structured approach based on the principles of the Model Driven Architecture can be beneficial and facilitate the implementation of smart contracts. This paper presents such an approach, which, in combination with Unified Modeling Language (UML) Class and State machine diagrams, allows the smart contract structure and behavior logic to be modeled in several abstraction layers. This paper delves into details on how the model-to-model transformations from the specified Blockchain Platform Independent Model (PIM) with specified state-like behavior can be used to produce a Solidity Platform Specific Model (PSM). Subsequently, we elaborate on how the Solidity PSM is used for Solidity smart contract code generation by employing model-to-text transformations. The paper also demonstrates the process of our proposed transformations and code generation using smart contract code examples from Solidity documentation. Based on the examples, a Blockchain PIM is specified and transformed to Solidity PSM, which is then used for Solidity smart contract code generation. The generated smart contract code is then compiled, deployed on the Ethereum blockchain JavaScript virtual machine, and compared to the original smart contract code in terms of Solidity code metrics, similarity scores, and execution costs. The evaluation results indicate that our approach could be successfully used to model and later generate smart contract code.INDEX TERMS Blockchain, model driven architecture, model-driven development, smart contracts, solidity, state machine, unified modeling language.

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Section: Related Workmentioning

confidence: 99%

Solidity Code Generation From UML State Machines in Model-Driven Smart Contract Development

2022

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“…At present, most research stays in the direction of security problem detection, ignoring the problem of smart contract development efficiency, and less research on the programming friendliness of smart contracts. Some researchers [4][5][6] use traditional neural networks such as RNN and XML language conversion of solidity language to achieve smart contract code generation, but there are still problems such as insecurity of generating smart contracts and insufficient code semantic comprehension ability. In the case of high demand for smart contracts, these methods can no longer meet the needs of current application scenarios.…”

Section: Introductionmentioning

confidence: 99%

Smart contract generation model based on code annotation and AST-LSTM tuning

Yong,

Defeng,

Chao

et al. 2024

Preprint

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With the wide application of smart contracts in many fields, the number, types, and complexity of smart contracts are showing a rapidly increasing trend. However , the development of smart contracts has its own unique programming language and security requirements, which are difficult for conventional software personnel to adapt to quickly, and how to realize the efficient development of smart contracts according to the application requirements is an important issue that needs to be solved for its further development. To this end, this paper proposes a smart contract generation method based on AST-LSTM characterization and code annotation tuning large language model, which adopts AST-LSTM model combining Abstract Syntax Tree (AST) and Tree-LSTM to vectorize the code as well as Sentence-Bert to vectorize the annotations and carry out a weighted analysis, and constructs a smart contract clustering analysis model to achieve accurate clustering of functionally similar smart contracts. Then the AST-LSTM+Transformer model is used to detect defects in the clustered code and correlate the related annotation information to construct a diverse Prompt feature prompt statement dataset. Finally, the LLaMA2-7B model is used as the basis for demand-specific smart contract generation with the help of Lora and P-Tuning v2 fine-tuning techniques. In this paper, with the help of BLEU, an auxiliary tool for bilingual translation quality assessment, and Mythril, VaaS, 1 and other code security detection tools, we conducted comparative experiments with existing methods. The results of the experiment show that the average value of BLEU of the code generated by this paper’s method is improved by about 25%, and the code security is improved by about 9%, which will greatly promote the rapid development and exploitation of smart contracts with high-security requirements.

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“…Since SCs are interdisciplinary in nature, different practitioners, such as lawyers, computer engineers, business and finance experts, and others from different fields, can collaborate to design, propose, and implement SCs [5]. At present, the mainstream method used to write SCs is technology-related.…”

Section: Introductionmentioning

confidence: 99%

A Reuse-Oriented Visual Smart Contract Code Generator for Efficient Development of Complex Multi-Party Interaction Scenarios

Shen

et al. 2023

Applied Sciences

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Multi-party interaction scenarios usually involve interaction and collaboration between multiple participants, such as business negotiation, teamwork, etc. In multi-party interaction scenarios, trust mechanisms are needed to ensure the use of rights and the fulfillment of obligations. The use of blockchain and smart contracts to establish a decentralized trust mechanism is a solution. The development process of smart contracts may require experts in different fields to design them together, and it is difficult for non-experts to understand smart contract code. The traditional method of smart contract development is for the developer to manually write the smart contract code, which may lead to low development efficiency and the inability of the scene participants to understand the smart contract code. To address this challenge, we propose a reuse-oriented visual smart contract generator to efficiently develop complex multi-party interaction scenarios. This paper proposes a model based on BPMN that uses smart contracts to express the process of multi-party interaction so that the parties in various domains understand the business requirements. Then, a multi-layer reusable library is proposed and used to generate a visual solidity code. We also integrate code compilation, security checking, and deployment into the target blockchain environment for testing. The function of the tool is verified in the case of flight delay insurance, which shows that it can aid the automated development of smart contracts for multi-party interaction scenarios. At the same time, the feasibility of the tool is verified by five cases selected from the literature, which shows that it can aid the development of smart contracts to achieve a high degree of reusability.

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Auto-generation of Smart Contracts from a Domain-Specific XML-Based Language

Cited by 9 publications

References 23 publications

Solidity Code Generation From UML State Machines in Model-Driven Smart Contract Development

Solidity Code Generation From UML State Machines in Model-Driven Smart Contract Development

Smart contract generation model based on code annotation and AST-LSTM tuning

A Reuse-Oriented Visual Smart Contract Code Generator for Efficient Development of Complex Multi-Party Interaction Scenarios

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