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Ethereum white paper pdf espanol

ethereum white paper pdf espanol

Home · Ethereum Whitepaper · Ethereum Introduction · Uses: DAOs and dapps · Getting Ether · FAQs · Design Rationale · EVM intro: Ethereum Yellow Paper. An auto- generated PDF is located at duhn.apnetvdesiserial.com io/yellowpaper/duhn.apnetvdesiserial.com References. Jacob Aron. BitCoin software finds new life. New Scientist. For example, two users can trade bitcoins for ether (or any two tokens on two different ledgers) using AXC transactions, even though Bitcoin and Ethereum are. ARE CRYPTO DEAD NOV 2018 Можно сделать с обеих и, к. То же перерабатывается совсем пластмассовых бутылках. При этом брать продукты 7 860. При этом батарей производятся - компьютер каждый год.

However, the scripting language as implemented in Bitcoin has several important limitations:. Thus, we see three approaches to building advanced applications on top of cryptocurrency: building a new blockchain, using scripting on top of Bitcoin, and building a meta-protocol on top of Bitcoin. Building a new blockchain allows for unlimited freedom in building a feature set, but at the cost of development time, bootstrapping effort and security. Using scripting is easy to implement and standardize, but is very limited in its capabilities, and meta-protocols, while easy, suffer from faults in scalability.

With Ethereum, we intend to build an alternative framework that provides even larger gains in ease of development as well as even stronger light client properties, while at the same time allowing applications to share an economic environment and blockchain security. The intent of Ethereum is to create an alternative protocol for building decentralized applications, providing a different set of tradeoffs that we believe will be very useful for a large class of decentralized applications, with particular emphasis on situations where rapid development time, security for small and rarely used applications, and the ability of different applications to very efficiently interact, are important.

Ethereum does this by building what is essentially the ultimate abstract foundational layer: a blockchain with a built-in Turing-complete programming language, allowing anyone to write smart contracts and decentralized applications where they can create their own arbitrary rules for ownership, transaction formats and state transition functions. A bare-bones version of Namecoin can be written in two lines of code, and other protocols like currencies and reputation systems can be built in under twenty.

Smart contracts, cryptographic "boxes" that contain value and only unlock it if certain conditions are met, can also be built on top of the platform, with vastly more power than that offered by Bitcoin scripting because of the added powers of Turing-completeness, value-awareness, blockchain-awareness and state.

In Ethereum, the state is made up of objects called "accounts", with each account having a byte address and state transitions being direct transfers of value and information between accounts. An Ethereum account contains four fields:. In general, there are two types of accounts: externally owned accounts , controlled by private keys, and contract accounts , controlled by their contract code. An externally owned account has no code, and one can send messages from an externally owned account by creating and signing a transaction; in a contract account, every time the contract account receives a message its code activates, allowing it to read and write to internal storage and send other messages or create contracts in turn.

The term "transaction" is used in Ethereum to refer to the signed data package that stores a message to be sent from an externally owned account. Transactions contain:. The first three are standard fields expected in any cryptocurrency. The data field has no function by default, but the virtual machine has an opcode using which a contract can access the data; as an example use case, if a contract is functioning as an on-blockchain domain registration service, then it may wish to interpret the data being passed to it as containing two "fields", the first field being a domain to register and the second field being the IP address to register it to.

The contract would read these values from the message data and appropriately place them in storage. In order to prevent accidental or hostile infinite loops or other computational wastage in code, each transaction is required to set a limit to how many computational steps of code execution it can use.

The fundamental unit of computation is "gas"; usually, a computational step costs 1 gas, but some operations cost higher amounts of gas because they are more computationally expensive, or increase the amount of data that must be stored as part of the state.

There is also a fee of 5 gas for every byte in the transaction data. The intent of the fee system is to require an attacker to pay proportionately for every resource that they consume, including computation, bandwidth and storage; hence, any transaction that leads to the network consuming a greater amount of any of these resources must have a gas fee roughly proportional to the increment. Contracts have the ability to send "messages" to other contracts.

Messages are virtual objects that are never serialized and exist only in the Ethereum execution environment. A message contains:. Essentially, a message is like a transaction, except it is produced by a contract and not an external actor. A message is produced when a contract currently executing code executes the CALL opcode, which produces and executes a message. Like a transaction, a message leads to the recipient account running its code.

Thus, contracts can have relationships with other contracts in exactly the same way that external actors can. Note that the gas allowance assigned by a transaction or contract applies to the total gas consumed by that transaction and all sub-executions. For example, if an external actor A sends a transaction to B with gas, and B consumes gas before sending a message to C, and the internal execution of C consumes gas before returning, then B can spend another gas before running out of gas.

For example, suppose that the contract's code is:. Note that in reality the contract code is written in the low-level EVM code; this example is written in Serpent, one of our high-level languages, for clarity, and can be compiled down to EVM code. Suppose that the contract's storage starts off empty, and a transaction is sent with 10 ether value, gas, 0. The process for the state transition function in this case is as follows:. If there was no contract at the receiving end of the transaction, then the total transaction fee would simply be equal to the provided GASPRICE multiplied by the length of the transaction in bytes, and the data sent alongside the transaction would be irrelevant.

Note that messages work equivalently to transactions in terms of reverts: if a message execution runs out of gas, then that message's execution, and all other executions triggered by that execution, revert, but parent executions do not need to revert. This means that it is "safe" for a contract to call another contract, as if A calls B with G gas then A's execution is guaranteed to lose at most G gas.

Finally, note that there is an opcode, CREATE , that creates a contract; its execution mechanics are generally similar to CALL , with the exception that the output of the execution determines the code of a newly created contract. The code in Ethereum contracts is written in a low-level, stack-based bytecode language, referred to as "Ethereum virtual machine code" or "EVM code".

The code consists of a series of bytes, where each byte represents an operation. In general, code execution is an infinite loop that consists of repeatedly carrying out the operation at the current program counter which begins at zero and then incrementing the program counter by one, until the end of the code is reached or an error or STOP or RETURN instruction is detected. The operations have access to three types of space in which to store data:.

The code can also access the value, sender and data of the incoming message, as well as block header data, and the code can also return a byte array of data as an output. The formal execution model of EVM code is surprisingly simple. For example, ADD pops two items off the stack and pushes their sum, reduces gas by 1 and increments pc by 1, and SSTORE pushes the top two items off the stack and inserts the second item into the contract's storage at the index specified by the first item.

Although there are many ways to optimize Ethereum virtual machine execution via just-in-time compilation, a basic implementation of Ethereum can be done in a few hundred lines of code. The Ethereum blockchain is in many ways similar to the Bitcoin blockchain, although it does have some differences.

The main difference between Ethereum and Bitcoin with regard to the blockchain architecture is that, unlike Bitcoin, Ethereum blocks contain a copy of both the transaction list and the most recent state. Aside from that, two other values, the block number and the difficulty, are also stored in the block. The basic block validation algorithm in Ethereum is as follows:.

The approach may seem highly inefficient at first glance, because it needs to store the entire state with each block, but in reality efficiency should be comparable to that of Bitcoin. The reason is that the state is stored in the tree structure, and after every block only a small part of the tree needs to be changed.

Thus, in general, between two adjacent blocks the vast majority of the tree should be the same, and therefore the data can be stored once and referenced twice using pointers ie. A special kind of tree known as a "Patricia tree" is used to accomplish this, including a modification to the Merkle tree concept that allows for nodes to be inserted and deleted, and not just changed, efficiently. Additionally, because all of the state information is part of the last block, there is no need to store the entire blockchain history - a strategy which, if it could be applied to Bitcoin, can be calculated to provide x savings in space.

A commonly asked question is "where" contract code is executed, in terms of physical hardware. This has a simple answer: the process of executing contract code is part of the definition of the state transition function, which is part of the block validation algorithm, so if a transaction is added into block B the code execution spawned by that transaction will be executed by all nodes, now and in the future, that download and validate block B.

In general, there are three types of applications on top of Ethereum. The first category is financial applications, providing users with more powerful ways of managing and entering into contracts using their money. This includes sub-currencies, financial derivatives, hedging contracts, savings wallets, wills, and ultimately even some classes of full-scale employment contracts. The second category is semi-financial applications, where money is involved but there is also a heavy non-monetary side to what is being done; a perfect example is self-enforcing bounties for solutions to computational problems.

Finally, there are applications such as online voting and decentralized governance that are not financial at all. On-blockchain token systems have many applications ranging from sub-currencies representing assets such as USD or gold to company stocks, individual tokens representing smart property, secure unforgeable coupons, and even token systems with no ties to conventional value at all, used as point systems for incentivization.

Token systems are surprisingly easy to implement in Ethereum. The key point to understand is that all a currency, or token system, fundamentally is, is a database with one operation: subtract X units from A and give X units to B, with the proviso that i A had at least X units before the transaction and 2 the transaction is approved by A. All that it takes to implement a token system is to implement this logic into a contract. The basic code for implementing a token system in Serpent looks as follows:.

This is essentially a literal implementation of the "banking system" state transition function described further above in this document. A few extra lines of code need to be added to provide for the initial step of distributing the currency units in the first place and a few other edge cases, and ideally a function would be added to let other contracts query for the balance of an address. But that's all there is to it. Theoretically, Ethereum-based token systems acting as sub-currencies can potentially include another important feature that on-chain Bitcoin-based meta-currencies lack: the ability to pay transaction fees directly in that currency.

The way this would be implemented is that the contract would maintain an ether balance with which it would refund ether used to pay fees to the sender, and it would refill this balance by collecting the internal currency units that it takes in fees and reselling them in a constant running auction.

Users would thus need to "activate" their accounts with ether, but once the ether is there it would be reusable because the contract would refund it each time. Financial derivatives are the most common application of a "smart contract", and one of the simplest to implement in code. The simplest way to do this is through a "data feed" contract maintained by a specific party eg. NASDAQ designed so that that party has the ability to update the contract as needed, and providing an interface that allows other contracts to send a message to that contract and get back a response that provides the price.

Given that critical ingredient, the hedging contract would look as follows:. Such a contract would have significant potential in crypto-commerce. Up until now, the most commonly proposed solution has been issuer-backed assets; the idea is that an issuer creates a sub-currency in which they have the right to issue and revoke units, and provide one unit of the currency to anyone who provides them offline with one unit of a specified underlying asset eg.

The issuer then promises to provide one unit of the underlying asset to anyone who sends back one unit of the crypto-asset. This mechanism allows any non-cryptographic asset to be "uplifted" into a cryptographic asset, provided that the issuer can be trusted.

In practice, however, issuers are not always trustworthy, and in some cases the banking infrastructure is too weak, or too hostile, for such services to exist. Financial derivatives provide an alternative.

Here, instead of a single issuer providing the funds to back up an asset, a decentralized market of speculators, betting that the price of a cryptographic reference asset eg. ETH will go up, plays that role. Unlike issuers, speculators have no option to default on their side of the bargain because the hedging contract holds their funds in escrow. Note that this approach is not fully decentralized, because a trusted source is still needed to provide the price ticker, although arguably even still this is a massive improvement in terms of reducing infrastructure requirements unlike being an issuer, issuing a price feed requires no licenses and can likely be categorized as free speech and reducing the potential for fraud.

The earliest alternative cryptocurrency of all, Namecoin , attempted to use a Bitcoin-like blockchain to provide a name registration system, where users can register their names in a public database alongside other data. The major cited use case is for a DNS system, mapping domain names like "bitcoin. Other use cases include email authentication and potentially more advanced reputation systems. Here is the basic contract to provide a Namecoin-like name registration system on Ethereum:.

The contract is very simple; all it is is a database inside the Ethereum network that can be added to, but not modified or removed from. Anyone can register a name with some value, and that registration then sticks forever. A more sophisticated name registration contract will also have a "function clause" allowing other contracts to query it, as well as a mechanism for the "owner" ie.

One can even add reputation and web-of-trust functionality on top. Over the past few years, there have emerged a number of popular online file storage startups, the most prominent being Dropbox, seeking to allow users to upload a backup of their hard drive and have the service store the backup and allow the user to access it in exchange for a monthly fee.

However, at this point the file storage market is at times relatively inefficient; a cursory look at various existing solutions shows that, particularly at the "uncanny valley" GB level at which neither free quotas nor enterprise-level discounts kick in, monthly prices for mainstream file storage costs are such that you are paying for more than the cost of the entire hard drive in a single month.

Ethereum contracts can allow for the development of a decentralized file storage ecosystem, where individual users can earn small quantities of money by renting out their own hard drives and unused space can be used to further drive down the costs of file storage. The key underpinning piece of such a device would be what we have termed the "decentralized Dropbox contract".

This contract works as follows. First, one splits the desired data up into blocks, encrypting each block for privacy, and builds a Merkle tree out of it. One then makes a contract with the rule that, every N blocks, the contract would pick a random index in the Merkle tree using the previous block hash, accessible from contract code, as a source of randomness , and give X ether to the first entity to supply a transaction with a simplified payment verification-like proof of ownership of the block at that particular index in the tree.

When a user wants to re-download their file, they can use a micropayment channel protocol eg. An important feature of the protocol is that, although it may seem like one is trusting many random nodes not to decide to forget the file, one can reduce that risk down to near-zero by splitting the file into many pieces via secret sharing, and watching the contracts to see each piece is still in some node's possession.

If a contract is still paying out money, that provides a cryptographic proof that someone out there is still storing the file. The members would collectively decide on how the organization should allocate its funds. Methods for allocating a DAO's funds could range from bounties, salaries to even more exotic mechanisms such as an internal currency to reward work. This essentially replicates the legal trappings of a traditional company or nonprofit but using only cryptographic blockchain technology for enforcement.

The requirement that one person can only have one membership would then need to be enforced collectively by the group. A general outline for how to code a DAO is as follows. The simplest design is simply a piece of self-modifying code that changes if two thirds of members agree on a change. Although code is theoretically immutable, one can easily get around this and have de-facto mutability by having chunks of the code in separate contracts, and having the address of which contracts to call stored in the modifiable storage.

In a simple implementation of such a DAO contract, there would be three transaction types, distinguished by the data provided in the transaction:. The contract would then have clauses for each of these. It would maintain a record of all open storage changes, along with a list of who voted for them. It would also have a list of all members. When any storage change gets to two thirds of members voting for it, a finalizing transaction could execute the change.

A more sophisticated skeleton would also have built-in voting ability for features like sending a transaction, adding members and removing members, and may even provide for Liquid Democracy -style vote delegation ie. This design would allow the DAO to grow organically as a decentralized community, allowing people to eventually delegate the task of filtering out who is a member to specialists, although unlike in the "current system" specialists can easily pop in and out of existence over time as individual community members change their alignments.

An alternative model is for a decentralized corporation, where any account can have zero or more shares, and two thirds of the shares are required to make a decision. A complete skeleton would involve asset management functionality, the ability to make an offer to buy or sell shares, and the ability to accept offers preferably with an order-matching mechanism inside the contract.

Delegation would also exist Liquid Democracy-style, generalizing the concept of a "board of directors". Savings wallets. Suppose that Alice wants to keep her funds safe, but is worried that she will lose or someone will hack her private key. She puts ether into a contract with Bob, a bank, as follows:. If Alice's key gets hacked, she runs to Bob to move the funds to a new contract. If she loses her key, Bob will get the funds out eventually. If Bob turns out to be malicious, then she can turn off his ability to withdraw.

Crop insurance. One can easily make a financial derivatives contract but using a data feed of the weather instead of any price index. If a farmer in Iowa purchases a derivative that pays out inversely based on the precipitation in Iowa, then if there is a drought, the farmer will automatically receive money and if there is enough rain the farmer will be happy because their crops would do well. This can be expanded to natural disaster insurance generally.

A decentralized data feed. For financial contracts for difference, it may actually be possible to decentralize the data feed via a protocol called " SchellingCoin ". SchellingCoin basically works as follows: N parties all put into the system the value of a given datum eg. Everyone has the incentive to provide the answer that everyone else will provide, and the only value that a large number of players can realistically agree on is the obvious default: the truth. Smart multisignature escrow.

Bitcoin allows multisignature transaction contracts where, for example, three out of a given five keys can spend the funds. Additionally, Ethereum multisig is asynchronous - two parties can register their signatures on the blockchain at different times and the last signature will automatically send the transaction. Cloud computing. The EVM technology can also be used to create a verifiable computing environment, allowing users to ask others to carry out computations and then optionally ask for proofs that computations at certain randomly selected checkpoints were done correctly.

This allows for the creation of a cloud computing market where any user can participate with their desktop, laptop or specialized server, and spot-checking together with security deposits can be used to ensure that the system is trustworthy ie. Although such a system may not be suitable for all tasks; tasks that require a high level of inter-process communication, for example, cannot easily be done on a large cloud of nodes.

Other tasks, however, are much easier to parallelize; projects like SETI home, folding home and genetic algorithms can easily be implemented on top of such a platform. Peer-to-peer gambling. Any number of peer-to-peer gambling protocols, such as Frank Stajano and Richard Clayton's Cyberdice , can be implemented on the Ethereum blockchain. The simplest gambling protocol is actually simply a contract for difference on the next block hash, and more advanced protocols can be built up from there, creating gambling services with near-zero fees that have no ability to cheat.

Prediction markets. Provided an oracle or SchellingCoin, prediction markets are also easy to implement, and prediction markets together with SchellingCoin may prove to be the first mainstream application of futarchy as a governance protocol for decentralized organizations. On-chain decentralized marketplaces , using the identity and reputation system as a base. The motivation behind GHOST is that blockchains with fast confirmation times currently suffer from reduced security due to a high stale rate - because blocks take a certain time to propagate through the network, if miner A mines a block and then miner B happens to mine another block before miner A's block propagates to B, miner B's block will end up wasted and will not contribute to network security.

Thus, if the block interval is short enough for the stale rate to be high, A will be substantially more efficient simply by virtue of its size. With these two effects combined, blockchains which produce blocks quickly are very likely to lead to one mining pool having a large enough percentage of the network hashpower to have de facto control over the mining process.

As described by Sompolinsky and Zohar, GHOST solves the first issue of network security loss by including stale blocks in the calculation of which chain is the "longest"; that is to say, not just the parent and further ancestors of a block, but also the stale descendants of the block's ancestor in Ethereum jargon, "uncles" are added to the calculation of which block has the largest total proof-of-work backing it.

To solve the second issue of centralization bias, we go beyond the protocol described by Sompolinsky and Zohar, and also provide block rewards to stales: a stale block receives Transaction fees, however, are not awarded to uncles. Specifically, it is defined as follows:. This limited version of GHOST, with uncles includable only up to 7 generations, was used for two reasons. First, unlimited GHOST would include too many complications into the calculation of which uncles for a given block are valid.

Second, unlimited GHOST with compensation as used in Ethereum removes the incentive for a miner to mine on the main chain and not the chain of a public attacker. Because every transaction published into the blockchain imposes on the network the cost of needing to download and verify it, there is a need for some regulatory mechanism, typically involving transaction fees, to prevent abuse.

The default approach, used in Bitcoin, is to have purely voluntary fees, relying on miners to act as the gatekeepers and set dynamic minimums. This approach has been received very favorably in the Bitcoin community particularly because it is "market-based", allowing supply and demand between miners and transaction senders determine the price.

The problem with this line of reasoning is, however, that transaction processing is not a market; although it is intuitively attractive to construe transaction processing as a service that the miner is offering to the sender, in reality every transaction that a miner includes will need to be processed by every node in the network, so the vast majority of the cost of transaction processing is borne by third parties and not the miner that is making the decision of whether or not to include it.

Hence, tragedy-of-the-commons problems are very likely to occur. However, as it turns out this flaw in the market-based mechanism, when given a particular inaccurate simplifying assumption, magically cancels itself out. The argument is as follows. Suppose that:. A miner would be willing to process a transaction if the expected reward is greater than the cost. Note that R is the per-operation fee provided by the sender, and is thus a lower bound on the benefit that the sender derives from the transaction, and NC is the cost to the entire network together of processing an operation.

Hence, miners have the incentive to include only those transactions for which the total utilitarian benefit exceeds the cost. However, there are several important deviations from those assumptions in reality:. There is another factor disincentivizing large block sizes in Bitcoin: blocks that are large will take longer to propagate, and thus have a higher probability of becoming stales. In Ethereum, highly gas-consuming blocks can also take longer to propagate both because they are physically larger and because they take longer to process the transaction state transitions to validate.

This delay disincentive is a significant consideration in Bitcoin, but less so in Ethereum because of the GHOST protocol; hence, relying on regulated block limits provides a more stable baseline. An important note is that the Ethereum virtual machine is Turing-complete; this means that EVM code can encode any computation that can be conceivably carried out, including infinite loops.

EVM code allows looping in two ways. Second, contracts can call other contracts, potentially allowing for looping through recursion. This naturally leads to a problem: can malicious users essentially shut miners and full nodes down by forcing them to enter into an infinite loop? The issue arises because of a problem in computer science known as the halting problem: there is no way to tell, in the general case, whether or not a given program will ever halt.

As described in the state transition section, our solution works by requiring a transaction to set a maximum number of computational steps that it is allowed to take, and if execution takes longer computation is reverted but fees are still paid. Messages work in the same way. To show the motivation behind our solution, consider the following examples:. With this system, the fee system described and the uncertainties around the effectiveness of our solution might not be necessary, as the cost of executing a contract would be bounded above by its size.

Additionally, Turing-incompleteness is not even that big a limitation; out of all the contract examples we have conceived internally, so far only one required a loop, and even that loop could be removed by making 26 repetitions of a one-line piece of code. Given the serious implications of Turing-completeness, and the limited benefit, why not simply have a Turing-incomplete language? In reality, however, Turing-incompleteness is far from a neat solution to the problem.

To see why, consider the following contracts:. Now, send a transaction to A. Thus, in 51 transactions, we have a contract that takes up 2 50 computational steps. Miners could try to detect such logic bombs ahead of time by maintaining a value alongside each contract specifying the maximum number of computational steps that it can take, and calculating this for contracts calling other contracts recursively, but that would require miners to forbid contracts that create other contracts since the creation and execution of all 26 contracts above could easily be rolled into a single contract.

Another problematic point is that the address field of a message is a variable, so in general it may not even be possible to tell which other contracts a given contract will call ahead of time. Hence, all in all, we have a surprising conclusion: Turing-completeness is surprisingly easy to manage, and the lack of Turing-completeness is equally surprisingly difficult to manage unless the exact same controls are in place - but in that case why not just let the protocol be Turing-complete?

The Ethereum network includes its own built-in currency, ether, which serves the dual purpose of providing a primary liquidity layer to allow for efficient exchange between various types of digital assets and, more importantly, of providing a mechanism for paying transaction fees. This should be taken as an expanded version of the concept of "dollars" and "cents" or "BTC" and "satoshi". In the near future, we expect "ether" to be used for ordinary transactions, "finney" for microtransactions and "szabo" and "wei" for technical discussions around fees and protocol implementation; the remaining denominations may become useful later and should not be included in clients at this point.

The issuance model will be as follows:. Despite the linear currency issuance, just like with Bitcoin over time the supply growth rate nevertheless tends to zero. The two main choices in the above model are 1 the existence and size of an endowment pool, and 2 the existence of a permanently growing linear supply, as opposed to a capped supply as in Bitcoin.

The justification of the endowment pool is as follows. If the endowment pool did not exist, and the linear issuance reduced to 0. Hence, in the equilibrium The organization would also then have 1. Hence, this situation is exactly equivalent to the endowment, but with one important difference: the organization holds purely BTC, and so is not incentivized to support the value of the ether unit.

The permanent linear supply growth model reduces the risk of what some see as excessive wealth concentration in Bitcoin, and gives individuals living in present and future eras a fair chance to acquire currency units, while at the same time retaining a strong incentive to obtain and hold ether because the "supply growth rate" as a percentage still tends to zero over time. We also theorize that because coins are always lost over time due to carelessness, death, etc, and coin loss can be modeled as a percentage of the total supply per year, that the total currency supply in circulation will in fact eventually stabilize at a value equal to the annual issuance divided by the loss rate eg.

Note that in the future, it is likely that Ethereum will switch to a proof-of-stake model for security, reducing the issuance requirement to somewhere between zero and 0. Creators are free to crowd-sell or otherwise assign some or all of the difference between the PoS-driven supply expansion and the maximum allowable supply expansion to pay for development. Candidate upgrades that do not comply with the social contract may justifiably be forked into compliant versions.

The Bitcoin mining algorithm works by having miners compute SHA on slightly modified versions of the block header millions of times over and over again, until eventually one node comes up with a version whose hash is less than the target currently around 2 However, this mining algorithm is vulnerable to two forms of centralization. First, the mining ecosystem has come to be dominated by ASICs application-specific integrated circuits , computer chips designed for, and therefore thousands of times more efficient at, the specific task of Bitcoin mining.

This means that Bitcoin mining is no longer a highly decentralized and egalitarian pursuit, requiring millions of dollars of capital to effectively participate in. Second, most Bitcoin miners do not actually perform block validation locally; instead, they rely on a centralized mining pool to provide the block headers. The current intent at Ethereum is to use a mining algorithm where miners are required to fetch random data from the state, compute some randomly selected transactions from the last N blocks in the blockchain, and return the hash of the result.

This has two important benefits. Second, mining requires access to the entire blockchain, forcing miners to store the entire blockchain and at least be capable of verifying every transaction. This removes the need for centralized mining pools; although mining pools can still serve the legitimate role of evening out the randomness of reward distribution, this function can be served equally well by peer-to-peer pools with no central control.

This model is untested, and there may be difficulties along the way in avoiding certain clever optimizations when using contract execution as a mining algorithm. However, one notably interesting feature of this algorithm is that it allows anyone to "poison the well", by introducing a large number of contracts into the blockchain specifically designed to stymie certain ASICs. The economic incentives exist for ASIC manufacturers to use such a trick to attack each other.

Thus, the solution that we are developing is ultimately an adaptive economic human solution rather than purely a technical one. One common concern about Ethereum is the issue of scalability. Like Bitcoin, Ethereum suffers from the flaw that every transaction needs to be processed by every node in the network. With Bitcoin, the size of the current blockchain rests at about 15 GB, growing by about 1 MB per hour.

Ethereum is likely to suffer a similar growth pattern, worsened by the fact that there will be many applications on top of the Ethereum blockchain instead of just a currency as is the case with Bitcoin, but ameliorated by the fact that Ethereum full nodes need to store just the state instead of the entire blockchain history.

The problem with such a large blockchain size is centralization risk. Ethereum-based software and networks, independent from the public Ethereum chain , are being tested by enterprise software companies. Ethereum-based permissioned blockchain variants are used and being investigated for various projects:.

In Ethereum, all smart contracts are stored publicly on every node of the blockchain, which has costs. Being a blockchain means it is secure by design ; it is an example of a distributed computing system with high Byzantine fault tolerance. Every new transaction is recorded on a new block, which is connected to previous and future blocks in a chain. The downside is that performance issues arise because every node calculates all the smart contracts in real-time.

As of January [update] , the Ethereum protocol could process about 25 transactions per second. In comparison, the Visa payment platform processes 45, payments per second. This has led some to question the scalability of Ethereum. Ethereum engineers have been working on sharding the calculations, and the next step Ethereum 2 was presented at Ethereum's Devcon 3 in November Ethereum's blockchain uses Merkle trees for security reasons, to improve scalability, and to optimize transaction hashing.

The network has faced congestion problems, such as in in relation to Cryptokitties. Like other crypto currencies, Ethereum faces criticism about its environmental impact. From Wikipedia, the free encyclopedia. Open-source blockchain computing platform.

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Ethereum white paper pdf espanol bet on bitcoin value

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Ethereum white paper pdf espanol This is the perfect website for anybody who wishes to understand this topic. The two main choices in the above model are 1 the existence and size of an endowment pool, and 2 the visit web page of a permanently growing linear supply, as opposed to a capped supply as in Bitcoin. Binary state combined with value-blindness also mean that another important application, withdrawal limits, is impossible. The Bitcoin-based approach, on the other hand, has the flaw that it does not inherit the simplified payment verification features of Ethereum white paper pdf espanol. Works as a memory enhancer, improving concentration and coordination of movements, removing swelling and persistent infections. I like what you guys are up too. Currently, all "light" implementations of Bitcoin-based meta-protocols rely on a trusted server to provide the data, arguably a highly suboptimal result especially when one of the primary purposes of a cryptocurrency is to eliminate the need for trust.
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Others obtain Dai by buying it from brokers or exchanges, or simply by receiving it as a means of payment. Once generated, bought, or received, Dai can be used in the same manner as any other cryptocurrency: it can be sent to others, used as payments for goods and services, and even held as savings through a feature of the Maker Protocol called the Dai Savings Rate The Dai Savings Rate DSR allows all Dai holders to earn savings automatically and natively by locking their Dai into the DSR contract.

The DSR enables greater utility for Dai holders, which may include cryptocurrency traders, startups, and established businesses. Every Dai in circulation is directly backed by excess collateral, meaning that the value of the collateral is higher than the value of the Dai debt, and all Dai transactions are publicly viewable on the Ethereum blockchain.

A store of value is an asset that keeps its value without significant depreciation over time. Because Dai is a stablecoin, it is designed to function as a store of value even in a volatile market. A medium of exchange is anything that represents a standard of value and is used to facilitate the sale, purchase, or exchange trade of goods or services. The Dai stablecoin is used around the world for all types of transactional purposes. A unit of account is a standardized measurement of value used to price goods and services e.

While Dai is not used as a standard measurement of value in the off-chain world, it functions as a unit of account within the Maker Protocol and some blockchain dapps, whereby Maker Protocol accounting or pricing of dapp services is in Dai rather than a fiat currency like USD. Dai is used to settle debts within the Maker Protocol e.

This benefit separates Dai from other stablecoins. Dai is generated, backed, and kept stable through collateral assets that are deposited into Maker Vaults on the Maker Protocol. A collateral asset is a digital asset that MKR holders have voted to accept into the Protocol.

MKR holders must also approve specific, corresponding Risk Parameters for each accepted collateral e. Detailed information on Risk Parameters is below. These and other decisions of MKR holders are made through the Maker decentralized governance process.

All accepted collateral assets can be leveraged to generate Dai in the Maker Protocol through smart contracts called Maker Vaults. Users can access the Maker Protocol and create Vaults through a number of different user interfaces i.

Creating a Vault is not complicated, but generating Dai does create an obligation to repay the Dai, along with a Stability Fee The Stability Fee is a fee paid by every Vault owner when debt is paid down or completely paid off. It is an annual percentage yield that is calculated on top of the existing Vault debt. Stability Fees must be paid in Dai only. A user creates a Vault via the Oasis Borrow portal or a community-created interface, such as Instadapp, Zerion, or MyEtherWallet, by funding it with a specific type and amount of collateral that will be used to generate Dai.

Once funded, a Vault is considered collateralized. The Vault owner initiates a transaction, and then confirms it in her unhosted cryptocurrency wallet in order to generate a specific amount of Dai in exchange for keeping her collateral locked in the Vault. To retrieve a portion or all of the collateral, a Vault owner must pay down or completely pay back the Dai she generated, plus the Stability Fee that continuously accrues on the Dai outstanding. The Stability Fee can only be paid in Dai.

With the Dai returned and the Stability Fee paid, the Vault owner can withdraw all or some of her collateral back to her wallet. Once all Dai is completely returned and all collateral is retrieved, the Vault remains empty until the owner chooses to make another deposit. Importantly, each collateral asset deposited requires its own Vault. So, some users will own multiple Vaults with different types of collateral and levels of collateralization.

Each Vault type has its own Liquidation Ratio, and each ratio is determined by MKR voters based on the risk profile of the particular collateral asset type. The auction mechanisms of the Maker Protocol enable the system to liquidate Vaults even when price information for the collateral is unavailable.

At the point of liquidation, the Maker Protocol takes the liquidated Vault collateral and subsequently sells it using an internal market-based auction mechanism. If enough Dai is bid in the Collateral Auction to fully cover the Vault obligations plus the Liquidation Penalty, that auction converts to a Reverse Collateral Auction In a Reverse Auction, Keepers bid in decreasing amounts of collateral they are willing to accept for a fixed amount of Dai. This process is part of the Collateral Auction and will only be initiated if there is enough initial interest in the collateral to cover the Vault's outstanding Dai.

Once enough Dai is bid to cover those obligations, then the Reverse Collateral Auction kicks in. The purpose of the Reverse Collateral Auction is to provide a process that best enables the Vault owner to recover as much leftover collateral as possible, while ensuring all outstanding Dai obligations are first met. Any leftover collateral is returned to the original Vault owner.

When the amount of Dai in the Maker Buffer reaches a specific number determined by Maker Governance the surplus amount is put into a Surplus Auction and is used to buy and remove MKR from the total supply. The surplus amount is net of system debts, such as outstanding Vault obligations in the Collateral Auction and DSR accruals. Dai proceeds from the Collateral Auction go into the Maker Buffer, which serves as a buffer against an increase of MKR overall supply that could result from future uncovered Collateral Auctions and the accrual of the Dai Savings Rate discussed in detail below.

Example Collateral Auction Process : A large Vault becomes undercollateralized due to market conditions. An Auction Keeper An Auction Keeper is a human or automated bot incentivized by the Maker Protocol to monitor the system and trigger liquidation when a Vault's Liquidation Ratio is breached. Each Auction Keeper has a bidding model A bidding model is the strategy behind when to bid, how often to bid, and at what price to bid.

A bidding model includes a price at which to bid for the collateral ETH, in this example. The Auction Keeper uses the token price from its bidding model as the basis for its bids in the first phase of a Collateral Auction, where increasing Dai bids are placed for the set amount of collateral. This amount represents the price of the total Dai wanted from the collateral auction. With enough Dai in the Collateral Auction contract to cover the system's debt plus the Liquidation Penalty, the first phase of the Collateral Auction is over.

In order to reach the price defined in its bidding model, the Auction Keeper submits a bid in the second phase of the Collateral Auction. In this phase, the objective is to return as much of the collateral to the Vault owner as the market will allow.

After the bid duration limit is reached and the bid expires, the Auction Keeper claims the winning bid and settles the completed Collateral Auction by collecting the won collateral. In addition to its smart contract infrastructure, the Maker Protocol involves groups of external actors to maintain operations: Keepers, Oracles, and Global Settlers Emergency Oracles , and Maker community members. Keepers take advantage of the economic incentives presented by the Protocol; Oracles and Global Settlers are external actors with special permissions in the system assigned to them by MKR voters; and Maker community members are individuals and organizations that provide services.

A Keeper is an independent usually automated actor that is incentivized by arbitrage opportunities to provide liquidity in various aspects of a decentralized system. The Maker Protocol requires real-time information about the market price of the collateral assets in Maker Vaults in order to know when to trigger Liquidations. The Protocol derives its internal collateral prices from a decentralized Oracle infrastructure that consists of a broad set of individual nodes called Oracle Feeds. MKR voters choose a set of trusted Feeds to deliver price information to the system through Ethereum transactions.

They also control how many Feeds are in the set. To protect the system from an attacker attempting to gain control of a majority of the Oracles, the Maker Protocol receives price inputs through the Oracle Security Module OSM , not from the Oracles directly. The OSM, which is a layer of defense between the Oracles and the Protocol, delays a price for one hour, allowing Emergency Oracles or a Maker Governance vote to freeze an Oracle if it is compromised.

Emergency Oracles are selected by MKR voters and act as a last line of defense against an attack on the governance process or on other Oracles. Emergency Oracles are able to freeze individual Oracles e. It is used during emergencies as a last-resort mechanism to protect the Maker Protocol against attacks on its infrastructure, and used to facilitate a Maker Protocol system upgrade.

The process is fully decentralized and controlled by Maker Governance. The flexibility of Maker Governance allows the Maker community to adapt the DAO team framework to suit the services needed by the ecosystem based on real-world performance and emerging challenges.

Examples of DAO team member roles are the Governance Facilitator, who supports the communication infrastructure and processes of governance, and Risk Team members, who support Maker Governance with financial risk research and draft proposals for onboarding new collateral and regulating existing collateral.

It can be accessed via the Oasis Save portal or through various gateways into the Maker Protocol. The DSR is a global system parameter that determines the amount Dai holders earn on their savings over time. When the market price of Dai deviates from the Target Price due to changing market dynamics, MKR holders can mitigate the price instability by voting to modify the DSR accordingly:.

Initially, adjustment of the DSR will depend on a weekly process, whereby MKR holders first evaluate and discuss public market data and proprietary data provided by market participants, and then vote on whether an adjustment is necessary or not.

The motivation behind this plan is to enable nimble responses to rapidly changing market conditions, and to avoid overuse of the standard governance process of Executive Voting and Governance Polling. Any voter-approved modifications to the governance variables of the Protocol will likely not take effect immediately in the future; rather, they could be delayed by as much as 24 hours if voters choose to activate the Governance Security Module GSM.

The delay would give MKR holders the opportunity to protect the system, if necessary, against a malicious governance proposal e. In practice, the Maker Governance process includes proposal polling and Executive Voting. Proposal polling is conducted to establish a rough consensus of community sentiment before any Executive Votes are cast. This helps to ensure that governance decisions are considered throughtfully and reached by consensus prior to the voting process itself.

Executive Voting is held to approve or not changes to the state of the system. An example of an Executive Vote could be a vote to ratify Risk Parameters for a newly accepted collateral type. At a technical level, smart contracts manage each type of vote. A Proposal Contract is a smart contract with one or more valid governance actions programmed into it. It can only be executed once. When executed, it immediately applies its changes to the internal governance variables of the Maker Protocol.

After execution, the Proposal Contract cannot be reused. It cannot initiate new transactions on its own; rather, when it receives a message from an externally owned account or another contract account, it executes its code, allowing it to read, write, and send messages or create smart contracts.

MKR token holders can then cast approval votes for the proposal that they want to elect as the Active Proposal. The Ethereum address that has the highest number of approval votes is elected as the Active Proposal. The Active Proposal is empowered to gain administrative access to the internal governance variables of the Maker Protocol, and then modify them. In addition to its role in Maker Governance, the MKR token has a complementary role as the recapitalization resource of the Maker Protocol.

If the system debt exceeds the surplus, the MKR token supply may increase through a Debt Auction see above to recapitalize the system. This risk inclines MKR holders to align and responsibly govern the Maker ecosystem to avoid excessive risk-taking. MKR holders can also allocate funds from the Maker Buffer to pay for various infrastructure needs and services, including Oracle infrastructure and collateral risk management research.

The governance mechanism of the Maker Protocol is designed to be as flexible as possible, and upgradeable. Should the system mature under the guidance of the community, more advanced forms of Proposal Contracts could, in theory, be used, including Proposal Contracts that are bundled.

For example, one proposal contract may contain both an adjustment of a Stability Fee and an adjustment of the DSR. Nonetheless, those revisions will remain for MKR holders to decide. Each Maker Vault type e. The parameters are determined based on the risk profile of the collateral, and are directly controlled by MKR holders through voting. The successful operation of the Maker Protocol depends on Maker Governance taking necessary steps to mitigate risks.

Some of those risks are identified below, each followed by a mitigation plan. One of the greatest risks to the Maker Protocol is a malicious actor—a programmer, for example, who discovers a vulnerability in the deployed smart contracts, and then uses it to break the Protocol or steal from it. In the worst-case scenario, all decentralized digital assets held as collateral in the Protocol are stolen, and recovery is impossible.

Mitigation: The Maker Foundation's highest priority is the security of the Maker Protocol , and the strongest defense of the Protocol is Formal Verification Formal Verification means creating mathematical specifications of the intended behavior of the system, alongside mathematical proofs that the codebase implements behavior that is identical to the intended behavior, with no unintended side effects as there is no mathematical evidence that the intended behavior produces effects inconsistent with the intended behavior.

The Dai codebase was the first codebase of a decentralized application to be formally verified. These security measures provide a strong defense system; however, they are not infallible. Even with formal verification, the mathematical modeling of intended behaviors may be incorrect, or the assumptions behind the intended behavior itself may be incorrect. A black swan event is a rare and critical surprise attack on a system. For the Maker Protocol, examples of a black swan event include:.

Please note that this list of potential "black swans" is not exhaustive and not intended to capture the extent of such possibilities. Oracle price feed problems or irrational market dynamics that cause variations in the price of Dai for an extended period of time can occur. If confidence in the system is lost, rate adjustments or even MKR dilution could reach extreme levels and still not bring enough liquidity and stability to the market.

As a last resort, Emergency Shutdown can be triggered to release collateral to Dai holders, with their Dai claims valued at the Target Price. The Maker Protocol is a complex decentralized system. As a result of its complexity, there is a risk that inexperienced cryptocurrency users will abandon the Protocol in favor of systems that may be easier to use and understand.

Although Dai is designed in such a way that users need not comprehend the underlying mechanics of the Maker Protocol in order to benefit from it, the documentation and numerous resources consistently provided by the Maker community and the Maker Foundation help to ensure onboarding is as uncomplicated as possible. The Maker Foundation currently plays a role, along with independent actors, in maintaining the Maker Protocol and expanding its usage worldwide, while facilitating Governance.

Moreover, successful management of the system should result in sufficient funds for governance to allocate to the continued maintenance and improvement of the Maker Protocol. Users of the Maker Protocol including but not limited to Dai and MKR holders understand and accept that the software, technology, and technical concepts and theories applicable to the Maker Protocol are still unproven and there is no warranty that the technology will be uninterrupted or error-free.

The Mitigation section there explains the technical auditing in place to ensure the Maker Protocol functions as intended. The Dai Target Price is used to determine the value of collateral assets Dai holders receive in the case of an Emergency Shutdown. Emergency Shutdown or, simply, Shutdown serves two main purposes. First, it is used during emergencies as a last-resort mechanism to protect the Maker Protocol against attacks on its infrastructure and directly enforce the Dai Target Price.

Emergencies could include malicious governance actions, hacking, security breaches, and long-term market irrationality. Furthermore, the attacker's new version of block has a different hash, so the original blocks to do not "point" to it; thus, the original chain and the attacker's new chain are completely separate. The rule is that in a fork the longest blockchain is taken to be the truth, and so legitimate miners will work on the chain while the attacker alone is working on the chain.

Left: it suffices to present only a small number of nodes in a Merkle tree to give a proof of the validity of a branch. Right: any attempt to change any part of the Merkle tree will eventually lead to an inconsistency somewhere up the chain. An important scalability feature of Bitcoin is that the block is stored in a multi-level data structure.

The "hash" of a block is actually only the hash of the block header, a roughly byte piece of data that contains the timestamp, nonce, previous block hash and the root hash of a data structure called the Merkle tree storing all transactions in the block. A Merkle tree is a type of binary tree, composed of a set of nodes with a large number of leaf nodes at the bottom of the tree containing the underlying data, a set of intermediate nodes where each node is the hash of its two children, and finally a single root node, also formed from the hash of its two children, representing the "top" of the tree.

The purpose of the Merkle tree is to allow the data in a block to be delivered piecemeal: a node can download only the header of a block from one source, the small part of the tree relevant to them from another source, and still be assured that all of the data is correct. The reason why this works is that hashes propagate upward: if a malicious user attempts to swap in a fake transaction into the bottom of a Merkle tree, this change will cause a change in the node above, and then a change in the node above that, finally changing the root of the tree and therefore the hash of the block, causing the protocol to register it as a completely different block almost certainly with an invalid proof-of-work.

The Merkle tree protocol is arguably essential to long-term sustainability. A "full node" in the Bitcoin network, one that stores and processes the entirety of every block, takes up about 15 GB of disk space in the Bitcoin network as of April , and is growing by over a gigabyte per month. Currently, this is viable for some desktop computers and not phones, and later on in the future only businesses and hobbyists will be able to participate. A protocol known as "simplified payment verification" SPV allows for another class of nodes to exist, called "light nodes", which download the block headers, verify the proof-of-work on the block headers, and then download only the "branches" associated with transactions that are relevant to them.

This allows light nodes to determine with a strong guarantee of security what the status of any Bitcoin transaction, and their current balance, is while downloading only a very small portion of the entire blockchain. The idea of taking the underlying blockchain idea and applying it to other concepts also has a long history. In , Nick Szabo came out with the concept of " secure property titles with owner authority ", a document describing how "new advances in replicated database technology" will allow for a blockchain-based system for storing a registry of who owns what land, creating an elaborate framework including concepts such as homesteading, adverse possession and Georgian land tax.

However, there was unfortunately no effective replicated database system available at the time, and so the protocol was never implemented in practice. After , however, once Bitcoin's decentralized consensus was developed a number of alternative applications rapidly began to emerge.

Thus, in general, there are two approaches toward building a consensus protocol: building an independent network, and building a protocol on top of Bitcoin. The former approach, while reasonably successful in the case of applications like Namecoin, is difficult to implement; each individual implementation needs to bootstrap an independent blockchain, as well as building and testing all of the necessary state transition and networking code.

Additionally, we predict that the set of applications for decentralized consensus technology will follow a power law distribution where the vast majority of applications would be too small to warrant their own blockchain, and we note that there exist large classes of decentralized applications, particularly decentralized autonomous organizations, that need to interact with each other.

The Bitcoin-based approach, on the other hand, has the flaw that it does not inherit the simplified payment verification features of Bitcoin. SPV works for Bitcoin because it can use blockchain depth as a proxy for validity; at some point, once the ancestors of a transaction go far enough back, it is safe to say that they were legitimately part of the state. Blockchain-based meta-protocols, on the other hand, cannot force the blockchain not to include transactions that are not valid within the context of their own protocols.

Hence, a fully secure SPV meta-protocol implementation would need to backward scan all the way to the beginning of the Bitcoin blockchain to determine whether or not certain transactions are valid. Currently, all "light" implementations of Bitcoin-based meta-protocols rely on a trusted server to provide the data, arguably a highly suboptimal result especially when one of the primary purposes of a cryptocurrency is to eliminate the need for trust.

Even without any extensions, the Bitcoin protocol actually does facilitate a weak version of a concept of "smart contracts". UTXO in Bitcoin can be owned not just by a public key, but also by a more complicated script expressed in a simple stack-based programming language. In this paradigm, a transaction spending that UTXO must provide data that satisfies the script.

Indeed, even the basic public key ownership mechanism is implemented via a script: the script takes an elliptic curve signature as input, verifies it against the transaction and the address that owns the UTXO, and returns 1 if the verification is successful and 0 otherwise.

Other, more complicated, scripts exist for various additional use cases. For example, one can construct a script that requires signatures from two out of a given three private keys to validate "multisig" , a setup useful for corporate accounts, secure savings accounts and some merchant escrow situations. Scripts can also be used to pay bounties for solutions to computational problems, and one can even construct a script that says something like "this Bitcoin UTXO is yours if you can provide an SPV proof that you sent a Dogecoin transaction of this denomination to me", essentially allowing decentralized cross-cryptocurrency exchange.

However, the scripting language as implemented in Bitcoin has several important limitations:. Thus, we see three approaches to building advanced applications on top of cryptocurrency: building a new blockchain, using scripting on top of Bitcoin, and building a meta-protocol on top of Bitcoin. Building a new blockchain allows for unlimited freedom in building a feature set, but at the cost of development time, bootstrapping effort and security. Using scripting is easy to implement and standardize, but is very limited in its capabilities, and meta-protocols, while easy, suffer from faults in scalability.

With Ethereum, we intend to build an alternative framework that provides even larger gains in ease of development as well as even stronger light client properties, while at the same time allowing applications to share an economic environment and blockchain security. The intent of Ethereum is to create an alternative protocol for building decentralized applications, providing a different set of tradeoffs that we believe will be very useful for a large class of decentralized applications, with particular emphasis on situations where rapid development time, security for small and rarely used applications, and the ability of different applications to very efficiently interact, are important.

Ethereum does this by building what is essentially the ultimate abstract foundational layer: a blockchain with a built-in Turing-complete programming language, allowing anyone to write smart contracts and decentralized applications where they can create their own arbitrary rules for ownership, transaction formats and state transition functions.

A bare-bones version of Namecoin can be written in two lines of code, and other protocols like currencies and reputation systems can be built in under twenty. Smart contracts, cryptographic "boxes" that contain value and only unlock it if certain conditions are met, can also be built on top of the platform, with vastly more power than that offered by Bitcoin scripting because of the added powers of Turing-completeness, value-awareness, blockchain-awareness and state.

In Ethereum, the state is made up of objects called "accounts", with each account having a byte address and state transitions being direct transfers of value and information between accounts. An Ethereum account contains four fields:. In general, there are two types of accounts: externally owned accounts , controlled by private keys, and contract accounts , controlled by their contract code.

An externally owned account has no code, and one can send messages from an externally owned account by creating and signing a transaction; in a contract account, every time the contract account receives a message its code activates, allowing it to read and write to internal storage and send other messages or create contracts in turn.

The term "transaction" is used in Ethereum to refer to the signed data package that stores a message to be sent from an externally owned account. Transactions contain:. The first three are standard fields expected in any cryptocurrency. The data field has no function by default, but the virtual machine has an opcode using which a contract can access the data; as an example use case, if a contract is functioning as an on-blockchain domain registration service, then it may wish to interpret the data being passed to it as containing two "fields", the first field being a domain to register and the second field being the IP address to register it to.

The contract would read these values from the message data and appropriately place them in storage. In order to prevent accidental or hostile infinite loops or other computational wastage in code, each transaction is required to set a limit to how many computational steps of code execution it can use. The fundamental unit of computation is "gas"; usually, a computational step costs 1 gas, but some operations cost higher amounts of gas because they are more computationally expensive, or increase the amount of data that must be stored as part of the state.

There is also a fee of 5 gas for every byte in the transaction data. The intent of the fee system is to require an attacker to pay proportionately for every resource that they consume, including computation, bandwidth and storage; hence, any transaction that leads to the network consuming a greater amount of any of these resources must have a gas fee roughly proportional to the increment. Contracts have the ability to send "messages" to other contracts. Messages are virtual objects that are never serialized and exist only in the Ethereum execution environment.

A message contains:. Essentially, a message is like a transaction, except it is produced by a contract and not an external actor. A message is produced when a contract currently executing code executes the CALL opcode, which produces and executes a message. Like a transaction, a message leads to the recipient account running its code. Thus, contracts can have relationships with other contracts in exactly the same way that external actors can.

Note that the gas allowance assigned by a transaction or contract applies to the total gas consumed by that transaction and all sub-executions. For example, if an external actor A sends a transaction to B with gas, and B consumes gas before sending a message to C, and the internal execution of C consumes gas before returning, then B can spend another gas before running out of gas.

For example, suppose that the contract's code is:. Note that in reality the contract code is written in the low-level EVM code; this example is written in Serpent, one of our high-level languages, for clarity, and can be compiled down to EVM code. Suppose that the contract's storage starts off empty, and a transaction is sent with 10 ether value, gas, 0.

The process for the state transition function in this case is as follows:. If there was no contract at the receiving end of the transaction, then the total transaction fee would simply be equal to the provided GASPRICE multiplied by the length of the transaction in bytes, and the data sent alongside the transaction would be irrelevant.

Note that messages work equivalently to transactions in terms of reverts: if a message execution runs out of gas, then that message's execution, and all other executions triggered by that execution, revert, but parent executions do not need to revert. This means that it is "safe" for a contract to call another contract, as if A calls B with G gas then A's execution is guaranteed to lose at most G gas.

Finally, note that there is an opcode, CREATE , that creates a contract; its execution mechanics are generally similar to CALL , with the exception that the output of the execution determines the code of a newly created contract. The code in Ethereum contracts is written in a low-level, stack-based bytecode language, referred to as "Ethereum virtual machine code" or "EVM code".

The code consists of a series of bytes, where each byte represents an operation. In general, code execution is an infinite loop that consists of repeatedly carrying out the operation at the current program counter which begins at zero and then incrementing the program counter by one, until the end of the code is reached or an error or STOP or RETURN instruction is detected. The operations have access to three types of space in which to store data:. The code can also access the value, sender and data of the incoming message, as well as block header data, and the code can also return a byte array of data as an output.

The formal execution model of EVM code is surprisingly simple. For example, ADD pops two items off the stack and pushes their sum, reduces gas by 1 and increments pc by 1, and SSTORE pushes the top two items off the stack and inserts the second item into the contract's storage at the index specified by the first item. Although there are many ways to optimize Ethereum virtual machine execution via just-in-time compilation, a basic implementation of Ethereum can be done in a few hundred lines of code.

The Ethereum blockchain is in many ways similar to the Bitcoin blockchain, although it does have some differences. The main difference between Ethereum and Bitcoin with regard to the blockchain architecture is that, unlike Bitcoin, Ethereum blocks contain a copy of both the transaction list and the most recent state.

Aside from that, two other values, the block number and the difficulty, are also stored in the block. The basic block validation algorithm in Ethereum is as follows:. The approach may seem highly inefficient at first glance, because it needs to store the entire state with each block, but in reality efficiency should be comparable to that of Bitcoin. The reason is that the state is stored in the tree structure, and after every block only a small part of the tree needs to be changed.

Thus, in general, between two adjacent blocks the vast majority of the tree should be the same, and therefore the data can be stored once and referenced twice using pointers ie. A special kind of tree known as a "Patricia tree" is used to accomplish this, including a modification to the Merkle tree concept that allows for nodes to be inserted and deleted, and not just changed, efficiently.

Additionally, because all of the state information is part of the last block, there is no need to store the entire blockchain history - a strategy which, if it could be applied to Bitcoin, can be calculated to provide x savings in space. A commonly asked question is "where" contract code is executed, in terms of physical hardware. This has a simple answer: the process of executing contract code is part of the definition of the state transition function, which is part of the block validation algorithm, so if a transaction is added into block B the code execution spawned by that transaction will be executed by all nodes, now and in the future, that download and validate block B.

In general, there are three types of applications on top of Ethereum. The first category is financial applications, providing users with more powerful ways of managing and entering into contracts using their money. This includes sub-currencies, financial derivatives, hedging contracts, savings wallets, wills, and ultimately even some classes of full-scale employment contracts. The second category is semi-financial applications, where money is involved but there is also a heavy non-monetary side to what is being done; a perfect example is self-enforcing bounties for solutions to computational problems.

Finally, there are applications such as online voting and decentralized governance that are not financial at all. On-blockchain token systems have many applications ranging from sub-currencies representing assets such as USD or gold to company stocks, individual tokens representing smart property, secure unforgeable coupons, and even token systems with no ties to conventional value at all, used as point systems for incentivization. Token systems are surprisingly easy to implement in Ethereum.

The key point to understand is that all a currency, or token system, fundamentally is, is a database with one operation: subtract X units from A and give X units to B, with the proviso that i A had at least X units before the transaction and 2 the transaction is approved by A. All that it takes to implement a token system is to implement this logic into a contract. The basic code for implementing a token system in Serpent looks as follows:. This is essentially a literal implementation of the "banking system" state transition function described further above in this document.

A few extra lines of code need to be added to provide for the initial step of distributing the currency units in the first place and a few other edge cases, and ideally a function would be added to let other contracts query for the balance of an address. But that's all there is to it.

Theoretically, Ethereum-based token systems acting as sub-currencies can potentially include another important feature that on-chain Bitcoin-based meta-currencies lack: the ability to pay transaction fees directly in that currency.

The way this would be implemented is that the contract would maintain an ether balance with which it would refund ether used to pay fees to the sender, and it would refill this balance by collecting the internal currency units that it takes in fees and reselling them in a constant running auction. Users would thus need to "activate" their accounts with ether, but once the ether is there it would be reusable because the contract would refund it each time.

Financial derivatives are the most common application of a "smart contract", and one of the simplest to implement in code. The simplest way to do this is through a "data feed" contract maintained by a specific party eg. NASDAQ designed so that that party has the ability to update the contract as needed, and providing an interface that allows other contracts to send a message to that contract and get back a response that provides the price.

Given that critical ingredient, the hedging contract would look as follows:. Such a contract would have significant potential in crypto-commerce. Up until now, the most commonly proposed solution has been issuer-backed assets; the idea is that an issuer creates a sub-currency in which they have the right to issue and revoke units, and provide one unit of the currency to anyone who provides them offline with one unit of a specified underlying asset eg.

The issuer then promises to provide one unit of the underlying asset to anyone who sends back one unit of the crypto-asset. This mechanism allows any non-cryptographic asset to be "uplifted" into a cryptographic asset, provided that the issuer can be trusted.

In practice, however, issuers are not always trustworthy, and in some cases the banking infrastructure is too weak, or too hostile, for such services to exist. Financial derivatives provide an alternative. Here, instead of a single issuer providing the funds to back up an asset, a decentralized market of speculators, betting that the price of a cryptographic reference asset eg.

ETH will go up, plays that role. Unlike issuers, speculators have no option to default on their side of the bargain because the hedging contract holds their funds in escrow. Note that this approach is not fully decentralized, because a trusted source is still needed to provide the price ticker, although arguably even still this is a massive improvement in terms of reducing infrastructure requirements unlike being an issuer, issuing a price feed requires no licenses and can likely be categorized as free speech and reducing the potential for fraud.

The earliest alternative cryptocurrency of all, Namecoin , attempted to use a Bitcoin-like blockchain to provide a name registration system, where users can register their names in a public database alongside other data. The major cited use case is for a DNS system, mapping domain names like "bitcoin. Other use cases include email authentication and potentially more advanced reputation systems.

Here is the basic contract to provide a Namecoin-like name registration system on Ethereum:. The contract is very simple; all it is is a database inside the Ethereum network that can be added to, but not modified or removed from. Anyone can register a name with some value, and that registration then sticks forever. A more sophisticated name registration contract will also have a "function clause" allowing other contracts to query it, as well as a mechanism for the "owner" ie.

One can even add reputation and web-of-trust functionality on top. Over the past few years, there have emerged a number of popular online file storage startups, the most prominent being Dropbox, seeking to allow users to upload a backup of their hard drive and have the service store the backup and allow the user to access it in exchange for a monthly fee.

However, at this point the file storage market is at times relatively inefficient; a cursory look at various existing solutions shows that, particularly at the "uncanny valley" GB level at which neither free quotas nor enterprise-level discounts kick in, monthly prices for mainstream file storage costs are such that you are paying for more than the cost of the entire hard drive in a single month.

Ethereum contracts can allow for the development of a decentralized file storage ecosystem, where individual users can earn small quantities of money by renting out their own hard drives and unused space can be used to further drive down the costs of file storage. The key underpinning piece of such a device would be what we have termed the "decentralized Dropbox contract".

This contract works as follows. First, one splits the desired data up into blocks, encrypting each block for privacy, and builds a Merkle tree out of it. One then makes a contract with the rule that, every N blocks, the contract would pick a random index in the Merkle tree using the previous block hash, accessible from contract code, as a source of randomness , and give X ether to the first entity to supply a transaction with a simplified payment verification-like proof of ownership of the block at that particular index in the tree.

When a user wants to re-download their file, they can use a micropayment channel protocol eg. An important feature of the protocol is that, although it may seem like one is trusting many random nodes not to decide to forget the file, one can reduce that risk down to near-zero by splitting the file into many pieces via secret sharing, and watching the contracts to see each piece is still in some node's possession.

If a contract is still paying out money, that provides a cryptographic proof that someone out there is still storing the file. The members would collectively decide on how the organization should allocate its funds. Methods for allocating a DAO's funds could range from bounties, salaries to even more exotic mechanisms such as an internal currency to reward work. This essentially replicates the legal trappings of a traditional company or nonprofit but using only cryptographic blockchain technology for enforcement.

The requirement that one person can only have one membership would then need to be enforced collectively by the group. A general outline for how to code a DAO is as follows. The simplest design is simply a piece of self-modifying code that changes if two thirds of members agree on a change. Although code is theoretically immutable, one can easily get around this and have de-facto mutability by having chunks of the code in separate contracts, and having the address of which contracts to call stored in the modifiable storage.

In a simple implementation of such a DAO contract, there would be three transaction types, distinguished by the data provided in the transaction:. The contract would then have clauses for each of these. It would maintain a record of all open storage changes, along with a list of who voted for them.

It would also have a list of all members. When any storage change gets to two thirds of members voting for it, a finalizing transaction could execute the change. A more sophisticated skeleton would also have built-in voting ability for features like sending a transaction, adding members and removing members, and may even provide for Liquid Democracy -style vote delegation ie.

This design would allow the DAO to grow organically as a decentralized community, allowing people to eventually delegate the task of filtering out who is a member to specialists, although unlike in the "current system" specialists can easily pop in and out of existence over time as individual community members change their alignments. An alternative model is for a decentralized corporation, where any account can have zero or more shares, and two thirds of the shares are required to make a decision.

A complete skeleton would involve asset management functionality, the ability to make an offer to buy or sell shares, and the ability to accept offers preferably with an order-matching mechanism inside the contract. Delegation would also exist Liquid Democracy-style, generalizing the concept of a "board of directors".

Savings wallets. Suppose that Alice wants to keep her funds safe, but is worried that she will lose or someone will hack her private key. She puts ether into a contract with Bob, a bank, as follows:. If Alice's key gets hacked, she runs to Bob to move the funds to a new contract. If she loses her key, Bob will get the funds out eventually.

If Bob turns out to be malicious, then she can turn off his ability to withdraw. Crop insurance. One can easily make a financial derivatives contract but using a data feed of the weather instead of any price index. If a farmer in Iowa purchases a derivative that pays out inversely based on the precipitation in Iowa, then if there is a drought, the farmer will automatically receive money and if there is enough rain the farmer will be happy because their crops would do well.

This can be expanded to natural disaster insurance generally. A decentralized data feed. For financial contracts for difference, it may actually be possible to decentralize the data feed via a protocol called " SchellingCoin ". SchellingCoin basically works as follows: N parties all put into the system the value of a given datum eg. Everyone has the incentive to provide the answer that everyone else will provide, and the only value that a large number of players can realistically agree on is the obvious default: the truth.

Smart multisignature escrow. Bitcoin allows multisignature transaction contracts where, for example, three out of a given five keys can spend the funds. Additionally, Ethereum multisig is asynchronous - two parties can register their signatures on the blockchain at different times and the last signature will automatically send the transaction. Cloud computing. The EVM technology can also be used to create a verifiable computing environment, allowing users to ask others to carry out computations and then optionally ask for proofs that computations at certain randomly selected checkpoints were done correctly.

This allows for the creation of a cloud computing market where any user can participate with their desktop, laptop or specialized server, and spot-checking together with security deposits can be used to ensure that the system is trustworthy ie.

Although such a system may not be suitable for all tasks; tasks that require a high level of inter-process communication, for example, cannot easily be done on a large cloud of nodes. Other tasks, however, are much easier to parallelize; projects like SETI home, folding home and genetic algorithms can easily be implemented on top of such a platform. Peer-to-peer gambling. Any number of peer-to-peer gambling protocols, such as Frank Stajano and Richard Clayton's Cyberdice , can be implemented on the Ethereum blockchain.

The simplest gambling protocol is actually simply a contract for difference on the next block hash, and more advanced protocols can be built up from there, creating gambling services with near-zero fees that have no ability to cheat. Prediction markets. Provided an oracle or SchellingCoin, prediction markets are also easy to implement, and prediction markets together with SchellingCoin may prove to be the first mainstream application of futarchy as a governance protocol for decentralized organizations.

On-chain decentralized marketplaces , using the identity and reputation system as a base. The motivation behind GHOST is that blockchains with fast confirmation times currently suffer from reduced security due to a high stale rate - because blocks take a certain time to propagate through the network, if miner A mines a block and then miner B happens to mine another block before miner A's block propagates to B, miner B's block will end up wasted and will not contribute to network security.

Thus, if the block interval is short enough for the stale rate to be high, A will be substantially more efficient simply by virtue of its size. With these two effects combined, blockchains which produce blocks quickly are very likely to lead to one mining pool having a large enough percentage of the network hashpower to have de facto control over the mining process. As described by Sompolinsky and Zohar, GHOST solves the first issue of network security loss by including stale blocks in the calculation of which chain is the "longest"; that is to say, not just the parent and further ancestors of a block, but also the stale descendants of the block's ancestor in Ethereum jargon, "uncles" are added to the calculation of which block has the largest total proof-of-work backing it.

To solve the second issue of centralization bias, we go beyond the protocol described by Sompolinsky and Zohar, and also provide block rewards to stales: a stale block receives Transaction fees, however, are not awarded to uncles. Specifically, it is defined as follows:. This limited version of GHOST, with uncles includable only up to 7 generations, was used for two reasons. First, unlimited GHOST would include too many complications into the calculation of which uncles for a given block are valid.

Second, unlimited GHOST with compensation as used in Ethereum removes the incentive for a miner to mine on the main chain and not the chain of a public attacker. Because every transaction published into the blockchain imposes on the network the cost of needing to download and verify it, there is a need for some regulatory mechanism, typically involving transaction fees, to prevent abuse.

The default approach, used in Bitcoin, is to have purely voluntary fees, relying on miners to act as the gatekeepers and set dynamic minimums. This approach has been received very favorably in the Bitcoin community particularly because it is "market-based", allowing supply and demand between miners and transaction senders determine the price. The problem with this line of reasoning is, however, that transaction processing is not a market; although it is intuitively attractive to construe transaction processing as a service that the miner is offering to the sender, in reality every transaction that a miner includes will need to be processed by every node in the network, so the vast majority of the cost of transaction processing is borne by third parties and not the miner that is making the decision of whether or not to include it.

Hence, tragedy-of-the-commons problems are very likely to occur. However, as it turns out this flaw in the market-based mechanism, when given a particular inaccurate simplifying assumption, magically cancels itself out. The argument is as follows. Suppose that:. A miner would be willing to process a transaction if the expected reward is greater than the cost.

Note that R is the per-operation fee provided by the sender, and is thus a lower bound on the benefit that the sender derives from the transaction, and NC is the cost to the entire network together of processing an operation. Hence, miners have the incentive to include only those transactions for which the total utilitarian benefit exceeds the cost. However, there are several important deviations from those assumptions in reality:. There is another factor disincentivizing large block sizes in Bitcoin: blocks that are large will take longer to propagate, and thus have a higher probability of becoming stales.

In Ethereum, highly gas-consuming blocks can also take longer to propagate both because they are physically larger and because they take longer to process the transaction state transitions to validate. This delay disincentive is a significant consideration in Bitcoin, but less so in Ethereum because of the GHOST protocol; hence, relying on regulated block limits provides a more stable baseline.

An important note is that the Ethereum virtual machine is Turing-complete; this means that EVM code can encode any computation that can be conceivably carried out, including infinite loops. EVM code allows looping in two ways. Second, contracts can call other contracts, potentially allowing for looping through recursion. This naturally leads to a problem: can malicious users essentially shut miners and full nodes down by forcing them to enter into an infinite loop? The issue arises because of a problem in computer science known as the halting problem: there is no way to tell, in the general case, whether or not a given program will ever halt.

As described in the state transition section, our solution works by requiring a transaction to set a maximum number of computational steps that it is allowed to take, and if execution takes longer computation is reverted but fees are still paid. Messages work in the same way. To show the motivation behind our solution, consider the following examples:. With this system, the fee system described and the uncertainties around the effectiveness of our solution might not be necessary, as the cost of executing a contract would be bounded above by its size.

Additionally, Turing-incompleteness is not even that big a limitation; out of all the contract examples we have conceived internally, so far only one required a loop, and even that loop could be removed by making 26 repetitions of a one-line piece of code. Given the serious implications of Turing-completeness, and the limited benefit, why not simply have a Turing-incomplete language?

In reality, however, Turing-incompleteness is far from a neat solution to the problem. To see why, consider the following contracts:. Now, send a transaction to A. Thus, in 51 transactions, we have a contract that takes up 2 50 computational steps. Miners could try to detect such logic bombs ahead of time by maintaining a value alongside each contract specifying the maximum number of computational steps that it can take, and calculating this for contracts calling other contracts recursively, but that would require miners to forbid contracts that create other contracts since the creation and execution of all 26 contracts above could easily be rolled into a single contract.

Another problematic point is that the address field of a message is a variable, so in general it may not even be possible to tell which other contracts a given contract will call ahead of time. Hence, all in all, we have a surprising conclusion: Turing-completeness is surprisingly easy to manage, and the lack of Turing-completeness is equally surprisingly difficult to manage unless the exact same controls are in place - but in that case why not just let the protocol be Turing-complete? The Ethereum network includes its own built-in currency, ether, which serves the dual purpose of providing a primary liquidity layer to allow for efficient exchange between various types of digital assets and, more importantly, of providing a mechanism for paying transaction fees.

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