In smart contract development, practitioners frequently reuse code to reduce development effort and avoid reinventing the wheel. This reused code, whether identical or similar to its original source, is referred to as a code clone. Unintentional code cloning can propagate flaws and vulnerabilities, potentially undermining the reliability and maintainability of software systems. Previous studies have identified a significant prevalence of code clones in Solidity smart contracts on the Ethereum blockchain. To mitigate the risks posed by code clones, clone detection has emerged as an active field of research and practice in software engineering. Recent studies have extended existing techniques or proposed novel techniques tailored to the unique syntactic and semantic features of Solidity. Nonetheless, the evaluations of existing techniques, whether conducted by their original authors or independent researchers, involve codebases in various programming languages and utilize different versions of the corresponding tools. The resulting inconsistency makes direct comparisons of the evaluation results impractical, and hinders the ability to derive meaningful conclusions across the evaluations. There remains a lack of clarity regarding the effectiveness of these techniques in detecting smart contract clones, and whether it is feasible to combine different techniques to achieve scalable yet accurate detection of code clones in smart contracts. To address this gap, we conduct a comprehensive empirical study that evaluates the effectiveness and scalability of five representative clone detection techniques on 33,073 verified Solidity smart contracts, along with a benchmark we curate, in which we manually label 72,010 pairs of Solidity smart contracts with clone tags. Moreover, we explore the potential of combining different techniques to achieve optimal performance of code clone detection for smart contracts, and propose SourceREClone, a framework designed for the refined integration of different techniques, which achieves a 36.9% improvement in F1 score compared to a straightforward combination of the state of the art. Based on our findings, we discuss implications, provide recommendations for practitioners, and outline directions for future research.
Mihai DuguleanÄ, Andreea Raluca DuguleanÄ, Cristina TÄnÄsescu, Florin GĂŽrbacia
In the contemporary robotics landscape, decentralized governance mechanisms offer promising avenues for democratizing control over robotic activities. This paper introduces a new framework integrating crowd-choice mechanisms inspired by Decentralized Autonomous Organizations (DAOs) with robotic control systems. Our framework enables any stakeholder (individuals, companies, public institutions, NGOs and so on) to collectively determine robot activities through transparent and auditable decision-making processes. By leveraging blockchain technology, users can participate in prioritizing and executing robot actions, similar to DAO voting. We outline the architecture, implementation guidelines, and potential applications of the framework across diverse domains such as industrial automation, healthcare, and disaster response. Furthermore, we discuss the governance model, security considerations, and future research directions in advancing decentralized robotics governance. Through this framework, we envision a paradigm shift towards inclusive, transparent, and efficient multi-user robot control.
Background: Solidity is the primary programming language used for developing smart contracts on Ethereum, representing a new generation of programming languages developed entirely in open environments. Objective: This longitudinal case study examines contribution patterns and emotional dynamics within the Solidity GitHub repository over a ten-year period (2014-2024). Method: We developed a contribution index combining metrics from developer activities (commits, pull requests, comments, and temporal engagement) and applied emotion detection to study communication patterns in a decade-long dataset of developer interactions. Results: The top 1 % of contributors are responsible for around 85 % of project contributions, yet the project exhibits dual paths to prominence: early contributors established technical foundations through code, while later contributors achieved influence through reviews and discussions. Emotional patterns show transitions from initial curiosity and confusion to eventual approval and gratitude. Conclusion: The project's recognition of diverse contribution types and evolving emotional dynamics enables sustainable growth despite concentrated contributions, demonstrating how open-source languages can evolve while maintaining both technical rigor and community engagement.
Francesco Salzano, Lodovica Marchesi, Cosmo Kevin Antenucci, Simone Scalabrino ¡ 7 authors
Abstract In this paper, we investigate the strategies adopted by Solidity developers to fix security vulnerabilities in smart contracts. Vulnerabilities are categorized using the DASP TOP 10 taxonomy, and fixing strategies are extracted from 364 commits collected from open-source Solidity projects on GitHub. Each commit was selected through a two-phase process: an initial filter using natural language processing techniques, followed by manual validation. We assessed whether these fixes adhere to established academic guidelines. Our analysis shows that 60.55% of the commits aligned with at least one literature-based recommendation, particularly for well-documented vulnerability types such as Reentrancy and Arithmetic. However, adherence dropped significantly for categories like Denial of Service, Time Manipulation, and Bad Randomness, highlighting gaps between academic best practices and real-world developer behavior. From the remaining 143 non-aligned commits, we identified 27 novel fixing strategies not previously discussed in the literature. To evaluate their quality, we conducted a structured questionnaire involving 9 experts from both academia and industry. Their feedback indicated high perceived effectiveness of the new fixes, especially for vulnerabilities like Reentrancy and Unchecked Return Values. Generalizability received more varied responses, suggesting context-specific applicability. Finally, we performed a post-fix evolution analysis on over 6700 subsequent commits to assess the long-term stability of the fixes. Most patches remained unchanged, confirming their persistence in production code. Our findings offer practical insights into how vulnerabilities are fixed in smart contracts today, reveal promising emerging patterns, and help bridge the gap between academic guidelines and developer practices.
John Stephan, Matej Pavlovic, Antonio Locascio, Benjamin Livshits
Zero-Knowledge (ZK) rollups have become a popular solution for scaling blockchain systems, offering improved transaction throughput and reduced costs by aggregating Layer 2 transactions and submitting them as a single batch to a Layer 1 blockchain. However, the computational burden of generating validity proofs, a key feature of ZK rollups, presents significant challenges in terms of performance and decentralization. Current solutions rely on centralized infrastructure to handle the computational tasks, limiting the scalability and decentralization of rollup systems. This paper proposes CrowdProve, a prover orchestration layer for outsourcing computation to unreliable commodity hardware run by a broad community of small provers. We apply CrowdProve to proving transaction batches for a popular ZK rollup. Through our experimental evaluation, we demonstrate that community proving can achieve performance comparable to, and in some cases better than, existing centralized deployments. Our results show that even systems utilizing modest hardware configurations can match the performance of centralized solutions, making community-based proof generation a viable and cost-effective alternative. CrowdProve allows both the rollup operator and community participants to benefit: the operator reduces infrastructure costs by leveraging idle community hardware, while community provers are compensated for their contributions.
Giacomo Vella, Valeria Portale, Daniel Trabucchi, Luca Gastaldi
This study investigates how blockchain-based platforms redefine traditional innovation platform models by analyzing Ethereum as a paradigmatic case.While classical platforms are characterized by centralized governance and selective openness, Ethereum introduces a decentralized architecture that structurally embeds openness, composability, and permissionless participation into its protocol.Drawing on a qualitative single-case study based on over 100 secondary sources, this research explores three dimensions: governance and orchestration, complementor engagement, and architectural modularity.Findings highlight that Ethereum operates through multi-actor orchestration, where governance is distributed among core developers, the Ethereum Foundation, decentralized autonomous organizations, and community contributors.Complementors engage directly with the platform, leveraging smart contracts and token-based incentives to build interoperable applications without the need for approval from a central authority.Moreover, Ethereum extends composability beyond core-periphery dynamics, enabling peer-level recombination of complements through public, reusable smart contracts.A comparative analysis with traditional platforms and open-source ecosystems positions Ethereum as a novel archetype of innovation platform, blending open-source governance with blockchain-enabled modularity and decentralized economic coordination.The study advances platform theory by proposing new conceptualizations of openness, modularity, and governance in decentralized digital ecosystems.
Ensuring the reproducibility of scientific simulations is a persistent challenge, despite current best practices like version control and containerization. Factors such as floating-point arithmetic variations, hardware differences, and concurrency issues often prevent bit-for-bit replication of results. This paper investigates the techniques that distributed ledger technologies employ to achieve deterministic computations and application of these techniques to enhance the reproducibility, trustworthiness and verifiability of scientific simulations. We explore two primary approaches: executing simulations directly âon-chainâ for complete transparency and deterministic replay, and performing computations âoff-chainâ while anchoring their integrity to a blockchain via cryptographic proofs, such as Zero-Knowledge Proofs (ZKPs) and Merkle trees.
Decentralized autonomous organizations (DAOs) crowdfunds to invest in various projects. The decentralization feature of DAOs submits that decision-making is a collective democratic action of all DAO members. The autonomy feature of DAOs suggests that decision-making is an algorithmic process governed by self-executing smart contracts. However, in reality, DAOs are neither perfectly decentralized nor completely autonomous. Our empirical analysis shows that deviations from the ideals of decentralization and autonomy are costly. Non-algorithmic off-chain voting governance of decision-making leads to a substantial discount in DAO value. Non-decentralized aspects such as large voting coalitions also affect DAO value. Interaction effects are also shown. The study implies that platform governance design choices are crucial for DAO success. ⢠DAOs with off-chain voting raise 87% less funding. ⢠Larger communities worsen the valuation hit from off-chain voting. ⢠Big voting coalitions deepen off-chain governance drawbacks. ⢠On-chain transparency is key to DAO successâespecially in large technical teams.
This article examines how âbrandless by designâ strategies in Web3, particularly among digital nomads and creators of non-fungible tokens (NFTs), reshape consumer behavior, market intermediation, and governance. Using a structured thematic synthesis of interdisciplinary academic and gray literature, we integrate five analytical lenses: affordances (provenance, programmability, composability, and token-gated access), signaling (credibility through on-chain histories and disclosures), consumer identity (the extended self in digital ownership and display), parasocial interaction (attachment without human embodiment), and governance (smart contract terms, platform policies, and community charters). Three primary themes emerge. First, creative autonomy and disintermediation, as NFTs enable direct creator-to-consumer exchange and programmable provenance. Second, engagement and authenticity, as communities cohere around transparent access and shared utility rather than traditional brand logos. Third, sustainability and decentralization, which highlight tensions around environmental impact, intellectual property, cultural legitimacy, and consumer protection. Cross-cutting subthemes, including parasocial credibility, accessibility and cultural sensitivity, and brand control versus co-creation, explain why brandlessness can appear simultaneously intimate and precarious. We propose a conceptual framework that links brandlessness to decentralized identity and on-chain governance, clarifying when provenance signals, token-bound permissions, and community norms substitute effectively for legacy brand cues. The review concludes with implications for practice and policy, such as standardized licenses, clear disclosures, participatory design, on-chain royalty registries, and interoperable memberships that balance value capture with oversight. Future research should prioritize cross-cultural adoption, sustainability auditing that incorporates off-chain infrastructure, and mixed-methods designs combining on-chain telemetry with ethnography and experiments to assess trust, authenticity, and wellbeing.
Artificial Intelligence (AI) is increasingly framed as a driver of economic transformation, yet its capacity to alleviate poverty in the Global South remains contested. This article introduces the notion of AI Economicsâthe political economy of value creation, extraction, and redistribution in AI systemsâto interrogate h ow innovation agendas intersect with structural inequalities. This article examines how Social Innovation (SI) systems, when coupled with decentralized Web3 technologies such as blockchain, Decentralized Autonomous Organizations (DAOs), and data cooperatives, may challenge data monopolies, redistribute economic gains, and support inclusive development. Drawing on Action Research (AR) conducted during the AI4SI International Summer School in Donostia-San SebastiĂĄn, this article compares two contrasting ecosystems: (i) the Established AI4SI Ecosystem, marked by centralized governance and uneven benefits, and (ii) the Decentralized Web3 Emerging Ecosystem, which promotes community-driven innovation, data sovereignty, and alternative economic models. Findings underscore AIâs dual economic role: while it can expand digital justice, service provision, and empowerment, it also risks reinforcing dependency and inequality where infrastructures and governance remain weak. This article concludes that embedding AI Economics in context-sensitive, decentralized social innovation systemsâaligned with ethical governance and the SDGsâis essential for realizing AIâs promise of poverty alleviation in the Global South.
This article investigates how Web3 decentralization unfolds in practice and asks two guiding questions: (i) How democratic are decentralized governance systems in practice? (ii) Under what institutional conditions can technological decentralization translate into social inclusion? Based on multi-year ethnographic fieldwork (2022â2025) across Silicon Valley, Washington, D.C., Europe, and the Global South, this study draws on participant observation, semi-structured interviews, and comparative analysis of seven ecosystemsâEthereum, MakerDAO, Uniswap, Mastodon, Celo, Grassroots Economics, and GoodDollar. The findings show that participation asymmetries are structural: token-based governance is dominated by a small group of technically skilled or capital-rich actors, while voter turnout often remains below ten percent. Intermediaries such as foundations, developers, NGOs, and cooperatives are indispensable for coordination, contradicting the idea of hierarchy-free decentralization. In contrast, projects that institutionalize clear membership, monitoring, and accountabilityâparticularly in cooperative and federated settingsâdisplay stronger democratic resilience. Comparative evidence also reveals oligarchic consolidation in Global North ecosystems and infrastructural exclusion in the Global South. These results substantiate what Richard R. Nelson termed âthe Moon and the Ghettoâ paradox: extraordinary technical innovation without corresponding social progress. Interpreted through innovation systems theory, the study concludes that advancing decentralized technologies requires parallel investment in mission-oriented institutions that ensure participation, equity, and accountability in digital infrastructures.
Mark C. Ballandies, Dino Carpentras, Evangelos Pournaras
Decentralized autonomous organizations (DAOs) have transformed organizational structures by shifting from traditional hierarchical control to decentralized approaches, leveraging blockchain and cryptoeconomics. Despite managing significant funds and building global networks, DAOs face challenges like declining participation, increasing centralization, and inabilities to adapt to changing environments, which stifle innovation. This paper explores DAOs as complex systems and applies complexity science to explain their inefficiencies. In particular, we discuss DAO challenges, their complex nature, and introduce the self-organization mechanisms of collective intelligence, digital democracy, and adaptation. By applying these mechanisms to refine DAO design and construction, a conceptual framework for assessing a DAOâs viability is created. This contribution lays the foundation for future research at the intersection of complexity science, digital democracy and DAOs.
Abstract Ethereum, as a leading blockchain platform, has attracted a significant number of practitioners. These practitioners require a platform for communication and collaborative problemâsolving, which led to Ethereum Stack Exchange (ESE), a Q&A site dedicated to Ethereumârelated issues. While the Q&A site facilitates communication among practitioners, it also introduces new challenges. Practitioners adopt code snippets from Q&A sites to address problems encountered. However, the quality of code snippets on ESE remains largely unexplored. Vulnerabilities and gasâinefficient patterns in ESE may spread to the code in Ethereum and threaten its regular operation. In this article, we conduct an empirical study investigating the distribution of vulnerabilities and gasâinefficient patterns in ESE. Further, we analyze the potential impact of vulnerabilities and gasâinefficient patterns from ESE on Ethereum. However, we encounter a problem during the vulnerability and gasâinefficient pattern detection. Established smart contract analysis tools in the mainstream realm necessitate complete source code files for thorough analysis, while codes on ESE are often incomplete code snippets. To address this, we introduce the ASTâbased code clone detection technique to construct detectable files corresponding to code snippets. This enables us to detect vulnerabilities and gasâinefficient patterns in code snippets. In the end, our findings demonstrate that 11.18% of the contractâlevel code snippets and 4.06% of functionâlevel code snippets in ESE have vulnerabilities. And 27.21% of contractâlevel code snippets and 17.89% of functionâlevel code snippets contain gasâinefficient patterns. The additional consumption caused by the gasâinefficient pattern in ESE is approximately $1,695,002. Based on these findings, we provide recommendations for both ESE and its users, aiming to foster collaborative efforts and create a more reliable Q&A site for practitioners.
Mark C. Ballandies, Valentin Holzwarth, Barry Sunderland, Evangelos Pournaras ¡ 5 authors
Abstract Organizations have to adjust to changes in the ecosystem, and customer feedback systems (CFS) provide important information to adapt products and services to changing customer preferences. However, current systems are limited to single-dimensional rating scales and are subject to self-selection biases. The work contributes design principles for CFS and implements a CFS that advances current systems by means of contextualized feedback according to specific organizational objectives. The authors apply Design Science Research (DSR) methodology and report on a longitudinal DSR journey considering multiple stakeholder values by utilizing value-sensitive design methods. They conducted expert interviews, design workshops, demonstrations, and a four-day experiment in an organizational setup, involving 132 customers of a major Swiss library. In the process, the identified design principles and the implemented software artifact were validated qualitatively and quantitatively, leading to conclusions for their efficient instantiation. The authors found that i) blockchain technology can afford four design principles of effective CFS. Also, ii) combining DSR with value-sensitive design methods explicitly provides rationale for design principles in the form of identified important values. Moreover, iii) combining DSR with value-sensitive design methods makes the construction of software artifacts more efficient it terms of design time by restricting the design space of a software artifact to those options that align with stakeholder values. The findings of this work thus extend the knowledge about the design of CFS and offer both researchers a theoretical contribution to reasoning about design principles and managers and decision makers a guide for the efficient design of software artifacts.
Andrea PeĂąa-Calvin, Javier Arroyo, Andrew B. Schwartz, Samer Hassan
Blockchain technology enables a new form of online community: Decentralized Autonomous Organizations (DAOs), where members typically vote on proposals using tokens. Enthusiasts claim DAOs provide new opportunities for openness, horizontality, and democratization. However, this phenomenon is still under research, especially given the lack of quantitative studies. This paper presents the first census-like quantitative analysis of the whole ecosystem of DAOs, including 30K DAO communities on the main DAO platforms. This enables us to provide insights into the allegedly "democratic'' nature of DAOs, building metrics concerning their lifespan, participation, and power concentration. Most DAOs have a short lifespan and low participation. There is also a positive correlation between community size and voting power concentration. Like other online communities, DAOs seem to follow the iron law: becoming increasingly oligarchic as they grow. Still, a significant amount of DAOs of varying sizes defy this idea by being egalitarian by design.
Che Wang, Yue Li, Jianbo Gao, Ke Wang ¡ 7 authors
The open-source nature of smart contracts provides the facility for developers to clone contracts and introduces the risk of vulnerability proliferation as well. Despite intensive research on smart contract clone detection in recent years, existing techniques are still unsatisfactory in detecting Solana smart contracts. To fill this gap, in this paper, we designed a clone detection tool SolaSim for Solana smart contracts and conducted an empirical study to understand the code reuse in the Solana ecosystem. Specifically, SolaSim is based on the semantic metadata extractor and the similarity checker. For each contract, the semantic metadata extractor generates an instruction-level weighted Attributed Control Flow Graph (ACFG) and its semantic metadata (i.e., a combination of high-level semantic and structure information) based on Rust Mid-level Intermediate Representation. The similarity checker adopts a combinatorial optimization algorithm to compute the statistical similarity of a pair of contracts. The evaluation results demonstrated the effectiveness of SolaSim in identifying clones with 94.3% accuracy and it can identify up to Type-3 clone level. Notably, we found there are over 50% clone ratios in the Solana smart contracts ecosystem, in which most of them are cloned from famous open-sourced projects.
Arthur Carvalho, Chad Anderson, Liudmila Zavolokina
Information systems (IS) conferences, as venues for the introduction of new knowledge to the IS community, require effective peer review systems to evaluate submitted research for quality, validity, and originality. We argue in this paper that questionable practices and degrading review quality may arise without direct incentives beyond reviewer altruism to engage in the peer review process. In particular, we highlight potential issues with arguably common practices in some IS conferences, such as peer review invitations sent to researchers who have also submitted papers for publication consideration and the increasing number of reviews performed by graduate students. To address these issues, we suggest three solutions: 1) quid pro quo rules; 2) the use of incentive-compatible methods whose scores are linked to relevant rewards; and 3) the use of blockchain-based tokens in tandem with smart contracts and zero-knowledge proofs. We conclude by offering directions the IS community can take to further study the highlighted issues and implement the proposed solutions.
In an era of rapid technological advancement, decisions about the ownership and governance of emerging technologies like Artificial Intelligence will shape the future of both urban and rural environments in the Global North and South. This article explores how AI can move beyond the noise of algorithms by adopting a technological humanistic approach to enable Social Innovation, focusing on global inequalities and digital justice. Using a fieldwork Action Research methodology, based on the Smart Rural Communities project in Colombia and Mozambique, the study develops a framework for integrating AI with SI. Drawing on insights from the AI4SI International Summer School held in Donostia-San SebastiĂĄn in 2024, the article examines the role of decentralized Web3 technologiesâsuch as Blockchain, Decentralized Autonomous Organizations, and Data Cooperativesâin enhancing data sovereignty and fostering inclusive and participatory governance. The results demonstrate how decentralization can empower marginalized communities in the Global South by promoting digital justice and addressing the imbalance of power in digital ecosystems. The conclusion emphasizes the potential for AI and decentralized technologies to bridge the digital divide, offering practical recommendations for scaling these innovations to support equitable, community-driven governance and address systemic inequalities across the Global North and South.
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Innovative Approaches in Technology and Social Development
Jan 1, 2024¡Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Annika Bengts, Ville Eloranta, Esko Hakanen, Taija Turunen ¡ 5 authors
Business models integrate activities for value creation and capture. While ecosystems have emerged as potent catalysts for value creation through collaborative innovation, the common understanding is that value capture occurs within individual firms. This paper challenges this dichotomy. In an empirical study using a polar types case approach, we first illustrate how two ecosystems employ decentralization technology, specifically blockchain-based Web3 platforms, to elevate value capture to the ecosystem level. We then outline the implications beyond the blockchain domain using two non-Web3 cases. Specifically, we showâfrom the perspectives of value proposition, value constellation, and profit equationâhow business models can rise to the ecosystem level.