There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

In recent years, the rapid development of cryptocurrencies and their underlying blockchain technology has revived Szabo’s original idea of smart contracts, i.e., computer protocols that are designed to automatically facilitate, verify, and enforce the negotiation and implementation of digital contracts without central authorities. Smart contracts can find a wide spectrum of potential application scenarios in the digital economy and intelligent industries, including financial services, management, healthcare, and Internet of Things, among others, and also have been integrated into the mainstream blockchain-based development platforms, such as Ethereum and Hyperledger. However, smart contracts are still far from mature, and major technical challenges such as security and privacy issues are still awaiting further research efforts. For instance, the most notorious case might be “The DAO Attack” in June 2016, which led to more than $50 million Ether transferred into an adversary’s account. In this paper, we strive to present a systematic and comprehensive overview of blockchain-enabled smart contracts, aiming at stimulating further research toward this emerging research area. We first introduced the operating mechanism and mainstream platforms of blockchain-enabled smart contracts, and proposed a research framework for smart contracts based on a novel six-layer architecture. Second, both the technical and legal challenges, as well as the recent research progresses, are listed. Third, we presented several typical application scenarios. Toward the end, we discussed the future development trends of smart contracts. This paper is aimed at providing helpful guidance and reference for future research efforts.

Blockchain-Enabled Smart Contracts: Architecture, Applications, and Future Trends

An overview on smart contracts : Challenges, advances and platforms

Smart contract, a term which was originally coined to refer to the automation of legal contracts in general, has recently seen much interest due to the advent of blockchain technology. Recently, the term is popularly used to refer to low-level code scripts running on a blockchain platform. Our study focuses exclusively on this subset of smart contracts. Such smart contracts have increasingly been gaining ground, finding numerous important applications (e.g., crowdfunding) in the real world. Despite the increasing popularity, smart contract development still remains somewhat a mystery to many developers largely due to its special design and applications. Are there any differences between smart contract development and traditional software development? What kind of challenges are faced by developers during smart contract development? Questions like these are important but have not been explored by researchers yet. In this paper, we performed an exploratory study to understand the current state and potential challenges developers are facing in developing smart contracts on blockchains, with a focus on Ethereum (the most popular public blockchain platform for smart contracts). Toward this end, we conducted this study in two phases. In the first phase, we conducted semi-structured interviews with 20 developers from GitHub and industry professionals who are working on smart contracts. In the second phase, we performed a survey on 232 practitioners to validate the findings from the interviews. Our interview and survey results revealed several major challenges developers are facing during smart contract development: (1) there is no effective way to guarantee the security of smart contract code; (2) existing tools for development are still very basic; (3) the programming languages and the virtual machines still have a number of limitations; (4) performance problems are hard to handle under resource constrained running environment; and (5) online resources (including advanced/updated documents and community support) are still limited. Our study suggests several directions that researchers and practitioners can work on to help improve developers’ experience on developing high-quality smart contracts.

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Smart Contract Development: Challenges and Opportunities

Existing blockchain systems scale poorly because of their distributed consensus protocols. Current attempts at improving blockchain scalability are limited to cryptocurrency. Scaling blockchain systems under general workloads (i.e., non-cryptocurrency applications) remains an open question. This work takes a principled approach to apply sharding to blockchain systems in order to improve their transaction throughput at scale. This is challenging, however, due to the fundamental difference in failure models between databases and blockchain. To achieve our goal, we first enhance the performance of Byzantine consensus protocols, improving individual shards' throughput. Next, we design an efficient shard formation protocol that securely assigns nodes into shards. We rely on trusted hardware, namely Intel SGX, to achieve high performance for both consensus and shard formation protocol. Third, we design a general distributed transaction protocol that ensures safety and liveness even when transaction coordinators are malicious. Finally, we conduct an extensive evaluation of our design both on a local cluster and on Google Cloud Platform. The results show that our consensus and shard formation protocols outperform state-of-the-art solutions at scale. More importantly, our sharded blockchain reaches a high throughput that can handle Visa-level workloads, and is the largest ever reported in a realistic environment.

Towards Scaling Blockchain Systems via Sharding

Modern cryptocurrency systems, such as Ethereum, permit complex financial transactions through scripts called smart contracts. These smart contracts are executed many, many times, always without real concurrency. First, all smart contracts are serially executed by miners before appending them to the blockchain. Later, those contracts are serially re-executed by validators to verify that the smart contracts were executed correctly by miners. Serial execution limits system throughput and fails to exploit today's concurrent multicore and cluster architectures. Nevertheless, serial execution appears to be required: contracts share state, and contract programming languages have a serial semantics. This paper presents a novel way to permit miners and validators to execute smart contracts in parallel, based on techniques adapted from software transactional memory. Miners execute smart contracts speculatively in parallel, allowing non-conflicting contracts to proceed concurrently, and "discovering" a serializable concurrent schedule for a block's transactions, This schedule is captured and encoded as a deterministic fork-join program used by validators to re-execute the miner's parallel schedule deterministically but concurrently. Smart contract benchmarks run on a JVM with ScalaSTM show that a speedup of 1.33x can be obtained for miners and 1.69x for validators with just three concurrent threads.

https://dl.acm.org/doi/pdf/10.1145/3087801.3087835

Adding Concurrency to Smart Contracts

Modern cryptocurrency systems, such as the Ethereum project, permit complex financial transactions through scripts called smart contracts. These smart contracts are executed many, many times, always without real concurrency. First, all smart contracts are serially executed by miners before appending them to the blockchain. Later, those contracts are serially reexecuted by validators to verify that the smart contracts were executed correctly by miners. Serial execution limits system throughput and fails to exploit today’s concurrent multicore and cluster architectures. Nevertheless, serial execution appears to be required: contracts share state, and contract programming languages have a serial semantics. This paper presents a novel way to permit miners and validators to execute smart contracts in parallel, based on techniques adapted from software transactional memory. Miners execute smart contracts speculatively in parallel, allowing non-conflicting contracts to proceed concurrently, and “discovering” a serializable concurrent schedule for a block’s transactions. This schedule is captured and encoded as a deterministic fork-join program used by validators to re-execute the miner’s parallel schedule deterministically but concurrently.

Modern cryptocurrency systems, such as the Ethereum project, permit complex financial transactions through scripts called smart contracts. These smart contracts are executed many, many times, always without real concurrency. First, all smart contracts are serially executed by miners before appending them to the blockchain. Later, those contracts are serially re-executed by validators to verify that the smart contracts were executed correctly by miners. Serial execution limits system throughput and fails to exploit today’s concurrent multicore and cluster architectures. Nevertheless, serial execution appears to be required: contracts share state, and contract programming languages have a serial semantics. This paper presents a novel way to permit miners and validators to execute smart contracts in parallel, based on techniques adapted from software transactional memory. Miners execute smart contracts speculatively in parallel, allowing non-conflicting contracts to proceed concurrently, and “discovering” a serializable concurrent schedule for a block’s transactions, This schedule is captured and encoded as a deterministic fork-join program used by validators to re-execute the miner’s parallel schedule deterministically but concurrently. We have proved that the validator’s execution is equivalent to miner’s execution. Smart contract benchmarks run on a JVM with ScalaSTM show that a speedup of 1.39$$\times $$ can be obtained for miners and 1.59$$\times $$ for validators with just three concurrent threads.

https://par.nsf.gov/servlets/purl/10206401

Adding concurrency to smart contracts

We propose a way to reconcile the apparent contradiction between the immutability of idealized smart contracts and the real-world need to update contracts to fix bugs and oversights. Our proposal is to raise the contract’s level of abstraction to guarantee a specification $\varphi $ instead of a particular implementation of that specification. A combination of proof-carrying code and proof-aware consensus allows contract implementations to be updated as needed, but so as to guarantee that $\varphi $ cannot be violated by any future upgrade.

Proof-Carrying Smart Contracts

Most STM systems are poorly equipped to support libraries of concurrent data structures. One reason is that they typically detect conflicts by tracking transactions' read sets and write sets, an approach that often leads to false conflicts. A second is that existing data structures and libraries often need to be rewritten from scratch to support transactional conflict detection and rollback. This paper introduces Proust, a framework for the design and implementation of transactional data structures. Proust is designed to maximize re-use of existing well-engineered by providing transactional "wrappers" to make existing thread-safe concurrent data structures transactional. Proustian objects are also integrated with an underling STM system, allowing them to take advantage of well-engineered STM conflict detection mechanisms. Proust generalizes and unifies prior approaches such as boosting and predication.

Thomas D. Dickerson

Papers

Adding Concurrency to Smart Contracts

Adding Concurrency to Smart Contracts

Adding concurrency to smart contracts

Proof-Carrying Smart Contracts

Proust: A Design Space for Highly-Concurrent Transactional Data Structures