Rob McLaughlin, Nir Chemaya, Dingyue Liu, Dahlia Malkhi
This paper introduces a trade ordering rule that aims to reduce intra-block price volatility in Automated Market Maker (AMM) powered decentralized exchanges. The ordering rule introduced here, Clever Look-ahead Volatility Reduction (CLVR), operates under the (common) framework in decentralized finance that allows some entities to observe trade requests before they are settled, assemble them into "blocks", and order them as they like. On AMM exchanges, asset prices are continuously and transparently updated as a result of each trade and therefore, transaction order has high financial value. CLVR aims to order transactions for traders' benefit. Our primary focus is intra-block price stability (minimizing volatility), which has two main benefits for traders: it reduces transaction failure rate and allows traders to receive closer prices to the reference price at which they submit their transactions accordingly. We show that CLVR constructs an ordering which approximately minimizes price volatility with a small computation cost and can be trivially verified externally.
Groundhog is a novel design for a smart contract execution engine based around concurrent execution of blocks of transactions. Unlike prior work, transactions within a block in Groundhog are not ordered relative to one another. Instead, our key design insights are first, to design a set of commutative semantics that lets the Groundhog runtime deterministically resolve concurrent accesses to shared data. Second, some storage accesses (such as withdrawing money from an account) conflict irresolvably; Groundhog therefore enforces validity constraints on persistent storage accesses via a reserve-commit process. These two ideas give Groundhog a set of semantics that, while not as powerful as traditional sequential semantics, are flexible enough to implement a wide variety of important applications, and are strictly more powerful than the semantics used in some production blockchains today. Unlike prior smart contract systems, transactions throughput never suffers from contention between transactions. Using 96 CPU cores, Groundhog can process more than half a million payment transactions per second, whether between 10M accounts or just 2.
Stuart Harshbarger, Rosa Heckle, Michael P. Collins
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Christian Ziegler, Marcos Luiz Cavalcanti de Miranda, Guangye Cao, Gustav Arentoft · 5 authors
Our study demonstrates the effective use of Large Language Models (LLMs) for automating the classification of complex datasets. We specifically target proposals of Decentralized Autonomous Organizations (DAOs), as the clas-sification of this data requires the understanding of context and, therefore, depends on human expertise, leading to high costs associated with the task. The study applies an iterative approach to specify categories and further re-fine them and the prompt in each iteration, which led to an accuracy rate of 95% in classifying a set of 100 proposals. With this, we demonstrate the po-tential of LLMs to automate data labeling tasks that depend on textual con-text effectively.
In recent years, particularly with the Ethereum blockchain’s advent, smart contracts have gained significant interest as a means of regulating exchanges among multiple parties via code. This surge has prompted the emergence of various smart contract (SC) programming languages, each possessing distinct philosophies, grammatical structures, and components. Conse-quently, developers are increasingly involved in SC programming. However, these languages are platform specific, implying that a transition to another platform necessitates the use of different languages. Additionally, developers require a certain level of control over SCs to address encountered bugs and ensure maintenance. To address these developer-centric challenges, this paper presents SCEditor, a novel Eclipse Sirius-based prototype editor designed for the visualization, design, and creation of SCs. The editor proposes a means of standardizing the usage of SC programming languages through the incorporation of graphical syntax and a metamodel conforming to Model-Driven Engineering (MDE) principles and SC construction rules to generate an abstract SC model. The efficacy of this editor is demonstrated through testing on a voting SC written in Vyper and Solidity languages. Furthermore, the editor holds potential for future exploitation in model transformation and code generation for various SC languages.
This article explores the concept of autopoiesis and its application to Decentralized Autonomous Organizations (DAOs). Autopoiesis describes the self-producing and self-maintaining characteristics of living systems, a concept that has been applied in various fields beyond biology. DAOs, operating on blockchain technology, exhibit a level of autonomy, transparency, and democratic governance. They are self-governing and self-sustaining systems that operate based on coded rules and protocols. The article suggests that DAOs align with the concept of autopoiesis, making them a specific type of complex system. Diverse case studies demonstrate the resilience and autopoietic features of these organizations. All things considered, the concept of autopoiesis could provide a valuable lens for understanding DAOs.
Distributed argumentation technology is a computational approach incorporating argumentation reasoning mechanisms within multi-agent systems. For the formal foundations of distributed argumentation technology, in this thesis, we conduct a principle-based analysis of structured argumentation as well as abstract multi-agent and abstract bipolar argumentation. The results of the principle-based approach of these theories provide an overview and guideline for further applications of the theories. Moreover, in this thesis we explore distributed argumentation technology using distributed ledgers. We envision an Intelligent Human-input-based Blockchain Oracle (IHiBO), an artificial intelligence tool for storing argumentation reasoning. We propose a decentralized and secure architecture for conducting decision-making, addressing key concerns of trust, transparency, and immutability. We model fund management with agent argumentation in IHiBO and analyze its compliance with European fund management legal frameworks. We illustrate how bipolar argumentation balances pros and cons in legal reasoning in a legal divorce case, and how the strength of arguments in natural language can be represented in structured arguments. Finally, we discuss how distributed argumentation technology can be used to advance risk management, regulatory compliance of distributed ledgers for financial securities, and dialogue techniques.
Attention-Aware Social Choice tackles the fundamental conflict faced by some agent communities between their desire to include all members in the decision making processes and the limited time and attention that are at the disposal of the community members. Here, we investigate a combination of two techniques for attention-aware social choice, namely Natural Language Processing (NLP) and Sampling. Essentially, we propose a system in which each governance proposal to change the status quo is first sent to a trained NLP model that estimates the probability that the proposal would pass if all community members directly vote on it; then, based on such an estimation, a population sample of a certain size is being selected and the proposal is decided upon by taking the sample majority. We develop several concrete algorithms following the scheme described above and evaluate them using various data, including such from several Decentralized Autonomous Organizations (DAOs).
Ilham Qasse, Shailesh Mishra, Björn Þór Jónsson, Foutse Khomh · 5 authors
The potential of automatic code generation through Model-Driven Engineering (MDE) frameworks has yet to be realized. Beyond their ability to help software professionals write more accurate, reusable code, MDE frameworks could make programming accessible for a new class of domain experts. However, domain experts have been slow to embrace these tools, as they still need to learn how to specify their applications' requirements using the concrete syntax (i.e., textual or graphical) of the new and unified domain-specific language. Conversational interfaces (chatbots) could smooth the learning process and offer a more interactive way for domain experts to specify their application requirements and generate the desired code. If integrated with MDE frameworks, chatbots may offer domain experts with richer domain vocabulary without sacrificing the power of agnosticism that unified modelling frameworks provide. In this paper, we discuss the challenges of integrating chatbots within MDE frameworks and then examine a specific application: the auto-generation of smart contract code based on conversational syntax. We demonstrate how this can be done and evaluate our approach by conducting a user experience survey to assess the usability and functionality of the chatbot framework. The paper concludes by drawing attention to the potential benefits of leveraging Language Models (LLMs) in this context.
A smart contract is a translation of a standard paper-based contract that can be enforced and executed by a contract management system. At a high level of abstraction, a contract is only a document that describes how the signing parties are to behave in different scenarios; nevertheless, the translation of a typical paper-based contract to its electronic counterpart has proved to be both time-consuming and difficult. The requirement for a language capable of capturing the core of a contract in simple phrases and definitions has been a focus of study for many years. EROP (Events, Rights, Obligations, Prohibitions) is a contract specification language that breaks a contract down into sets of events, rights, obligations, and prohibitions.
In the span of just six years, the once-nascent concept of the decentralized autonomous organization (DAO) has grown into a rich tapestry of fluid organizations and token-powered communities.1 Today, DAO governance is considered to be a new universal primitive for value generation and capture across digital markets and industries. The thinking is that, in all instances in which value is generated by networks of prosumers and consumers, a DAO model has the potential to reallocate value capture to the network.
Cristóbal Marinkovic, Julio López Fenner, Óscar Ancán, Carlos Cares
Smart contracts are contracts made of executable code running on Blockchain platforms. DasContract was introduced in 2019-2020 as a domain-specific language (DSL) for smart contract modeling with the ability to generate code in a programming language (Solidity), yet its environment exhibits various limitations, both in technical and design aspects. In this work, we propose a user interface with improved usability that includes tools for syntax verification, develop a software prototype, demonstrate its usage with a case study, and identify future lines of research.
The Ph.D research project aims to explore the potential of the Decentralized Autonomous Organization paradigm in conjunction with classic software architectures for Artificial Intelligence applications. The intended goal is to investigate and formalize a possible integration path between Multi-agent System architectures and Decentralized Autonomous Organizations. Starting from the Foundation for Intelligent Physical Agents standards, we will extend basic primitives to integrate Multi-agent Systems on Distributed Ledger Technology networks. Possible deployment of services and applications in the Internet-of-Things, Artificial Intelligence and Distributed Machine Learning areas will be tested. Application of Data Analysis techniques on datasets built on such a framework will be also addressed.
Bernd Finkbeiner, Jana Hofmann, Florian Kohn, Noemi Passing
Smart contracts are small but highly error-prone programs that implement agreements between multiple parties. We present a reactive synthesis approach for the automatic construction of smart contract state machines. Towards this end, we extend temporal stream logic (TSL) with universally quantified parameters over infinite domains. Parameterized TSL is a convenient logic to specify the temporal control flow, i.e., the correct order of transactions, as well as the data flow of the contract's fields. We develop a two-step approach that 1) synthesizes a finite representation of the - in general - infinite-state system and 2) splits the system into a compact hierarchical architecture that enables the implementation of the state machine in Solidity. We implement the approach in our prototype tool SCSynt, which - within seconds - automatically constructs Solidity code that realizes the specified control flow.
The concept of "Decentralized Autonomous Organization" has been popularized as part of the "Web 3.0" movement. This movement is characterized by digital infrastructures that are 'decentralized' in network architecture and permissionless to use. Decentralized autonomous organizations, referred to as DAOs, are a digital expression of the political will to self-organize. The granular entanglement of social and technical concepts makes it challenging to identify a historical precedent for DAOs. Yet, literature review and analysis reveals that this particular entanglement of information systems and self-organization is consistent with longstanding conceptual development and practice in the field of cybernetics. Drawing on Stafford Beer's Viable Systems Model, this piece bridges DAOs and cybernetics via two main principles of organization: viability and purpose. Viability is a property of a system such that it has sufficient adaptive capacity to thrive in the face of change; adaptive capacity is characterized according to Ross Ashby's concept of 'variety'. Purpose is the ability to define and collectively pursue a goal in the sense of feedback control systems. Building on the control theoretic concepts of observability, controllability, and reachability, we examine the 'governance surface' of an organization and the associated trade-offs between resilience and robustness that emerge in governance surface design. We propose that this trade-off can be addressed with a constitutional archetype whereby an organization's ability to update its code is constrained but not eliminated. A case study from a DAO known as '1Hive' is explored to demonstrate this archetype in action. We consider the limitations of the cybernetics perspective by emphasizing the subjectivity of the governance designer. Finally, we conclude with future research directions.
The revolutionary potential of automatic code generation tools based on Model-Driven Engineering (MDE) frameworks has yet to be realized. Beyond their ability to help software professionals write more accurate, reusable code, they could make programming accessible for a whole new class of non-technical users. However, non-technical users have been slow to embrace these tools. This may be because their concrete syntax is often patterned after the operations of textual or graphical interfaces. The interfaces are common, but users would need more extensive, precise and detailed knowledge of them than they can be assumed to have, to use them as concrete syntax. Conversational interfaces (chatbots) offer a much more accessible way for non-technical users to generate code. In this paper, we discuss the basic challenge of integrating conversational agents within Model-Driven Engineering (MDE) frameworks, then turn to look at a specific application: the auto-generation of smart contract code in multiple languages by non-technical users, based on conversational syntax. We demonstrate how this can be done, and evaluate our approach by conducting user experience survey to assess the usability and functionality of the chatbot framework.
Kunjian Song, Nedas Matulevicius, Eddie B. de Lima Filho, Lucas C. Cordeiro
Smart contracts written in Solidity are programs used in blockchain networks, such as Etherium, for performing transactions. However, as with any piece of software, they are prone to errors and may present vulnerabilities, which malicious attackers could then use. This paper proposes a solidity frontend for the efficient SMT-based context-bounded model checker (ESBMC), named ESBMC-Solidity, which provides a way of verifying such contracts with its framework. A benchmark suite with vulnerable smart contracts was also developed for evaluation and comparison with other verification tools. The experiments performed here showed that ESBMC-Solidity detected all vulnerabilities, was the fastest tool, and provided a counterexample for each benchmark. A demonstration is available at https://youtu.be/3UH8_1QAVN0.
A key component of blockchain technology is the ledger, viz., a database that, unlike standard databases, keeps in memory the complete history of past transactions as in a notarial archive for the benefit of any future test. In second-generation blockchains such as Ethereum the ledger is coupled with smart contracts, which enable the automation of transactions associated with agreements between the parties of a financial or commercial nature. The coupling of smart contracts and ledgers provides the technological background for very innovative application areas, such as Decentralized Autonomous Organizations (DAOs), Initial Coin Offerings (ICOs) and Decentralized Finance (DeFi), which propelled blockchains beyond cryptocurrencies that were the only focus of first generation blockchains such as the Bitcoin. However, the currently used implementation of smart contracts as arbitrary programming constructs has made them susceptible to dangerous bugs that can be exploited maliciously and has moved their semantics away from that of legal contracts. We propose here to recompose the split and recover the reliability of databases by formalizing a notion of contract modelled as a finite-state automaton with well-defined computational characteristics derived from an encoding in terms of allocations of resources to actors, as an alternative to the approach based on programming. To complete the work, we use temporal logic as the basis for an abstract query language that is effectively suited to the historical nature of the information kept in the ledger.
Blockchains are gaining momentum due to the interest of industries and people in \emph{decentralized applications} (Dapps), particularly in those for trading assets through digital certificates secured on blockchain, called tokens. As a consequence, providing a clear unambiguous description of any activities carried out on blockchains has become crucial, and we feel the urgency to achieve that description at least for trading. This paper reports on how to leverage the \emph{Ontology for Agents, Systems, and Integration of Services} ("\ONT{}") as a general means for the semantic representation of smart contracts stored on blockchain as software agents. Special attention is paid to non-fungible tokens (NFTs), whose management through the ERC721 standard is presented as a case study.
Blockchains are gaining momentum due to the interest of industries and people in \emph{decentralized applications} (Dapps), particularly in those for trading assets through digital certificates secured on blockchain, called tokens. As a consequence, providing a clear unambiguous description of any activities carried out on blockchains has become crucial, and we feel the urgency to achieve that description at least for trading. This paper reports on how to leverage the \emph{Ontology for Agents, Systems, and Integration of Services} ("\ONT{}") as a general means for the semantic representation of smart contracts stored on blockchain as software agents. Special attention is paid to non-fungible tokens (NFTs), whose management through the ERC721 standard is presented as a case study.
Abstract We introduce the probabilistic two-agent justification logic $\textsf {IPJ}$, a logic in which we can reason about agents that perform interactive proofs. In order to study the growth rate of the probabilities in $\textsf {IPJ}$, we present a new method of parametrizing $\textsf {IPJ}$ over certain negligible functions. Further, our approach leads to a new notion of zero-knowledge proofs.