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An Empirical Analysis of Smart Contracts: Platforms, Applications, and Design Patterns

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Financial Cryptography and Data Security (FC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10323))

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Abstract

Smart contracts are computer programs that can be consistently executed by a network of mutually distrusting nodes, without the arbitration of a trusted authority. Because of their resilience to tampering, smart contracts are appealing in many scenarios, especially in those which require transfers of money to respect certain agreed rules (like in financial services and in games). Over the last few years many platforms for smart contracts have been proposed, and some of them have been actually implemented and used. We study how the notion of smart contract is interpreted in some of these platforms. Focussing on the two most widespread ones, Bitcoin and Ethereum, we quantify the usage of smart contracts in relation to their application domain. We also analyse the most common programming patterns in Ethereum, where the source code of smart contracts is available.

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Notes

  1. 1.

    http://www.coindesk.com/category/technology/smart-contracts-news.

  2. 2.

    As far as we know, currently only the Eligius mining pool accepts more general transactions (called non-standard in the Bitcoin community). However, this pool only mines \(\sim 1\%\) of the total mined blocks [20].

  3. 3.

    The consensus mechanism of Ethereum is a variant of the GHOST protocol in [46].

  4. 4.

    Solidity: http://solidity.readthedocs.io/en/develop/index.html.

  5. 5.

    See FAQ: How do Smart Contracts “form a consensus” on Counterparty? http://counterparty.io/docs/faq-smartcontracts/#how-do-smart-contracts-form-a-consensus-on-counterparty.

  6. 6.

    https://www.stellar.org/developers/guides/concepts/operations.html.

  7. 7.

    https://tendermint.com/.

  8. 8.

    https://lisk.io/documentation?i=lisk-handbooks/DelegateHandbook.

  9. 9.

    https://redd.it/5om2lw.

  10. 10.

    Sources: https://blockchain.info/charts/n-transactions-total (for Bitcoin), https://blockscan.com (Counterparty), and https://etherscan.io (Ethereum).

  11. 11.

    Market capitalization estimated by http://coinmarketcap.com.

  12. 12.

    https://github.com/BitcoinOpReturn/OpReturnTool.

  13. 13.

    Bitcoin financial contracts: Colu, CoinSpark, OpenAssets, Omni, SmartBit, BitPos.

  14. 14.

    Bitcoin notary contracts: Factom, Stampery, Proof of Existence, Blocksign, Crypto-Copyright, Stampd, BitProof, ProveBit, Remembr, OriginalMy, LaPreuve, Nicosia, Chainpoint, Diploma, Monegraph, Blockai, Ascribe, Eternity Wall, Blockstore.

  15. 15.

    Although the Ethereum virtual machine is designed to be Turing-complete, in practice the limitations on the amount of gas which can be used to invoke contracts also limit the set of computable functions (e.g., verifying checkmate exceeds the current gas limits of a transaction [35]).

  16. 16.

    http://www.oraclize.it/.

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Acknowledgments

This work is partially supported by Aut. Reg. of Sardinia project P.I.A. 2013 “NOMAD”.

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Authors and Affiliations

  1. Università degli Studi di Cagliari, Cagliari, Italy

    Massimo Bartoletti & Livio Pompianu

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  1. Massimo Bartoletti
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Correspondence to Massimo Bartoletti .

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Editors and Affiliations

  1. Leibniz Universität Hannover, Hannover, Germany

    Michael Brenner

  2. New Jersey Institute of Technology, Newark, New Jersey, USA

    Kurt Rohloff

  3. New York University, New York, New York, USA

    Joseph Bonneau

  4. University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

    Andrew Miller

  5. University of Luxembourg, Luxembourg, Luxembourg

    Peter Y.A. Ryan

  6. University of Melbourne, Parkville, Victoria, Australia

    Vanessa Teague

  7. University of Stirling, Stirling, United Kingdom

    Andrea Bracciali

  8. University of Trento, Trento, Italy

    Massimiliano Sala

  9. University of Trento, Trento, Italy

    Federico Pintore

  10. Agari Inc., San Mateo, California, USA

    Markus Jakobsson

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Bartoletti, M., Pompianu, L. (2017). An Empirical Analysis of Smart Contracts: Platforms, Applications, and Design Patterns. In: Brenner, M., et al. Financial Cryptography and Data Security. FC 2017. Lecture Notes in Computer Science(), vol 10323. Springer, Cham. https://doi.org/10.1007/978-3-319-70278-0_31

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