Most languages are given an informal semantics until they are implemented, so the formal semantics comes later. Consequently, there are usually inconsistencies among the informal semantics, the implementation, and the formal semantics. IELE is an LLVM-like language for the blockchain that was specified formally and its implementation, a virtual machine, generated from the formal specification. Moreover, its design was based on problems observed formalizing the semantics of the Ethereum Virtual Machine (EVM) and from formally specifying and verifying EVM programs (also called “smart contracts”), so even the design decisions made for IELE are based on formal specifications. A compiler from Solidity, the predominant high-level language for smart contracts, to IELE has also been implemented, so Ethereum contracts can now also be executed on IELE. The virtual machine automatically generated from the semantics of IELE is shown to be competitive in terms of performance with the state of the art and hence can stand as the de facto implementation of the language in a production setting. Indeed, IOHK, a major blockchain company, is currently experimenting with the IELE VM in order to deploy it as its computational layer in a few months. This makes IELE the first practical language that is designed and implemented as a formal specification. It took only 10 man-months to develop IELE, which demonstrates that the programming language semantics field has reached a level of maturity that makes it appealing over the traditional, adhoc approach even for pragmatic reasons.
Florentin Guth, Valentin Wüstholz, Maria Christakis, Péter Müller
Smart contracts are programs that manage digital assets according to a certain protocol, expressing for instance the rules of an auction. Understanding the possible behaviors of a smart contract is difficult, which complicates development, auditing, and the post-mortem analysis of attacks. This paper presents the first specification mining technique for smart contracts. Our technique extracts the possible behaviors of smart contracts from contract executions recorded on a blockchain and expresses them as finite automata. A novel dependency analysis allows us to separate independent interactions with a contract. Our technique tunes the abstractions for the automata construction automatically based on configurable metrics, for instance, to maximize readability or precision. We implemented our technique for the Ethereum blockchain and evaluated its usability on several real-world contracts.
The historic rise of blockchain-based cryptocurrencies to over $327 billion in market capitalization has sparked significant research efforts studying their reliability, performance, and security. Bitcoin, the highest valued cryptocurrency, has received the most thorough scrutiny, with many studies analyzing its peer properties and network health. In contrast, the network layer for Ethereum, the second-largest cryptocurrency, has gone mostly ignored, even though it employs different algorithms for transaction propagation. \n\nIn this thesis, we perform timing analysis on transactions propagated through Ethereum networks to identify the origin nodes. We build a tool called TxSniper to verify our approach on Ethereum's main network. We find that we can identify the origin with a 70% probability; this method is not always effective due to presence of nodes running clients that use different implementations of transaction propagation.
Pietro Danzi, Anders E. Kalør, Čedomir Stefanović, Petar Popovski
The emerging blockchain protocols provide a decentralized architecture that is suitable of supporting Internet of Things (IoT) interactions. However, keeping a local copy of the blockchain ledger is infeasible for low-power and memory-constrained devices. For this reason, they are equipped with lightweight software implementations that only download the useful data structures, e.g. state of accounts, from the blockchain network, when they are updated. In this paper, we consider and analyze a novel scheme, implemented by the nodes of the blockchain network, which aggregates the blockchain data in periodic updates and further reduces the communication cost of the connected IoT devices. We show that the aggregation period should be selected based on the channel quality, the offered rate, and the statistics of updates of the useful data structures. The results, obtained for the Ethereum protocol, illustrate the benefits of the aggregation scheme in terms of a reduced duty cycle of the device, particularly for low signal-to-noise ratios, and the overall reduction of the amount of information transmitted in downlink (e.g., from the wireless base station to the IoT device). A potential application of the proposed scheme is to let the IoT device request more information than actually needed, hence increasing its privacy, while keeping the communication cost constant. In conclusion, our work is the first to provide rigorous guidelines for the design of lightweight blockchain protocols with wireless connectivity.
Arati Baliga, I Subhod, Pandurang Kamat, Siddhartha Chatterjee
Quorum is a permissioned blockchain platform built from the Ethereum codebase with adaptations to make it a permissioned consortium platform. It is one of the key contenders in the permissioned ledger space. Quorum supports confidentiality and privacy of smart contracts and transactions, and crash and Byzantine fault tolerant consensus algorithms. In this paper, we characterize the performance features of Quorum. We study the throughput and latency characteristics of Quorum with different workloads and consensus algorithms that it supports. Through a suite of micro-benchmarks, we explore how certain transaction and smart contract parameters can affect transaction latencies.
Constrained devices in IoT networks often require to outsource resource-heavy computations or data processing tasks. Currently, most of those jobs are done in the centralised cloud. However, with rapidly increasing number of devices and amount of produced data, edge computing represents a much more efficient solution decreasing the cost, the delay and improves users' privacy. To enable wide deployment of execution nodes at the edge, the requesting devices require a way to pay for submitted tasks. We present SPOC - a secure payment system for networks where nodes distrust each other. SPOC allows any node to execute tasks, includes result verification and enforce users' proper behaviour without 3rd parties, replication or costly proof of computations. We implement our system using Ethereum Smart Contracts and Intel SGX and present first evaluation proving its security and low usage cost.
One of the most important components in a public blockchain like Bitcoin and Ethereum is the authenticated data structure that keeps track of all block data, transactions, and the world state (account balance, smart contract states, etc.) Thanks to authenticated data structures, lightweight nodes only need to store authentication information and can delegate queries to those nodes with a full replica of data and the authenticated data structure. The lightweight nodes can trust the query results after verifying against the authentication information. It is also critical to have enough nodes in the network that are equipped with the authenticated data structure to ensure scalability and availability, which is especially important for public blockchains. Therefore, every public blockchain highly encourages users to download the authenticated data structure as the first step.\n\nFetching all elements from the entire authenticated data structure is a novel query type that has not gathered attention in the past. We describe this new emerging query type in the three-party authenticated data structure (ADS). We improve the design and implementation of the authenticated data structure so that the new query type is well-supported. We specifically apply the improvements to the Ethereum blockchain network. With our proposed ADS system in Ethereum, we improve Ethereum state synchronization performance by 216 times.
Francesco Bortolussi, Zeger Hoogeboom, Frank W. Takes
Cryptocurrencies such as Bitcoin and Ethereum have recently gained a lot of popularity, not only as a digital form of currency but also as an investment vehicle. Online marketplaces and exchanges allow users across the world to convert between dozens of different cryptocurrencies and regular currencies such as euros or dollars. Due to the novelty of this concept, the volatility of these markets and the differences in maturity and usage of particular marketplaces, currency pairs may appear at multiple marketplaces but at different trading prices. This paper proposes a novel algorithmic approach to take advantage of these mispricings and capitalize upon the pricing differences that exist between exchanges and currency pairs. To do so, we model each combination of a currency and a market as one node in a graph. A directed link between two nodes indicates that a conversion between these two currency/market pairs is possible. The weight of the link relates to the exchange rate of executing this particular currency exchange. To leverage the mispricings, we seek for cycles in the graph such that upon multiplying the weights of the links in the cycle, a value greater than 1 is found and thus a profit can be made. Our goal is to do this efficiently, without exhaustively enumerating all possible cycles in the graph. Therefore, we convert our data and address the problem in terms of finding minimum weight triangles in graphs with integer weights, for which efficient algorithms can be utilized. We experiment with parameter settings (heuristics) related to the conversion of exchange rate data into integer weight values. We show that our approach improves upon a reasonable baseline algorithm in terms of computation time. Furthermore, using a real-world dataset, we demonstrate how the obtained minimal weight cycles indeed unveil a number of currency exchange cycles that result in a net profit.
The recent emergence of cryptocurrencies such as Bitcoin and Ethereum has posed possible alternatives to global payments as well as financial assets around the globe, making investors and financial regulators aware of the importance of modeling them correctly. The Lvy's stable distribution is one of the attractive distributions that well describes the fat tails and scaling phenomena in economic systems. In this paper, we show that the behaviors of price fluctuations in emerging cryptocurrency markets can be characterized by a non-Gaussian Lvy's stable distribution with ' 1:4 under certain conditions on time intervals ranging roughly from 30 min to 4 h. Our arguments are developed under quantitative valuation defined as a distance function using the Parseval's relation in addition to the theoretical background of the General Central Limit Theorem (GCLT). We also discuss the model-fitting for returns by employing the method based on likelihood ratios. Even though the cubic power-law model is a better fitting model than the Lvy's stable model in the tail part of returns, the Lvy's stable model outperforms the fit for the entire and wider range of returns. Our approach can be extended for further analysis of statistical properties and contribute to developing proper applications for financial modeling.
The paper presents Tendermint, a new protocol for ordering events in a distributed network under adversarial conditions. More commonly known as Byzantine Fault Tolerant (BFT) consensus or atomic broadcast, the problem has attracted significant attention in recent years due to the widespread success of blockchain-based digital currencies, such as Bitcoin and Ethereum, which successfully solved the problem in a public setting without a central authority. Tendermint modernizes classic academic work on the subject and simplifies the design of the BFT algorithm by relying on a peer-to-peer gossip protocol among nodes.
Decentralized cryptocurrencies feature the use of blockchain to transfer values among peers on networks without central agency. Smart contracts are programs running on top of the blockchain consensus protocol to enable people make agreements while minimizing trusts. Millions of smart contracts have been deployed in various decentralized applications. The security vulnerabilities within those smart contracts pose significant threats to their applications. Indeed, many critical security vulnerabilities within smart contracts on Ethereum platform have caused huge financial losses to their users. In this work, we present ContractFuzzer, a novel fuzzer to test Ethereum smart contracts for security vulnerabilities. ContractFuzzer generates fuzzing inputs based on the ABI specifications of smart contracts, defines test oracles to detect security vulnerabilities, instruments the EVM to log smart contracts runtime behaviors, and analyzes these logs to report security vulnerabilities. Our fuzzing of 6991 smart contracts has flagged more than 459 vulnerabilities with high precision. In particular, our fuzzing tool successfully detects the vulnerability of the DAO contract that leads to USD 60 million loss and the vulnerabilities of Parity Wallet that have led to the loss of USD 30 million and the freezing of USD 150 million worth of Ether.
Blockchain platforms, such as Ethereum, allow a set of actors to maintain a ledger of transactions without relying on a central authority and to deploy scripts, called smart contracts, that are executed whenever certain transactions occur. These features can be used as basic building blocks for executing collaborative business processes between mutually untrusting parties. However, implementing business processes using the low-level primitives provided by blockchain platforms is cumbersome and error-prone. In contrast, established business process management systems, such as those based on the standard Business Process Model and Notation (BPMN), provide convenient abstractions for rapid development of process-oriented applications. This article demonstrates how to combine the advantages of a business process management system with those of a blockchain platform. The article introduces a blockchain-based BPMN execution engine, namely Caterpillar. Like any BPMN execution engine, Caterpillar supports the creation of instances of a process model and allows users to monitor the state of process instances and to execute tasks thereof. The specificity of Caterpillar is that the state of each process instance is maintained on the (Ethereum) blockchain and the workflow routing is performed by smart contracts generated by a BPMN-to-Solidity compiler. The Caterpillar compiler supports a large array of BPMN constructs, including subprocesses, multi-instances activities and event handlers. The paper describes the architecture of Caterpillar, and the interfaces it provides to support the monitoring of process instances, the allocation and execution of work items, and the execution of service tasks.
Blockchain platforms, such as Ethereum, allow a set of actors to maintain a\nledger of transactions without relying on a central authority and to deploy\nscripts, called smart contracts, that are executed whenever certain\ntransactions occur. These features can be used as basic building blocks for\nexecuting collaborative business processes between mutually untrusting parties.\nHowever, implementing business processes using the low-level primitives\nprovided by blockchain platforms is cumbersome and error-prone. In contrast,\nestablished business process management systems, such as those based on the\nstandard Business Process Model and Notation (BPMN), provide convenient\nabstractions for rapid development of process-oriented applications. This\narticle demonstrates how to combine the advantages of a business process\nmanagement system with those of a blockchain platform. The article introduces a\nblockchain-based BPMN execution engine, namely Caterpillar. Like any BPMN\nexecution engine, Caterpillar supports the creation of instances of a process\nmodel and allows users to monitor the state of process instances and to execute\ntasks thereof. The specificity of Caterpillar is that the state of each process\ninstance is maintained on the (Ethereum) blockchain and the workflow routing is\nperformed by smart contracts generated by a BPMN-to-Solidity compiler. The\nCaterpillar compiler supports a large array of BPMN constructs, including\nsubprocesses, multi-instances activities and event handlers. The paper\ndescribes the architecture of Caterpillar, and the interfaces it provides to\nsupport the monitoring of process instances, the allocation and execution of\nwork items, and the execution of service tasks.\n
Hao Dai, H. P. Young, Thomas J S Durant, Guannan Gong · 8 authors
The governance of data used for biomedical research and clinical trials is an important requirement for generating accurate results. To improve the visibility of data quality and analysis, we developed TrialChain, a blockchain-based platform that can be used to validate data integrity from large, biomedical research studies. We implemented a private blockchain using the MultiChain platform and integrated it with a data science platform deployed within a large research center. An administrative web application was built with Python to manage the platform, which was built with a microservice architecture using Docker. The TrialChain platform was integrated during data acquisition into our existing data science platform. Using NiFi, data were hashed and logged within the local blockchain infrastructure. To provide public validation, the local blockchain state was periodically synchronized to the public Ethereum network. The use of a combined private/public blockchain platform allows for both public validation of results while maintaining additional security and lower cost for blockchain transactions. Original data and modifications due to downstream analysis can be logged within TrialChain and data assets or results can be rapidly validated when needed using API calls to the platform. The TrialChain platform provides a data governance solution to audit the acquisition and analysis of biomedical research data. The platform provides cryptographic assurance of data authenticity and can also be used to document data analysis.
Patrick G. Sylim, Fang Liu, Alvin Marcelo, Paul Fontelo
BACKGROUND: Drug counterfeiting is a global problem with significant risks to consumers and the general public. In the Philippines, 30% of inspected drug stores in 2003 were found with substandard/spurious/falsely-labeled/falsified/counterfeit drugs. The economic burden on the population drug expenditures and on governments is high. The Philippine Food and Drug Administration (FDA) encourages the public to check the certificates of product registration and report any instances of counterfeiting. The National Police of Philippines responds to such reports through a special task force. However, no literature on its impact on the distribution of such drugs were found. Blockchain technology is a cryptographic ledger that is allegedly immutable through repeated sequential hashing and fault-tolerant through a consensus algorithm. This project will develop and test a pharmacosurveillance blockchain system that will support information sharing along the official drug distribution network. OBJECTIVE: This study aims to develop a pharmacosurveillance blockchain system and test its functions in a simulated network. METHODS: We are developing a Distributed Application (DApp) that will run on smart contracts, employing Swarm as the Distributed File System (DFS). Two instances will be developed: one for Ethereum and another for Hyperledger Fabric. The proof-of-work (PoW) consensus algorithm of Ethereum will be modified into a delegated proof-of-stake (DPoS) or practical Byzantine fault tolerance (PBFT) consensus algorithm as it is scalable and fits the drug supply chain environment. The system will adopt the GS1 pedigree standard and will satisfy the data points in the data standardization guidelines from the US FDA. Simulations will use the following 5 nodes: for FDA, manufacturer, wholesaler, retailer, and the consumer portal. RESULTS: Development is underway. The design of the system will place FDA in a supervisory data verification role, with each pedigree type-specific data source serving a primary data verification role. The supply chain process will be initiated by the manufacturer, with recursive verification for every transaction. It will allow consumers to scan a code printed on the receipt of their purchases to review the drug distribution history. CONCLUSIONS: Development and testing will be conducted in a simulated network, and thus, results may differ from actual practice. The project being proposed is disruptive; once tested, the team intends to engage the Philippine FDA to discuss implementation plans and formulate policies to facilitate adoption and sustainability. REGISTERED REPORT IDENTIFIER: RR1-10.2196/10163.
This letter questions the true nature (true versus spurious) of the Long Range Dependence (LRD) behavior observed in the returns and volatility series of four Cryptocurrencies (CC). Using a robust approach, this letter shows that the LRD behavior exhibited by the returns and volatility series of Bitcoin, Litecoin, and Ripple is a true behavior, and not a statistical artifact. As for Ethereum, the results show that the true LRD is only supported for the volatility series. Our results confirm the inefficiency of all the considered markets, with the exception of Ethereum.
Paolo Missier, Shaimaa Bajoudah, Angelo Capossele, Andrea Gaglione · 5 authors
Internet of Things (IoT) data are increasingly viewed as a new form of massively distributed and large scale digital assets, which are continuously generated by millions of connected devices. The real value of such assets can only be realized by allowing IoT data trading to occur on a marketplace that rewards every single producer and consumer, at a very granular level. Crucially, we believe that such a marketplace should not be owned by anybody, and should instead fairly and transparently self-enforce a well defined set of governance rules. In this paper we address some of the technical challenges involved in realizing such a marketplace. We leverage emerging blockchain technologies to build a decentralized, trusted, transparent and open architecture for IoT traffic metering and contract compliance, on top of the largely adopted IoT brokered data infrastructure. We discuss an Ethereum-based prototype implementation and experimentally evaluate the overhead cost associated with Smart Contract transactions, concluding that a viable business model can indeed be associated with our technical approach.
Gihan J. Mendis, Moein Sabounchi, Wei Jin, Rigoberto Roche
Deep learning algorithms have recently gained attention due to their inherent capabilities and the application opportunities that they provide. Two of the main reasons for the success of deep learning methods are the availability of processing power and big data. Both of these two are expensive and rare commodities that present limitations to the usage and implementation of deep learning. Decentralization of the processing and data is one of the most prevalent solutions for these issues. This paper proposes a cooperative decentralized deep learning architecture. The contributors can train deep learning models with private data and share them to the cooperative data-driven applications initiated elsewhere. Shared models are fused together to obtain a better model. In this work, the contributors can both design their own models or train the models provided by the initiator. In order to utilize an efficient decentralized learning algorithm, blockchain technology is incorporated as a method of creating an incentive-compatible market. In the proposed method, Ethereum blockchain's scripting capabilities are employed to devise a decentralized deep learning mechanism, which provides much higher, collective processing power and grants access to large amounts of data, which would be otherwise inaccessible. The technical description of the mechanism is described and the simulation results are presented.
Regio A. Michelin, Ali Dorri, Roben Castagna Lunardi, Marco Steger · 7 authors
There is increased interest in smart vehicles acting as both data consumers and producers in smart cities. Vehicles can use smart city data for decision-making, such as dynamic routing based on traffic conditions. Moreover, the multitude of embedded sensors in vehicles can collectively produce a rich data set of the urban landscape that can be used to provide a range of services. Key to the success of this vision is a scalable and private architecture for trusted data sharing. This paper proposes a framework called SpeedyChain, that leverages blockchain technology to allow smart vehicles to share their data while maintaining privacy, integrity, resilience and non-repudiation in a decentralized, and tamper-resistant manner. Differently from traditional blockchain usage (e.g., Bitcoin and Ethereum), the proposed framework uses a blockchain design that decouples the data stored in the transactions from the block header, thus allowing for fast addition of data to the blocks. Furthermore, an expiration time for each block to avoid large sized blocks is proposed. This paper also presents an evaluation of the proposed framework in a network emulator to demonstrate its benefits.
Blockchain and Cryptocurrencies are gaining unprecedented popularity and understanding. Meanwhile, Ethereum is gaining a significant popularity in the blockchain community, mainly due to the fact that it is designed in a way that enables developers to write smart contract and decentralized applications (Dapps). This new paradigm of applications opens the door to many possibilities and opportunities. However, the security of Ethereum smart contracts has not received much attention; several Ethereum smart contracts malfunctioning have recently been reported. Unlike many previous works that have applied static and dynamic analyses to find bugs in smart contracts, we do not attempt to define and extract any features; instead we focus on reducing the expert's labor costs. We first present a new in-depth analysis of potential attacks methodology and then translate the bytecode of solidity into RGB color code. After that, we transform them to a fixed-sized encoded image. Finally, the encoded image is fed to convolutional neural network (CNN) for automatic feature extraction and learning, detecting compiler bugs of Ethereum smart contract.
This article evaluates the legal framework of cryptocurrency in various countries. The new currency instrument is abstract currencies. They are currencies in the sense that they can be exchanged peer-to-peer. They are representations of numbers, i.e. abstract objects. An abstract currency system is a self-enforcing system of property rights over an abstract instrument which gives its owners the freedom to use and the right to exclude others from using the instrument. Cryptocurrency or virtual currency is a cryptographically protected, decentralized digital currency used as a means of exchange. Due to the development of new technologies and innovations, the rate of use of virtual currency is rapidly increasing throughout the globe, replacing not only cash payments and payments by bank transfer, but also electronic cash payments. Among the best-known representatives of cryptocurrencies are Bitcoin, Litecoin and Ethereum. Legal scholars have not yet reached a consensus regarding the nature and legal status of virtual currency. Virtual currency possesses the nature of obligations righ ts as well as property rights, since it may be both a means of payment and a commodity. Depending on the country, the approach to cryptocurrencies may be different. Today there is already an international cryptocurrency community that does not have a single coordinating center. Only progressive jurisdiction and state regulation of cryptocurrency activity will allow the creation of the conditions that will ensure the implementation of legitimate and safe cryptocurrency relations.
Decentralized Ledger Technology, popularized by the Bitcoin network, aims to keep track of a ledger of valid transactions between agents of a virtual economy without a central institution for coordination. In order to keep track of a faithful and accurate list of transactions, the ledger is broadcast and replicated across machines in a peer-to-peer network. To enforce validity of transactions in the ledger (i.e., no negative balance or double spending), the network as a whole coordinates to accept or reject new transactions based on a set of rules aiming to detect and block operations of malicious agents (i.e., Byzantine attacks). Consensus protocols are particularly important to coordinate operation of the network, since they are used to reconcile potentially conflicting versions of the ledger. Regardless of architecture and consensus mechanism used, resulting economic networks remain largely similar, with economic agents driven by incentives under a set of rules. Due to the intense activity in this area, proper mathematical frameworks to model and analyze behavior of blockchain-enabled systems are essential. In this paper, we address this need and provide the following contributions: (i) we establish a formal framework, with tools from dynamical systems theory, to mathematically describe core concepts in blockchain-enabled networks, (ii) we apply this framework to the Bitcoin network and recover its key properties, and (iii) we connect our modeling framework with powerful tools from control engineering, such as Lyapunov-like functions, to properly engineer economic systems with provable properties. Apart from the aforementioned contributions, the mathematical framework herein proposed lays a foundation for engineering more general economic systems built on emerging Turing complete networks, such as the Ethereum network, through which complex alternative economic models are explored.
This article intention was to set up the big picture of all 1,639 cryptocurrencies up and give a policy recommendation for Thai government. Hence, there were three following objectives as follows: 1) to investigate the state of the art of all cryptocurencies in the source of Code / Forking due to limitation of number of pages 2) to identify the best practice of cryptocurrency, and 3) to study the role of General Prayuth Chan-o-cha’s government towards cryptocurrency. Documentary research and descriptive statistics like frequency and percentage were used in this study. The findings found that there were twelve groups of qualified cryptocurrencies in CoinMarketCap, led by two well-known giant family of crypto market, Ethereum (35.5%) and Bitcoin (16.1%). Then, the best practices were on the provision of coins or tokens, twelve techniques for managing blokchain (such as Blockchainas-a Service), blocktime was between 0.03 and 30 minutes with Mean = 1.96, S.D. = 2.29 whereas TPS was between 0 - 1,400,000 with Mean = 1341.87 and S.D. = 36021.52, most of cryptocurrencies had their own Web Site (95.8%) and E-mail (78.8%), coding played a big role in cryptocurrency such as C . Last, cryptocurrency had both open and hidden-and-dark faces. In the open face, tax, law, people’s identification will be useful. In contrary to the open side, setting an autonomous public organization is one and only one solution for all cryptocentric affairs.
Growing consumer awareness as well as manufacturers' internal quality requirements lead to novel demands on supply chain traceability. Existing centralized solutions suffer from isolated data storage and lacking trust when multiple parties are involved. Decentralized blockchain-based approaches attempt to overcome these shortcomings by creating digital representations of physical goods to facilitate tracking across multiple entities. However, they currently do not capture the transformation of goods in manufacturing processes. Therefore, the relation between ingredients and product is lost, limiting the ability to trace a product's provenance. We propose a blockchain-based supply chain traceability system using smart contracts. In such contracts, manufacturers define the composition of products in the form of recipes. Each ingredient of the recipe is a non-fungible token that corresponds to a batch of physical goods. When the recipe is applied, its ingredients are consumed and a new token is produced. This mechanism preserves the traceability of product transformations. The system is implemented for the Ethereum Virtual Machine and is applicable to any blockchain configuration that supports it. Our evaluation reveals that the gas costs scale linearly with the number of products considered in the system. This leads to the conclusion that the solution can handle complex use cases.