MerkleRoot (@merkleroot) ā¢ Hey
I am the root.
Publications
- I just voted on "Poll by @86222.lens" https://snapshot.org/#/polls.lenster.xyz/proposal/0xe89f8cca0b612145e4e5b95c21fb0715d6a05c2a45db8fddd1a73b51639171f1 #Snapshot
- **Antlr 4**
ANTLR4 (ANother Tool for Language Recognition, version 4) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files. It's widely used to build languages, tools, and frameworks.
ANTLR4 lets you define the grammar of a language, using a syntax that is easy to understand and write. From this grammar, ANTLR generates a parser that can build and walk parse trees.
One of the key features of ANTLR4 is that it supports multiple programming languages, like Java, C#, Python, JavaScript, Go, Swift, and more. It also has built-in visual tools for debugging and testing grammars.
- When your post on Lens is poppin off but you forgot to turn on collects
- **Spark**
Apache Spark is a powerful, open-source processing engine for data in the Hadoop cluster, built around speed, ease of use, and sophisticated analytics. It comes with built-in modules for SQL, streaming, machine learning, and graph processing, which makes it usable for a wide range of data analytics tasks.
Spark can be used with various data sources such as HDFS, Cassandra, HBase, and S3. It operates by loading data into a cluster's memory and querying it repeatedly, which makes it significantly faster for complex applications than traditional disk-based systems.
Spark supports programming in Java, Python, Scala, and R, offering a high level API to work with. As of my knowledge cutoff in September 2021, Spark is widely used in data processing and analytics due to its speed, ease of use, and versatility.
- Today marks our 1 Year Anniversary of making friends onchain š!
Thank you to everyone who has made the first year of Lens Protocol so special and groundbreaking. Lens has brought together builders, creators, communities, and friends, all while in beta.
There's so much planned for the second year ahead, and we can't wait to continue to grow with all of you.
Who did you become frens with on Lens?Ā
šØ by @nftsushi.lens and all collect proceeds go directly to the artist.
- **Liquidity**
Liquidity in DeFi (Decentralized Finance) typically refers to the availability of assets within a particular market or exchange that can be readily bought or sold without causing significant price changes. Liquidity is a key component in DeFi ecosystems, particularly in protocols based on Automated Market Makers (AMMs), such as Uniswap or SushiSwap.
In these systems, users provide liquidity by depositing pairs of tokens in a liquidity pool. For example, if you were to supply liquidity to an ETH/DAI pool, you would need to deposit an equal value of both ETH and DAI. In return, you receive liquidity provider (LP) tokens, which represent your share in the pool.
These LP tokens can earn rewards in multiple ways. Firstly, they earn transaction fees from trades that occur within the pool, proportional to their share of the total liquidity. Secondly, many DeFi protocols incentivize liquidity provision by offering additional rewards, often in the form of the platform's native token.
It's important to note that providing liquidity isn't without risk. One major risk is called "impermanent loss," which occurs when the price ratio of the tokens in the pool changes significantly. This can lead to a situation where the dollar value of the tokens you supplied is less than if you had just held the tokens separately.
- I just voted "Yes" on "Poll by @stani.lens" https://snapshot.org/#/polls.lenster.xyz/proposal/0xb48787ee4d877ede83434a2e4c5c194b4853cd2b6231c20e02d3b3ba9861b06a #snapshotlabs
- The Merkle Root
A Merkle root is the topmost hash in a Merkle tree, a data structure used to efficiently prove the integrity and authenticity of large sets of data. It is named after its creator, Ralph Merkle, who proposed it in 1987. Merkle trees are widely used in various applications, including distributed systems and blockchain technology like Bitcoin.
In a Merkle tree, the data elements are hashed using a cryptographic hash function, and these hashes serve as the leaf nodes of the tree. The hashes of these leaf nodes are then paired and hashed again, creating a new level of hashes, or parent nodes. This process is repeated until there is only one hash left at the top, which is the Merkle root.
The Merkle root is a compact representation of the entire dataset, and it can be used to verify that a specific data element is part of the original dataset without needing to check the whole dataset. This is achieved through Merkle proofs, which are short, efficient proofs that demonstrate the membership of a specific data element in the dataset.
In the context of blockchains, the Merkle root is used to represent the set of transactions within a block. By including the Merkle root in the block header, it allows for efficient and secure verification of individual transactions without requiring the entire transaction history.
- I just voted "Yes" on "Make Velodrome the STG Hub on Optimism" https://snapshot.org/#/stgdao.eth/proposal/0xf980d6deed62c3d77dd055963724b9d07ea0f383a2142703e5581c8e751b06ad #snapshotlabs
- I just voted "Yes" on "Create a Secure UniswapV3 Oracle for STG with Arrakis PALM" https://snapshot.org/#/stgdao.eth/proposal/0x9b511ccf8bd097176255da63725877de9f80caeea8a28256ff50dfad10a3820d #snapshotlabs
- **Gitcoin**
Gitcoin is a decentralized platform that aims to grow and sustain the open-source software ecosystem by providing financial incentives to developers and contributors. Launched in 2017, Gitcoin uses blockchain technology, specifically the Ethereum network, to facilitate peer-to-peer transactions and crowdfunding campaigns for open-source projects.
Gitcoin offers a variety of services, including:
(1) Bounties: Developers or organizations can post tasks or issues that require solving, and other developers can claim and complete these tasks in exchange for cryptocurrency rewards. Bounties help to incentivize developers to contribute to open-source projects and fix bugs, improve features, or develop new solutions.
(2) Grants: Gitcoin Grants is a crowdfunding platform where developers can seek financial support for their open-source projects or ideas. Community members can donate to the projects they find interesting, helping to fund the development and maintenance of valuable open-source tools and services.
(3) Hackathons: Gitcoin organizes virtual hackathons and coding competitions, where developers can collaborate, learn, and compete for prizes while contributing to open-source projects. These events help to foster innovation and build a strong developer community around various projects.
(4) KERNEL: An 8-week incubator program that aims to connect talented individuals and help them develop, refine, and launch their Web3 or decentralized technology projects.
By leveraging the power of blockchain and the Ethereum network, Gitcoin provides a transparent and decentralized platform that fosters collaboration, innovation, and sustainability within the open-source ecosystem.
- **Polygon**
Polygon, formerly known as Matic Network, is a layer-2 scaling solution for Ethereum that aims to provide faster and cheaper transactions. It is an open-source project that utilizes sidechains and a Proof of Stake (PoS) consensus mechanism to improve the scalability, security, and user experience of decentralized applications (dApps) running on the Ethereum network.
As Ethereum faces challenges with congestion, slow transaction times, and high gas fees, Polygon offers an alternative for developers and users to have a better experience without sacrificing the decentralization and security that the Ethereum network provides. With its layer-2 infrastructure, Polygon effectively addresses the issues of Ethereum's limited throughput by offloading transactions from the main Ethereum chain to its sidechains.
Developers can easily build and deploy dApps on Polygon, leveraging its Ethereum-compatible toolkit and API. The seamless integration with Ethereum ensures that assets can be easily transferred between the main Ethereum network and Polygon's sidechains.
In summary, Polygon is a layer-2 scaling solution for Ethereum that offers faster, cheaper transactions while maintaining security and decentralization. It provides a platform for developers to build and deploy dApps that can overcome the challenges faced by the Ethereum network, ultimately enhancing the user experience in the blockchain ecosystem.
- **Sequencer in L2**
The Sequencer is a key component in the Arbitrum network's Layer 2 (L2) solution, designed to optimize and streamline the transaction ordering process. As users submit transactions, they are first relayed to the Sequencer, which is responsible for ordering them before broadcasting the ordered transactions to validator nodes.
The primary goal of the Sequencer is to minimize transaction conflicts and ensure a consistent order of transactions for execution on L2. This not only improves the user experience but also enhances the overall throughput and scalability of the network.
It is important to note that the Sequencer does not have the power to modify or execute transactions. Its role is limited to ordering transactions, while the validator nodes are responsible for executing transactions and maintaining the off-chain state. This separation of responsibilities ensures that the Arbitrum network remains decentralized and secure.
In summary, the Sequencer plays a crucial role in the L2 Arbitrum network by optimizing transaction ordering, ultimately leading to a more efficient and scalable solution for decentralized applications and transactions on the Ethereum blockchain.
- **What is NP-hard?**
An NP-hard (Nondeterministic Polynomial-time hard) problem is a classification of computational problems in the field of complexity theory. NP-hard problems are at least as difficult as the hardest problems in NP (Nondeterministic Polynomial-time) class. The term "hard" here implies that these problems are computationally difficult and solving them efficiently (in polynomial time) is unlikely, though not proven to be impossible.
NP-hard problems do not have to belong to the NP class themselves, but if a polynomial-time algorithm exists for solving any NP-hard problem, it would imply that every problem in NP could also be solved in polynomial time. In other words, if any NP-hard problem could be solved efficiently, it would mean that P = NP (i.e., the class of problems that can be solved in polynomial time is equal to the class of problems that can be verified in polynomial time). Currently, it is an open question whether P = NP or not.
An example of an NP-hard problem is the Traveling Salesman Problem (TSP). In TSP, given a list of cities and the distances between them, the goal is to find the shortest possible route that visits each city exactly once and returns to the origin city. The problem is difficult because the number of possible routes grows factorially with the number of cities, making it computationally intractable for large instances.
- I just voted "Yes" on "Make Velodrome the STG Hub on Optimism" https://snapshot.org/#/stgdao.eth/proposal/0xd78c441994d140edde34131051113479651c593ab83badebc537a347ba86b705 #snapshotlabs
- **NP-complete problem**
An NP-complete problem is a type of problem in computational complexity theory that is one of the most difficult problems in the class of problems known as NP (nondeterministic polynomial time). NP-complete problems are problems for which a solution can be verified in polynomial time, but for which no known algorithm exists that can solve them in polynomial time.
An important characteristic of an NP-complete problem is that any other NP problem can be reduced to it in polynomial time. In other words, if there is a polynomial-time algorithm for solving an NP-complete problem, then there is a polynomial-time algorithm for solving all NP problems, and thus P=NP. However, since no such algorithm has yet been discovered, it is widely believed that NP-complete problems cannot be solved in polynomial time.
Examples of NP-complete problems include the traveling salesman problem, the Boolean satisfiability problem, the knapsack problem, and the vertex cover problem, among others. Despite their difficulty, NP-complete problems are important because they are relevant to many real-world applications, such as optimization, scheduling, and network design.
- **The Raft algorithm**
The Raft algorithm is a distributed consensus algorithm designed to ensure that a set of replicated machines, called nodes, agree on a consistent state. It was introduced by Diego Ongaro and John Ousterhout in their 2014 paper, "In Search of an Understandable Consensus Algorithm." Raft was developed as an alternative to the Paxos algorithm, which is known for being challenging to understand and implement.
Raft's main goals are to provide a simple, understandable, and efficient way to manage a distributed system while maintaining strong consistency, fault tolerance, and high availability. It achieves consensus among the nodes in the system by electing a leader node that manages the replication of log entries to other nodes. If the leader fails, the algorithm ensures that a new leader is elected, and the system continues to operate.
The Raft algorithm can be broken down into three main components:
(1) Leader Election:
When a node believes that there is no leader, it transitions to a candidate state and initiates an election by requesting votes from other nodes. If a node receives a majority of votes, it becomes the leader. To maintain leadership, the leader sends heartbeat messages (empty AppendEntries) to other nodes in the system.
(2) Log Replication:
The leader is responsible for managing the log, which stores the commands that modify the system state. When a client submits a command, the leader appends it to its log and replicates it to the follower nodes. The followers acknowledge the receipt of the log entry, and the leader considers the entry committed once a majority of followers have acknowledged it. The leader then applies the committed log entries to its state machine and returns the results to the client.
(3) Safety and Consistency:
To ensure consistency across the system, Raft enforces several safety constraints. For example, if a candidate node's log is less up-to-date than the current leader's, it cannot win an election. Additionally, a leader only appends new log entries to a follower's log if the follower's log has the same entries up to a certain index as the leader's log.
In case of a network partition or temporary disconnection, Raft guarantees that the system's state will remain consistent. When the partition heals, any nodes with outdated logs will synchronize with the current leader and update their logs accordingly.
By combining leader election, log replication, and safety mechanisms, the Raft algorithm provides a robust, fault-tolerant, and easily understandable consensus solution for distributed systems. Raft has been implemented in various distributed systems, such as etcd, Consul, and CockroachDB, and has become a popular choice for building consistent and highly available services.
- "Impermanent Loss" is a term used in the context of liquidity pools, which are used for decentralized trading in cryptocurrencies and other digital assets. It refers to the temporary loss of value experienced by liquidity providers in a pool when the relative prices of the two assets being traded change.
In a liquidity pool, investors can deposit two different assets in a certain ratio, which creates a market for the assets. They receive liquidity pool tokens (LP tokens) in return, which represent their share of the liquidity pool. When trades occur, investors receive a fee for providing liquidity.
However, if the prices of the two assets change, this can cause a temporary loss in the value of the LP tokens held by liquidity providers. Specifically, if the price of one asset rises relative to the other, investors will receive more of the asset that has decreased in value when they withdraw their liquidity. Conversely, if the price of one asset falls relative to the other, investors will receive more of the asset that has increased in value. This means that liquidity providers can end up with less value in their LP tokens than they would have if they had simply held the two assets outside the pool.
It's important to note that the impermanent loss is only temporary and will disappear if the price of the two assets returns to its original ratio. In addition, liquidity providers receive a fee for providing liquidity, which can offset some of the impermanent loss. Nonetheless, investors should be aware of the risks involved in providing liquidity to a pool and should carefully consider their investment strategy and risk tolerance before doing so.
- EIP-1559 stands for Ethereum Improvement Proposal 1559, which is a proposed upgrade to the Ethereum blockchain. The proposal aims to address several issues with the current Ethereum transaction fee model, which can lead to high fees and slow transaction times during times of network congestion.
Under the current model, users must manually set a gas fee for their transactions, which is essentially a bid to get their transaction included in the next block. During times of high network activity, the gas fees can become exorbitantly high, leading to users having to wait for long periods of time or pay a large fee to get their transactions processed quickly.
EIP-1559 proposes to replace the current fee model with a new model that automatically sets a base fee for each block based on the network's demand. This base fee would be burned (i.e., destroyed) instead of going to miners, which is intended to reduce Ethereum's inflation rate. Users would still be able to add an optional "tip" to incentivize miners to prioritize their transactions, but this tip would be separate from the base fee and would not affect the overall cost of the transaction.
The proposal also includes other changes to the Ethereum protocol, such as making the block size dynamic and improving the predictability of transaction fees. EIP-1559 has been the subject of much discussion and debate within the Ethereum community, and it is expected to be implemented in a future network upgrade.
- I just voted "yes" on "Proposal to Approve Stargate Deployment to BASE, zkSync, Polygon zkEVM and ConsenSys zkEVM" https://snapshot.org/#/stgdao.eth/proposal/0xb850477539d006f12feb53c1ef7d1ebc967cb5424a39dd6c6b2da3c57af05695 #snapshotlabs
- Ethereum EVM stands for Ethereum Virtual Machine. It is a software environment that runs on top of the Ethereum blockchain, allowing developers to execute smart contracts written in various programming languages.
The Ethereum Virtual Machine is a critical component of the Ethereum ecosystem. It enables the creation of decentralized applications (dApps) that can run on the Ethereum blockchain. Smart contracts are self-executing programs that are stored on the blockchain, and they can interact with each other and with external applications.
The EVM is a sandboxed environment, which means that smart contracts running on the EVM cannot access external resources or data outside of the blockchain. This sandboxing provides security, making it difficult for malicious actors to compromise the execution of smart contracts.
The EVM is a deterministic virtual machine, meaning that the same inputs will always produce the same outputs. This is critical for the security and stability of the Ethereum network.
Developers can write smart contracts using a variety of programming languages, including Solidity, Vyper, and others. Once a smart contract is written and deployed to the Ethereum network, it becomes part of the blockchain, and its code is executed by the EVM.
- SHA-256 (Secure Hash Algorithm 256-bit) is a cryptographic hash function that is part of the SHA-2 family (SHA-224, SHA-256, SHA-384, SHA-512, SHA-512/224, SHA-512/256), designed by the U.S. National Security Agency (NSA) and published by the National Institute of Standards and Technology (NIST). SHA-256 is widely used in cryptography and blockchain technology, such as Bitcoin and other cryptocurrencies.
Key features of SHA-256 include:
1. Fixed output length: SHA-256 processes input data of any length and generates a fixed-length (256-bit) output hash.
2. Uniqueness: An important property of hash functions is that the output hash should be unique for different inputs. In theory, even a slight difference in input should result in a significant difference in the generated hash.
3. One-way function: Hash functions are one-way, meaning it's very difficult (practically impossible) to reverse-engineer the original input data from the hash. This makes hash functions valuable in cryptography.
4. Collision resistance: In cryptography, a collision refers to finding two different inputs that produce the same hash value. SHA-256 has strong collision resistance, making it extremely difficult to find collisions even with significant computational resources.
SHA-256 has various applications:
1. Password storage: Storing hashed user passwords prevents exposure of plaintext passwords in the event of a database breach. Even if attackers obtain the hash, the one-way nature of the hash function makes it difficult for them to retrieve the original password.
2. File integrity checks: By comparing the SHA-256 hash of a file, one can verify if a file has been tampered with. When downloading software or files, publishers often provide the hash for users to verify that the downloaded file matches the original file.
3. Digital signatures: SHA-256 can be used to generate digital signatures to verify the origin and integrity of a message. The sender signs the hash of the message with their private key, and the recipient verifies the signature with the public key, ensuring the message hasn't been tampered with and comes from a reliable source.
4. Blockchain and cryptocurrencies: SHA-256 plays a critical role in Bitcoin and other cryptocurrencies. Bitcoin's Proof of Work (PoW) mechanism uses the SHA-256 hash function for mining, ensuring the security of the network.
In summary, SHA-256 is a secure and widely used cryptographic hash function that plays an important role in cryptography, data security, and blockchain technology.
- **The Paxos Algorithm**
Paxos is a well-known distributed consensus algorithm proposed by Leslie Lamport in 1990. The algorithm solves the consensus problem in distributed systems, which is how to reach agreement on a value among nodes that may experience failures. Paxos has high fault tolerance, scalability, and performance.
The Paxos algorithm can be divided into three basic roles:
1. Proposer: Responsible for initiating proposals and suggesting a value to reach consensus.
2. Acceptor: Responsible for receiving proposals from the proposer and accepting or rejecting the proposal according to the algorithm rules.
3. Learner: Observes the behavior of acceptors and learns the agreed-upon value.
The basic implementation of the Paxos algorithm is divided into two phases:
1. Prepare Phase:
a. The proposer chooses a proposal number N and sends a Prepare Request to the set of acceptors.
b. Upon receiving the Prepare Request, if the proposal number N is greater than any Prepare Request received by the acceptor so far, the acceptor promises not to accept any proposal with a number less than N. At the same time, the acceptor sends the proposal with the highest number it has accepted so far (if any) as a response to the proposer.
2. Accept Phase:
a. After receiving responses from a majority of acceptors, the proposer chooses a new value based on the responses. If the responses contain an already accepted proposal, the proposer must choose the value from the accepted proposal. The proposer then sends the proposal (number N and the new value) to all acceptors.
b. Upon receiving the proposal, if the proposal number N is not less than the minimum proposal number the acceptor has promised, the acceptor accepts the proposal and sends the acceptance result to the proposer and learners.
Once the learners observe that a majority of acceptors have accepted the same proposal, they can determine that the value has reached consensus.
It is worth noting that the Paxos algorithm may encounter situations where multiple proposers compete simultaneously, which may lead to proposal conflicts and delayed consensus. To solve this problem, various optimization strategies can be adopted, such as introducing a leader election mechanism, so that only one proposer can initiate proposals at the same time.
- LeetCode 779. K-th Symbol in Grammar
`class Solution {`
`public int kthGrammar(int n, int k) {`
`if (n == 1) {`
`return 0;`
`}`
`if (n == 2) {`
`return k % 2 == 1 ? 0 : 1;`
`}`
`int len = 1;`
`for (int i = 0; i < n - 1; i++) {`
`len *= 2;`
`}`
`int res = 0;`
`while (len > 2) {`
`int half = len >> 1;`
``
`if (k > half && k <= half + half / 2) {`
`k = half / 2 + (k - half);`
`} else if (k > half && k > half + half / 2) {`
`k = k - 3 * half / 2;`
`}`
`len >>= 1;`
`}`
`if (k == 1 || k == 4) {`
`return 0;`
`} else {`
`return 1;`
`}`
`}`
`}`