More than eight million smart contracts have been deployed into Ethereum, which is the most popular blockchain that supports smart contract. However, less than 1% of deployed smart contracts are open-source, and it is difficult for users to understand the functionality and internal mechanism of those closed-source contracts. Although a few decompilers for smart contracts have been recently proposed, it is still not easy for users to grasp the semantic information of the contract, not to mention the potential misleading due to decompilation errors. In this paper, we propose the first system named STAN to generate descriptions for the bytecodes of smart contracts to help users comprehend them. In particular, for each interface in a smart contract, STAN can generate four categories of descriptions, including functionality description, usage description, behavior description, and payment description, by leveraging symbolic execution and NLP (Natural Language Processing) techniques. Extensive experiments show that STAN can generate adequate, accurate, and readable descriptions for contract's bytecodes, which have practical value for users.
Being the most popular permissionless blockchain that supports smart contracts, Ethereum allows any user to create accounts on it. However, not all accounts matter. For example, the accounts due to attacks can be removed. In this paper, we conduct the first investigation on erasable accounts that can be removed to save system resources and even users' money (i.e., ETH or gas). In particular, we propose and develop a novel tool named GLASER, which analyzes the State DataBase of Ethereum to discover five kinds of erasable accounts. The experimental results show that GLASER can accurately reveal 508,482 erasable accounts and these accounts lead to users wasting more than 106 million dollars. GLASER can help stop further economic loss caused by these detected accounts. Moreover, GLASER characterizes the attacks/behaviors related to detected erasable accounts through graph analysis.
Blockchain software development is becoming more and more important for any modern software developer and IT startup. Nonetheless, blockchain software production still lacks a disciplined, organized and mature development process, as demonstrated by the many and (in)famous failures and frauds occurred in recent years. In this paper we present ABCDE, a complete method addressing blockchain software development. The method considers the software integration among the blockchain components—smart contracts, libraries, data structures—and the out-of-chain components, such as web or mobile applications, which all together constitute a complete DApp system. We advocate for ABCDE the use of agile practices, because these are suited to develop systems whose requirements are not completely understood since the beginning, or tend to change, as it is the case of most blockchain-based applications. ABCDE is based on Scrum, and is therefore iterative and incremental. From Scrum, we kept the requirement gathering with user stories, the iterative-incremental approach, the key roles, and the meetings. The main difference with Scrum is the separation of development activities in two flows—one for smart contracts and the other for out-of-chain software interacting with the blockchain—each performed iteratively, with integration activities every 2–3 iterations. ABCDE makes explicit the activities that must be performed to design, develop, test and integrate smart contracts and out-of-chain software, and documents the smart contracts using formal diagrams to help development, security assessment, and maintenance. A diagram derived from UML class diagram helps to effectively model the data structure of smart contracts, whereas the exchange of messages between the entities of the system is modeled using a modified UML sequence diagram. The proposed method has also specific activities for security assessment and gas optimization, through systematic use of patterns and checklists. ABCDE focuses on Ethereum blockchain and its Solidity language, but preserves generality and with proper modifications might be applied to any blockchain software project. ABCDE method is described in detail, and an example is given to show how to concretely implement the various development steps.
Smart contract technology is reshaping conventional industry and business processes. Being embedded in blockchains, smart contracts enable the contractual terms of an agreement to be enforced automatically without the intervention of a trusted third party. As a result, smart contracts can cut down administration and save services costs, improve the efficiency of business processes and reduce the risks. Although smart contracts are promising to drive the new wave of innovation in business processes, there are a number of challenges to be tackled.This paper presents a survey on smart contracts. We first introduce blockchains and smart contracts. We then present the challenges in smart contracts as well as recent technical advances. We also compare typical smart contract platforms and give a categorization of smart contract applications along with some representative examples.
Xiao Liang Yu, Omar I. Al-Bataineh, David Lo, Abhik Roychoudhury
Smart contracts are automated or self-enforcing contracts that can be used to exchange assets without having to place trust in third parties. Many commercial transactions use smart contracts due to their potential benefits in terms of secure peer-to-peer transactions independent of external parties. Experience shows that many commonly used smart contracts are vulnerable to serious malicious attacks, which may enable attackers to steal valuable assets of involving parties. There is, therefore, a need to apply analysis and automated repair techniques to detect and repair bugs in smart contracts before being deployed. In this work, we present the first general-purpose automated smart contract repair approach that is also gas-aware. Our repair method is search-based and searches among mutations of the buggy contract. Our method also considers the gas usage of the candidate patches by leveraging our novel notion of gas dominance relationship . We have made our smart contract repair tool SCRepair available open-source, for investigation by the wider community.
Blockchain is gaining extensive attention due to its provision of secure and decentralized resource sharing manner. However, the incumbent blockchain systems also suffer from a number of challenges in operational maintenance, quality assurance of smart contracts and malicious behaviour detection of blockchain data. The recent advances in artificial intelligence bring the opportunities in overcoming the above challenges. The integration of blockchain with artificial intelligence can be beneficial to enhance current blockchain systems. This article presents an introduction of the convergence of blockchain and artificial intelligence (namely blockchain intelligence). This article also gives a case study to further demonstrate the feasibility of blockchain intelligence and point out the future directions.
Smart contracts are immutable, verifiable, and autonomous pieces of code that can be deployed and ran on blockchain networks like Ethereum. Due to the immutability nature of blockchain, no change is possible on a deployed smart contract or a verified transaction. On the other hand, there are millions of dollars carried by smart contracts in Ethereum blockchain, and hence, a faulty smart contract can lead to a huge monetary loss. Therefore, it is important for smart contract developers to fully test and check the correctness of their code before deploying it on the blockchain. In this paper, we propose a testing mechanism for smart contracts in Solidity language, based on mutation testing. We analyzed a comprehensive list of known bugs in Solidity smart contracts, and designed 10 classes of mutation operators inspired by the real faults. Our experimental results show that our proposed mutation operators can regenerate 10 of 15 famous faulty smart contracts, which have resulted in millions of dollars loss. The results show the effectiveness of our proposed mutation operators in detecting real faults in Solidity smart contracts. We have also extended {\em Universal Mutator } tool with our mutation operators, so that it can automatically generate mutants for smart contracts written in Solidity.
Michael Coblenz, Gauri Kambhatla, Paulette Koronkevich, Jenna L. Wise · 8 authors
Programming language design requires making many usability-related design decisions. However, existing HCI methods can be impractical to apply to programming languages: they have high iteration costs, programmers require significant learning time, and user performance has high variance. To address these problems, we adapted both formative and summative HCI methods to make them more suitable for programming language design. We integrated these methods into a new process, PLIERS, for designing programming languages in a user-centered way. We evaluated PLIERS by using it to design two new programming languages. Glacier extends Java to enable programmers to express immutability properties effectively and easily. Obsidian is a language for blockchains that includes verification of critical safety properties. Summative usability studies showed that programmers were able to program effectively in both languages after short training periods.
Jiaming Ye, Mingliang Ma, Yun Lin, Lei Ma · 6 authors
Recent years have seen smart contracts are getting increasingly popular in building trustworthy decentralized applications. Previous research has proposed static and dynamic techniques to detect vulnerabilities in smart contracts. These tools check vulnerable contracts against several predefined rules. However, the emerging new vulnerable types and programming skills to prevent possible vulnerabilities emerging lead to a large number of false positive and false negative reports of tools. To address this, we propose Vulpedia, which mines expressive vulnerability signatures from contracts. Vulpedia is based on the relaxed assumption that the owner of contract is not malicious. Specifically, we extract structural program features from vulnerable and benign contracts as vulnerability signatures, and construct a systematic detection method based on detection rules composed of vulnerability signatures. Compared with the rules defined by state-of-the-arts, our approach can extract more expressive rules to achieve better completeness (i.e., detection recall) and soundness (i.e., precision). We further evaluate Vulpedia with four baselines (i.e., Slither, Securify, SmartCheck and Oyente) on the testing dataset consisting of 17,770 contracts. The experiment results show that Vulpedia achieves best performance of precision on 4 types of vulnerabilities and leading recall on 3 types of vulnerabilities meanwhile exhibiting the great efficiency performance.
Smart contracts are appealing because they are self-executing business agreements between parties with the predefined and immutable obligations and rights. However, as with all software, smart contracts may contain vulnerabilities because of design flaws, which may be exploited by one of the parties to defraud the others. In this paper, we demonstrate a systematic approach to building secure design models for smart contracts using formal methods. To build the secure models, we first model the behaviors of participating parties as state machines, and then, we model the predefined obligations and rights of contracts, which specify the interactions among state machines for achieving the business goal. After that, we illustrate executable secure model design patterns in TLA+ (Temporal Logic of Actions) to against well-known smart contract vulnerabilities in terms of state machines and obligations and rights at the design level. These vulnerabilities are found in Ethereum contracts, including Call to the unknown, Gasless send, Reentrancy, Lost in the transfer, and Unpredictable state. The resultant TLA+ specifications are called secure models. We illustrate our approach to detect the vulnerabilities using a real-estate contract example at the design level.
Swati Megha, Joseph Lamptey, Hamza Salem, Manuel Mazzara
The energy industry needs to shift to a new paradigm from its classical model of energy generation, distribution, and management. This shift is necessary to handle digitization, increased renewable energy generation, and to achieve goals of environmental sustainability. This shift has several challenges on its way and has been seen through research and development that blockchain which is one of the budding technology in this era could be suitable for addressing those challenges. This paper is aimed at the survey of all the research and development related to blockchain in the energy industry and uses a software engineering approach to categories all the existing work in several clusters such as challenges addressed, quality attribute promoted, the maturity level of the solutions, etc. This survey provides researchers in this field a well-defined categorization and insight into the existing work in this field from 3 different perspectives (challenges, quality attributes, maturity).
As a blockchain platform that has developed vigorously in recent years, Ethereum is different from Bitcoin in that it introduces smart contracts into blockchain.Solidity is one of the most mature and widely used smart contract programming language,which is used to write smart contracts and deploy them on blockchain. However, once the data in the blockchain is written, it cannot be modified. Ethereum smart contract is stored in the block chain, which makes the smart contract can no longer repair the code problems such as re-entrancy vulnerabilities or integer overflow problems. Currently, there still lacks of an efficient and effective approach for detecting these problems in Solidity. In this paper, we first classify all the possible problems in Solidity, then propose a smart contract problem detection approach for Solidity, namely SolidityCheck. The approach uses regular expressions to define the characteristics of problematic statements and uses regular matching and program instrumentation to prevent or detect problems. Finally, a large number of experiments is performed to show that SolidityCheck is superior to existing approaches.
Alex Groce, Josselin Feist, Gustavo Grieco, Michael Colburn
An important problem in smart contract security is understanding the likelihood and criticality of discovered, or potential, weaknesses in contracts. In this paper we provide a summary of Ethereum smart contract audits performed for 23 professional stakeholders, avoiding the common problem of reporting issues mostly prevalent in low-quality contracts. These audits were performed at a leading company in blockchain security, using both open-source and proprietary tools, as well as human code analysis performed by professional security engineers. We categorize 246 individual defects, making it possible to compare the severity and frequency of different vulnerability types, compare smart contract and non-smart contract flaws, and to estimate the efficacy of automated vulnerability detection approaches.
Wouter Lueks, Bogdan Kulynych, Jules Fasquelle, Simon Le Bail-Collet · 5 authors
Zero-knowledge proofs are an essential building block in many privacy-preserving systems. However, implementing these proofs is tedious and error-prone. In this paper, we present zksk, a well-documented Python library for defining and computing sigma protocols: the most popular class of zero-knowledge proofs. In zksk, proofs compose: programmers can convert smaller proofs into building blocks that then can be combined into bigger proofs. zksk features a modern Python-based domain-specific language. This makes possible to define proofs without learning a new custom language, and to benefit from the rich Python syntax and ecosystem. The library is available at https://github.com/spring-epfl/zksk
Abstract Blockchain and blockchain‐based decentralised applications have been attracting increasing attention recently. In public blockchain systems, users usually connect to third‐party peers or run a peer to join the P2P blockchain network. However, connecting to unreliable blockchain peers will lead to resource waste and even loss of cryptocurrencies by repeated transactions. In order to select reliable blockchain peers, it is urgently needed to evaluate and predict their reliability of them. Faced with this problem, we propose hybrid blockchain reliability prediction (H‐BRP), a Hybrid Blockchain Reliability Prediction model, to extract the blockchain reliability factors and then make the personalised prediction for each user. Comprehensive experiments conducted on 100 blockchain requesters and 200 blockchain peers demonstrate the effectiveness of the proposed H‐BRP model. Further, the implementation and dataset of 2,000,000 test cases are released.
Thomas Durieux, João F. Ferreira, Rui Abreu, Pedro E. D. Cruz
Over the last few years, there has been substantial research on automated analysis, testing, and debugging of Ethereum smart contracts. However, it is not trivial to compare and reproduce that research. To address this, we present an empirical evaluation of 9 state-of-the-art automated analysis tools using two new datasets: i) a dataset of 69 annotated vulnerable smart contracts that can be used to evaluate the precision of analysis tools; and ii) a dataset with all the smart contracts in the Ethereum Blockchain that have Solidity source code available on Etherscan (a total of 47,518 contracts). The datasets are part of SmartBugs, a new extendable execution framework that we created to facilitate the integration and comparison between multiple analysis tools and the analysis of Ethereum smart contracts. We used SmartBugs to execute the 9 automated analysis tools on the two datasets. In total, we ran 428,337 analyses that took approximately 564 days and 3 hours, being the largest experimental setup to date both in the number of tools and in execution time. We found that only 42% of the vulnerabilities from our annotated dataset are detected by all the tools, with the tool Mythril having the higher accuracy (27%). When considering the largest dataset, we observed that 97% of contracts are tagged as vulnerable, thus suggesting a considerable number of false positives. Indeed, only a small number of vulnerabilities (and of only two categories) were detected simultaneously by four or more tools.
Ethereum is a distributed blockchain that can execute smart contracts, which inter-communicate and perform transactions automatically. The execution of smart contracts is paid in the form of gas, which is a monetary unit used in the Ethereum blockchain. The Ethereum Virtual Machine (EVM) provides the metering capability for smart contract execution. Instruction costs vary depending on the instruction type and the approximate computational resources required to execute the instruction on the network. The cost of gas is adjusted using transaction fees to ensure adequate payment of the network. In this work, we highlight the "real" economics of smart contracts. We show that the actual costs of executing smart contracts are disproportionate to the computational costs and that this gap is continuously widening. We show that the gas cost-model of the underlying EVM instruction-set is wrongly modeled. Specifically, the computational cost for the SLOAD instruction increases with the length of the blockchain. Our proposed performance model estimates gas usage and execution time of a smart contract at a given block-height. The new gas-cost model incorporates the block-height to eliminate irregularities in the Ethereum gas calculations. Our findings are based on extensive experiments over the entire history of the EVM blockchain.
The widespread recognition of the smart contracts has established their importance in the landscape of next generation blockchain technology. However, writing a correct smart contract is notoriously difficult. Moreover, once a state-changing transaction is confirmed by the network, the result is immutable. For this reason, it is crucial to perform a thorough testing of a smart contract application before its deployment. This paper's focus is on the test coverage criteria for smart contracts, which are objective rules that measure test quality. We analyze the unique characteristics of the Ethereum smart contract program model as compared to the conventional program model. To capture essential control flow behaviors of smart contracts, we propose the notions of whole transaction basis path set and bounded transaction interaction. The former is a limited set of linearly independent inter-procedural paths from which the potentially infinite paths of Ethereum transactions can be constructed by linear combination, while the latter is the permutations of transactions within a certain bound. Based on these two notions, we define a family of path-based test coverage criteria. Algorithms are given to the generation of coverage requirements. A case study is conducted to compare the effectiveness of the proposed test coverage criteria with random testing and statement coverage testing.
Scott Ruoti, Benjamin Kaiser, Arkady Yerukhimovich, Jeremy Clark · 5 authors
Bitcoin's success has led to significant interest in its underlying components, particularly Blockchain technology. Over 10 years after Bitcoin's initial release, the community still suffers from a lack of clarity regarding what properties defines Blockchain technology, its relationship to similar technologies, and which of its proposed use-cases are tenable and which are little more than hype. In this paper we answer four common questions regarding Blockchain technology: (1) what exactly is Blockchain technology, (2) what capabilities does it provide, and (3) what are good applications for Blockchain technology, and (4) how does it relate to other approache distributed technologies (e.g., distributed databases). We accomplish this goal by using grounded theory (a structured approach to gathering and analyzing qualitative data) to thoroughly analyze a large corpus of literature on Blockchain technology. This method enables us to answer the above questions while limiting researcher bias, separating thought leadership from peddled hype and identifying open research questions related to Blockchain technology. The audience for this paper is broad as it aims to help researchers in a variety of areas come to a better understanding of Blockchain technology and identify whether it may be of use in their own research.
It is crucial that smart contracts are tested thoroughly due to their immutable nature. Even small bugs in smart contracts can lead to huge monetary losses. However, testing is not enough; it is also important to ensure the quality and completeness of the tests. There are already several approaches that tackle this challenge with mutation testing, but their effectiveness is questionable since they only considered small contract samples. Hence, we evaluate the quality of smart contract mutation testing at scale. We choose the most promising of the existing (smart contract specific) mutation operators, analyse their effectiveness in terms of killability and highlight severe vulnerabilities that can be injected with the mutations. Moreover, we improve the existing mutation methods by introducing a novel killing condition that is able to detect a deviation in the gas consumption, i.e., in the monetary value that is required to perform transactions. This paper has a replication package at https://github.com/pieterhartel/Mutation-at-scale
IoT systems have enabled ubiquitous communication in physical spaces, making them smart Nowadays, there is an emerging concern about evaluating suspicious transactions in smart spaces. Suspicious transactions might have a logical structure, but they are not correct under the present contextual information of smart spaces. This research reviews suspicious transactions in smart spaces and evaluates the characteristics of blockchain technology to manage them. Additionally, this research presents a blockchain-based system model with the novel idea of iContracts (interactive contracts) to enable contextual evaluation through proof-of-provenance to detect suspicious transactions in smart spaces.
Blockchain platforms are coming into broad use for processing critical transactions among participants who have not established mutual trust. Many blockchains are programmable, supporting smart contracts, which maintain persistent state and support transactions that transform the state. Unfortunately, bugs in many smart contracts have been exploited by hackers. Obsidian is a novel programming language with a type system that enables static detection of bugs that are common in smart contracts today. Obsidian is based on a core calculus, Silica, for which we proved type soundness. Obsidian uses typestate to detect improper state manipulation and uses linear types to detect abuse of assets. We describe two case studies that evaluate Obsidian's applicability to the domains of parametric insurance and supply chain management, finding that Obsidian's type system facilitates reasoning about high-level states and ownership of resources. We compared our Obsidian implementation to a Solidity implementation, observing that the Solidity implementation requires much boilerplate checking and tracking of state, whereas Obsidian does this work statically.
Summary With the increasing popularity of blockchain technologies in recent years, blockchain‐based decentralized applications (DApps for short in this paper) have been rapidly developed and widely adopted in many areas, being a hot topic in both academia and industry. Despite of the importance of DApps, we still have quite little understanding of DApps along with its ecosystem. To bridge the knowledge gap, this paper presents the first comprehensive empirical study of blockchain‐based DApps to date, based on an extensive dataset of 995 Ethereum DApps and 29,846,075 transaction logs over them. We make a descriptive analysis of the popularity of DApps, summarize the patterns of how DApps use smart contracts to access the underlying blockchain, and explore the worth‐addressing issues of deploying and operating DApps. Based on the findings, we propose some implications for DApp users to select proper DApps, for DApp developers to improve the efficiency of DApps, and for blockchain vendors to enhance the support of DApps.
With the advent of blockchain technology, multiple research avenues and platforms for dialogue have opened up. However technology transfer to the pubic has not been implemented, such that regular public can access and make use of secure and decentralized software. Most blockchain solutions till date deal with financial applications or monetary transactions, which may not be helpful or be accessible to the general public, especially the lower levels of the financial society. Medi-Chain is a people-first medical blockchain with a usable desktop application and interface which makes use of cutting-edge blockchain technology along with BFT consensus protocols to ensure highly secure and private medical data records. This paper aims to bring about a change in how blockchains-as-a-service is perceived and how adoption of new technology is largely based on usability and ease of adoption.