Blockly2Hooks: Smart Contracts for Everyone with the XRP Ledger and Google Blockly

• URL: http://arxiv.org/abs/2511.08403v1
• Date: Wed, 12 Nov 2025 01:57:32 GMT
• Title: Blockly2Hooks: Smart Contracts for Everyone with the XRP Ledger and Google Blockly
• Authors: Lucian Trestioreanu, Wazen Shbair, Flaviene Scheidt de Cristo, Radu State,
• Abstract summary: Due to increasing demand, smart contracts could soon face a shortage of knowledgeable users and tools to handle them in practice.<n>Because of a steep learning curve, the handling of smart contracts is currently performed by specialised developers mainly.<n>In this paper we designed, developed and tested Blockly2Hooks, a solution towards filling this gap even in challenging scenarios.
• Score: 0.7933039558471408
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent technologies such as inter-ledger payments, non-fungible tokens, and smart contracts are all fruited from the ongoing development of Distributed Ledger Technologies. The foreseen trend is that they will play an increasingly visible role in daily life, which will have to be backed by appropriate operational resources. For example, due to increasing demand, smart contracts could soon face a shortage of knowledgeable users and tools to handle them in practice. Widespread smart contract adoption is currently limited by security, usability and costs aspects. Because of a steep learning curve, the handling of smart contracts is currently performed by specialised developers mainly, and most of the research effort is focusing on smart contract security, while other aspects like usability being somewhat neglected. Specific tools would lower the entry barrier, enabling interested non-experts to create smart contracts. In this paper we designed, developed and tested Blockly2Hooks, a solution towards filling this gap even in challenging scenarios such as when the smart contracts are written in an advanced language like C. With the XRP Ledger as a concrete working case, Blockly2Hooks helps interested non-experts from the community to learn smart contracts easily and adopt the technology, through leveraging well-proven teaching methodologies like Visual Programming Languages, and more specifically, the Blockly Visual Programming library from Google. The platform was developed and tested and the results are promising to make learning smart contract development smoother.

Related papers

• Trace: Securing Smart Contract Repository Against Access Control Vulnerability [58.02691083789239]
  GitHub hosts numerous smart contract repositories containing source code, documentation, and configuration files.<n>Third-party developers often reference, reuse, or fork code from these repositories during custom development.<n>Existing tools for detecting smart contract vulnerabilities are limited in their ability to handle complex repositories.
  arXiv  Detail & Related papers  (2025-10-22T05:18:28Z)
• Ai-Driven Vulnerability Analysis in Smart Contracts: Trends, Challenges and Future Directions [0.2797210504706914]
  Vulnerabilities such as numerical overflows, reentrancy attacks, and improper access permissions have led to the loss of millions of dollars.<n>Traditional smart contract auditing techniques face limitations in scalability, automation, and adaptability to evolving development patterns.<n>This paper examines novel AI-driven techniques for vulnerability detection in smart contracts, focusing on machine learning, deep learning, graph neural networks, and transformer-based models.
  arXiv  Detail & Related papers  (2025-06-07T09:44:26Z)
• Smart Contracts for SMEs and Large Companies [0.0]
  We show how the approach is used to support collaborations via smart contracts for companies ranging from SMEs with little IT capabilities to companies with IT using blockchain smart contracts.<n>We also show how the approach is used for certain applications to generate smart contracts by a BPMN modeler who does not need any knowledge of blockchain technology or smart contract development.
  arXiv  Detail & Related papers  (2025-05-28T17:40:21Z)
• Versioned Analysis of Software Quality Indicators and Self-admitted Technical Debt in Ethereum Smart Contracts with Ethstractor [2.052808596154225]
  This paper proposes Ethstractor, the first smart contract collection tool for gathering a dataset of versioned smart contracts. The collected dataset is then used to evaluate the reliability of code metrics as indicators of vulnerabilities in smart contracts.
  arXiv  Detail & Related papers  (2024-07-22T18:27:29Z)
• Contractual Reinforcement Learning: Pulling Arms with Invisible Hands [68.77645200579181]
  We propose a theoretical framework for aligning economic interests of different stakeholders in the online learning problems through contract design. For the planning problem, we design an efficient dynamic programming algorithm to determine the optimal contracts against the far-sighted agent. For the learning problem, we introduce a generic design of no-regret learning algorithms to untangle the challenges from robust design of contracts to the balance of exploration and exploitation.
  arXiv  Detail & Related papers  (2024-07-01T16:53:00Z)
• Vulnerabilities of smart contracts and mitigation schemes: A Comprehensive Survey [0.6554326244334866]
  This paper presents a literature review combined with an experimental report that aims to assist developers in developing secure smarts. It provides a list of frequent vulnerabilities and corresponding mitigation solutions. It evaluates the community most widely used tools by executing and testing them on sample smart contracts.
  arXiv  Detail & Related papers  (2024-03-28T19:36:53Z)
• Formally Verifying a Real World Smart Contract [52.30656867727018]
  We search for a tool capable of formally verifying a real-world smart contract written in a recent version of Solidity. In this article, we present our search for a tool capable of formally verifying a real-world smart contract written in a recent version of Solidity.
  arXiv  Detail & Related papers  (2023-07-05T14:30:21Z)
• Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions [54.55334589363247]
  We study whether conveying information about uncertainty enables programmers to more quickly and accurately produce code. We find that highlighting tokens with the highest predicted likelihood of being edited leads to faster task completion and more targeted edits.
  arXiv  Detail & Related papers  (2023-02-14T18:43:34Z)
• An Empirical Study on Real Bug Fixes from Solidity Smart Contract Projects [37.39791127265096]
  We conduct an empirical study on historical bug fixes from 46 real-world Solidity smart contract projects. We distill four findings during the process to explore these four questions. We provide actionable implications to improve the current approaches to fixing bugs in Solidity smart contracts.
  arXiv  Detail & Related papers  (2022-10-21T14:26:53Z)
• Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion [48.744359070088166]
  Conventional smart contract vulnerability detection methods heavily rely on fixed expert rules. Recent deep learning approaches alleviate this issue but fail to encode useful expert knowledge. We develop automatic tools to extract expert patterns from the source code. We then cast the code into a semantic graph to extract deep graph features.
  arXiv  Detail & Related papers  (2021-06-17T07:12:13Z)
• ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learning [80.85273827468063]
  Existing machine learning-based vulnerability detection methods are limited and only inspect whether the smart contract is vulnerable. We propose ESCORT, the first Deep Neural Network (DNN)-based vulnerability detection framework for smart contracts. We show that ESCORT achieves an average F1-score of 95% on six vulnerability types and the detection time is 0.02 seconds per contract.
  arXiv  Detail & Related papers  (2021-03-23T15:04:44Z)
• Blockchain Enabled Smart Contract Based Applications: Deficiencies with the Software Development Life Cycle Models [0.0]
  The immutability of the blocks, where the smart contracts are stored, causes conflicts with the traditional Software Development Life Cycle (SDLC) models. This research article addresses this current problem by first exploring the six traditional SDLC models. It advocates that there is an urgent need to develop new standard model(s) to address the arising issues.
  arXiv  Detail & Related papers  (2020-01-21T03:48:46Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.