An Empirical Study Into the Success of Listed Smart Contracts in Ethereum

Since it takes time and effort to put a new product or service on the market, one would like to predict whether it will be a success. In general this is not possible, but it is possible to follow best practices in order to maximize the chance of success. A smart contract is intended to encode business logic and is therefore at the heart of every new business on the Ethereum blockchain. We have investigated how to measure the success of smart contracts, and whether successful smart contracts have characteristics that less successful smart contracts lack. The appearance of a smart contract on a listing website such as Etherscan or StateoftheDapps is such a characteristic. In this paper, we present a three-pronged analysis of the relative success of listed smart contracts. First, we have used statistical analysis on the publicly visible transaction history of the Ethereum blockchain to determine that listed contracts are significantly more successful than their unlisted counterparts. Next, we have conducted a survey among more than 200 developers via an anonymous online survey about their experience with the listing process. A significant majority of respondents do not believe that listing a contract itself contributes to its success, but they believe that the extra attention that is typically paid in tandem with the listing process does contribute. Finally, based on the respondents’ answers, we have drafted 10 recommendations for developers and validated them by submitting them to an international panel of experts.

[1]  Robert M. Hierons,et al.  Smart contracts vulnerabilities: a call for blockchain software engineering? , 2018, 2018 International Workshop on Blockchain Oriented Software Engineering (IWBOSE).

[2]  Andrea Pinna,et al.  A Massive Analysis of Ethereum Smart Contracts Empirical Study and Code Metrics , 2019, IEEE Access.

[3]  M. Angela Sasse,et al.  Why Trust Seals Don't Work: A Study of User Perceptions and Behavior , 2012, TRUST.

[4]  Anindya Iqbal,et al.  Understanding the motivations, challenges and needs of Blockchain software developers: a survey , 2018, Empirical Software Engineering.

[5]  AntoniolGiulio,et al.  Comparison and Evaluation of Clone Detection Tools , 2007 .

[6]  R. Cooper,et al.  New Products: What Separates Winners from Losers? , 1987 .

[7]  Shari Lawrence Pfleeger,et al.  Software Quality: The Elusive Target , 1996, IEEE Softw..

[8]  Giuliano Antoniol,et al.  Comparison and Evaluation of Clone Detection Tools , 2007, IEEE Transactions on Software Engineering.

[9]  Mohan V. Tatikonda,et al.  New service development: areas for exploitation and exploration , 2002 .

[10]  Massimo Bartoletti,et al.  A Survey of Attacks on Ethereum Smart Contracts (SoK) , 2017, POST.

[11]  Haim Mendelson,et al.  Modeling Success and Engagement for the App Economy , 2018, WWW.

[12]  Henry M. Kim,et al.  Understanding a Revolutionary and Flawed Grand Experiment in Blockchain: The DAO Attack , 2017, J. Cases Inf. Technol..

[13]  Gernot Salzer,et al.  Mayflies, Breeders, and Busy Bees in Ethereum: Smart Contracts Over Time , 2019, Proceedings of the Third ACM Workshop on Blockchains, Cryptocurrencies and Contracts - BCC '19.

[14]  Gözem Güçeri-Ucar,et al.  Motivations of application developers: Innovation, business model choice, release policy, and success , 2017, J. Organ. Comput. Electron. Commer..

[15]  Michele Marchesi,et al.  Smart contracts software metrics: A first study , 2018, PloS one.

[16]  A. Johne Listening to the Voice of the Market , 1994 .

[17]  Jun Han,et al.  Blockchain Versus Database: A Critical Analysis , 2018, 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE).

[18]  A. Johne,et al.  New service development: a review of the literature and annotated bibliography , 1998 .

[19]  Andrea Pinna,et al.  Blockchain-Oriented Software Engineering: Challenges and New Directions , 2017, 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C).

[20]  Arthur Gervais,et al.  Do you Need a Blockchain? , 2018, 2018 Crypto Valley Conference on Blockchain Technology (CVCBT).

[21]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[22]  Sandro Morasca,et al.  A Survey on Open Source Software Trustworthiness , 2011, IEEE Software.

[23]  Kwaku Atuahene-Gima,et al.  Differential potency of factors affecting innovation performance in manufacturing and services firms in Australia , 1996 .

[24]  Lei Wu,et al.  Characterizing Code Clones in the Ethereum Smart Contract Ecosystem , 2019, Financial Cryptography.

[25]  Massimo Bartoletti,et al.  Financial Cryptography and Data Security , 2017, Lecture Notes in Computer Science.

[26]  Sangaralingam Kajanan,et al.  Do App Launch Times Impact their Subsequent Commercial Success? An Analytical Approach , 2013, 2013 International Conference on Cloud Computing and Big Data.

[27]  Abhishek Dubey,et al.  VeriSolid: Correct-by-Design Smart Contracts for Ethereum , 2019, Financial Cryptography.

[28]  Vitalik Buterin A NEXT GENERATION SMART CONTRACT & DECENTRALIZED APPLICATION PLATFORM , 2015 .

[29]  Sasu Tarkoma,et al.  Exploiting Usage to Predict Instantaneous App Popularity , 2019, ACM Trans. Web.