Blockchain Guide

1. What problem is the project solving, and how does the blockchain uniquely address this?

• Understand the project's core purpose, use case, and why blockchain is essential for its solution.
• Note that even as a layer 2 or application specific project it is important to understand the basic layer underneath it and its dependencies.

2. What is the project's consensus mechanism and how does it impact scalability, security, and decentralization?

• A broad look at how the blockchain secures itself and whether it can handle growth.

3. What role does the native token play within the ecosystem, and how are users incentivized to participate?

• A basic understanding of token utility, rewards, and overall economic model.

4. How decentralized is the network, and what measures are in place to ensure fair governance and validator distribution?

• Understanding of the project's commitment to decentralization and governance mechanisms.

5. What does the project roadmap look like, and what key milestones have been achieved so far?

• A first impression of how well the team is executing on its promises and what future developments to expect.

1. EVM or Non-EVM?

Is the blockchain Ethereum Virtual Machine (EVM) compatible or does it have its own unique virtual machine?

• If EVM, Solidity-based smart contracts are likely being used, and Ethereum tooling is available.
• If non-EVM, different language support and unique VM architecture will be needed (e.g., Rust for Solana or Move for Sui).

2. UTXO or Account-Based Model?

Does the blockchain use a UTXO (Unspent Transaction Output) model like Bitcoin, or an account-based model like Ethereum?

• UTXO-based blockchains focus on individual outputs for transactions, whereas account-based blockchains track balances tied to an account address.
• The UTXO model can provide slightly better privacy, since users might have multiple funds distributed across various unspent outputs. However, this places strain in wallet implementations, since they have to track multiple outputs to compute how many funds a user owns. Also, when sending a transaction the wallet has to spend said outputs and provide fresh addresses/public keys for change amounts. If not managed correctly this can lead to bad user experience (UX).
• The account based model makes state management easier, since each account has a single state entry, which stores the balance, along with other information.

3. Addressing Format (Hexadecimal, Base58, Bench32,...)

What is the addressing format used for accounts or wallets on the blockchain (Hexadecimal like Ethereum/Avalanche(C), Base58 like Bitcoin/Solana, Bech32 like BTC SegWit/Avalanche(P and X), SS58 like Polkadot/Substrate)?

• Understanding this helps with integration of wallets, tools, and user interaction with the blockchain.
• Base58 is more readable and avoids confusion between 0 ("zero") and capital O ("oh"), while Bech32 is similar but with a prefix that can distinguish between the same address in different networks.
• SS58 used in Substrate also employs a network prefix so that the same wallet public key leads to visibly different addresses in different networks, while still using base58 for readability.

4. Consensus Mechanism

What consensus mechanism is used (Longest chain, Practical Byzantine Fault Tolerance, Casper FFG/GHOST, BABE/GRANDPA, Tendermint, HotStuff/Diem/AptosBFT, etc.)?

• Choice of consensus mechanism impacts network security, decentralization, scalability, energy efficiency, among other factors.
• Examples:
  • Bitcoin uses the Longest Chain (PoW) model, prioritizing security and simplicity but sacrificing energy efficiency. Ethereum's transition to Proof of Stake (PoS) introduced Casper FFG, a hybrid protocol that balances security and speed using the GHOST fork choice rule. Cosmos adopted Tendermint (based on PBFT), emphasizing fast finality and low latency, which set a precedent for chains like Sei. Polkadot opted for a dual-consensus model with BABE (block production) and GRANDPA (finality), combining speed and resilience.
  • Avalanche innovated with its DAG-based consensus (Slush), and also created a block-based version (Snowman++) to support the C-Chain, which offers high throughput while maintaining EVM compatibility. Meta's Libra, now defunct, made improvements upon HotStuff, which inspired successors Aptos and Sui, each adapting it for improved speed and efficiency. Monad aims to push this further, addressing existing trade-offs like latency versus TPS, showcasing the ongoing evolution in consensus design focused on optimizing performance.
  • The HotStuff consensus algorithm and its derived successors all share the same main cryptographic requirement: signature aggregation is necessary in order to maintain linear scalability. However, these signatures are not ready for the advent of quantum computers. BitFashioned team members have done research on this topic, creating a novel consensus protocol (xxBFT), which achieves linear scalability regardless of the type of signature scheme used. This way, xxBFT can be used with, for example, hash-based quantum secure signatures and stay safe even in the presence of quantum computers.

5. Validator Set

Who can become a validator, is it permissionless or permissioned? How are validators selected? (Proof of Work, Proof of Stake, Delegated PoS)

• How can anyone join the network as a validator and which rules are in place.
• Examples:
  • Networks like Bitcoin are Permissionless, anyone can join to validate and propose blocks. To ensure that a single entity can't spin up multiple validators and take over the network, Proof of Work is used to ensure Sybil Resistance. The security is provided by computational power.
  • Networks like Ethereum use Proof of Stake instead. In this case to spin up multiple validators an entity has to Stake more funds, so the security is provided by economics instead.
  • Other networks like Polkadot and Cosmos use a Delegated Proof of Stake model, which allows users to stake their funds on existing validators instead of running one themselves.

6. Smart Contract Language

If the blockchain is EVM-compatible, are smart contracts written in Solidity? If not, what language is used (e.g., Vyper, Rust, Move)?

• The smart contract language used by a chain is directly tied to how it executes code, i.e. the chain's Virtual Machine (VM). Developers will write code in one of the supported languages, and then a compiler will convert that into bytecode that can be interpreted by the VM.
• Examples:
  • Ethereum's execution environment is called the Ethereum Virtual Machine (EVM). Solidity is the most popular language to write EVM contracts. There are other languages that also compile bytecode for the EVM, such as Yul and Vyper. A lot of blockchains use the EVM, due to the popularity of Solidity and the vast amount of existing tooling (see point 20 below).
  • Solana smart contracts are developed in Rust, with a code library that facilitates compatibility with the Solana Virtual Machine (SVM). This makes it more attractive to developers that already know Rust or other high level programming languages, instead of having to learn a new language like Solidity.
  • Polkadot smart contracts are developed in Ink!, which is a Rust-based custom language. Contracts are compiled into WASM bytecode and executed in a WASM interpreter that runs as part of the Polkadot Runtime.
  • More modern chains like Aptos and Sui use the Move Virtual Machine, which supports the Move programming language that was developed by the Diem project. Move is gaining a lot of traction because of its efficiency and object-oriented nature.

7. Transaction Finality

How long does it take for transactions to achieve finality, and is finality probabilistic or deterministic (e.g., Bitcoin's/Ethereum's old (PoW) probabilistic finality vs. Tendermint's deterministic finality)?

• Affects user experience and security guarantees.
• Examples:
  • Bitcoin and other Proof of Work (PoW) blockchains like Ethereum (pre-Merge) rely on probabilistic finality, where a transaction is considered final after a certain number of block confirmations (e.g., 6 blocks for Bitcoin), making finality slower but highly secure. By contrast, blockchains like Cosmos (using Tendermint) and Polkadot (with GRANDPA) use deterministic finality, where transactions are finalized as soon as a block is added, typically within seconds. This provides faster, more predictable finality times, enhancing user experience.
  • Avalanche offers near-instant finality through its Snowman consensus, delivering high throughput without compromising on speed. Ethereum's shift to PoS (post-Merge) introduces faster finality via Casper FFG, reducing wait times compared to its previous PoW model. Newer blockchains like Aptos leverage the HotStuff BFT variant for rapid deterministic finality, while Monad aims to minimize latency, pushing towards sub-second finality times for improved throughput and user experience.

8. Scalability Techniques

What scalability solutions are implemented? Does the blockchain use sharding, layer 2 solutions (rollups, plasma), sidechains, or a combination?

• Critical for handling large volumes of transactions and smart contract executions.
• Examples:
  • Blockchains employ various methods like Layer 2 solutions, sharding, and sidechains to address scalability challenges. Ethereum initially focused on Layer 2 rollups (e.g., Optimistic and ZK-rollups) to process transactions off-chain, reducing congestion and fees. Now, Ethereum plans to implement protosharding, an early stage of sharding, to split the network into smaller partitions called shards, increasing throughput by processing multiple transactions in parallel.
  • NEAR Protocol uses Nightshade sharding, a unique approach where each shard handles a subset of transactions, but the state remains unified. This method aims to provide seamless scalability while maintaining network security and efficiency.
  • Bitcoin, in contrast, scales primarily through Layer 2 solutions like the Lightning Network, which handles micropayments off-chain using payment channels. This significantly reduces congestion on the main Bitcoin network and allows for near-instant transactions at minimal cost.
  • Polkadot and Cosmos use sharded multi-chain architectures, where independent parachains (Polkadot) or zones (Cosmos) run transactions in parallel, enhancing throughput. Avalanche leverages subnets and its DAG-based consensus, isolating specific applications to avoid congestion on the main chain. Solana relies on its unique Proof of History (PoH) mechanism, enabling high throughput on a single-chain architecture without using sharding or Layer 2s.
  • Newer projects like Aptos and Sui experiment with parallel execution techniques and advanced data structures to push the boundaries of scalability. These innovations illustrate the diverse approaches taken by blockchains to balance complexity, security, and throughput for optimal performance.

9. Gas Model (Fee Structure)

Is there a gas model for transactions and smart contract executions (like Ethereum), and how are fees calculated?

• Determines user transaction costs and how developers optimize contracts for cost-efficiency.
• Examples:
  • While Ethereum's gas fees are dynamically determined by an open market, with prices increasing as demand for block space grows, Solana uses a different approach. Solana's fee structure is fixed and designed around parallel transaction processing, which allows for higher throughput. Increased usage doesn't automatically raise fees, as Solana checks for smart contract execution dependencies and prioritizes parallel processing, which keeps transaction costs low as long as there's no resource contention.

10. Interoperability and Cross-Chain Communication

Does the blockchain support interoperability with other chains? If so, how are cross-chain interactions or atomic swaps handled?

• Cross-chain communication is essential for multi-chain projects and DeFi applications that need to interact across different blockchain networks. Many leading blockchain platforms have developed sophisticated interoperability solutions to enable secure and efficient cross-chain transactions.
• Examples:
  • Cosmos, through its Inter-Blockchain Communication (IBC) protocol, allows blockchains within its ecosystem to securely transfer tokens and data across independent chains, making it a leader in decentralized cross-chain transfers.
  • Polkadot employs its Cross-Chain Messaging Protocol (XCMP), which facilitates secure and efficient communication between its parachains, allowing them to exchange messages and assets without the need for third-party bridges.
  • Chainlink, with its Cross-Chain Interoperability Protocol (CCIP), takes interoperability further by enabling smart contracts on different blockchains to interact, allowing for token and data transfers across distinct ecosystems.
  • Meanwhile, Avalanche offers multiple cross-chain solutions, including the Avalanche Bridge (AB) for asset transfers between Avalanche and Ethereum, as well as its Warp Messaging system, which allows subnets within Avalanche to communicate securely. This technical solution makes it easier for dApps and other blockchain networks to interact and collaborate in real time. Together, these technologies showcase the growing importance of interoperability for multi-chain DeFi and dApp ecosystems.

11. Forking and Network Upgrades

What is the process for handling hard forks and network upgrades? How is backward compatibility maintained?

• Important for developers who need to upgrade smart contracts or adapt to protocol changes.
• Example:
  • Ethereum follows a traditional model where upgrades are proposed via Ethereum Improvement Proposals (EIPs). Validators and node operators must manually implement changes, often leading to hard forks if there's no consensus, like the Ethereum Classic split. Upgrades require significant coordination, and backward compatibility isn't always guaranteed.
  • Polkadot and Cosmos use on-chain governance for more seamless upgrades. In Polkadot, upgrades are automatically implemented once approved by token holders, avoiding manual hard forks. Cosmos follows a similar model but relies on validators to implement changes after governance approval. Both use modular architectures—Polkadot with its relay chain and parachains, and Cosmos with its hub-and-spoke IBC model—allowing independent blockchains to upgrade with minimal disruption. Polkadot's process is more automated, while Cosmos gives more autonomy to individual chains.
  • Sui enables flexible upgrades through the Move programming language, allowing changes without major disruptions. Its governance involves validators voting on changes, ensuring smooth upgrades and backward compatibility for developers.
  • Avalanche uses a modular subnet architecture, allowing each subnet to upgrade independently. Validators must upgrade nodes after governance decisions, with Warp Messaging ensuring subnets stay compatible post-upgrade, reducing disruptions.
  • Solana handles upgrades by requiring validators to quickly update software during protocol changes. Its design minimizes disruption while maintaining performance, ensuring backward compatibility and avoiding major forks through effective validator coordination.
  • Cardano focuses on security and stability, using formal verification in its Ouroboros consensus. Upgrades are decided through on-chain voting and introduced carefully to ensure backward compatibility. Though slower, Cardano's rigorous testing reduces risk and errors during upgrades.

  Overall, platforms like Polkadot and Cosmos focus on automation, while Ethereum, Solana, and Cardano rely on validator coordination and community-driven decisions to implement changes effectively.

12. Block Time and Throughput

What is the average block time, and what is the transaction throughput (TPS)?

• Critical for evaluating the speed and performance of the network.
• Stats here

13. Node Types and Roles

What types of nodes exist (light, full and Blog nodes?), and what are their roles in the network?

• Helps in understanding the network infrastructure and decentralization.
• Example: Generally speaking, these are the most common node types:
  • Light nodes download only essential data, allowing them to verify transactions more efficiently but without storing the full blockchain - crucial for network accessibility, especially on mobile devices or low-power environments, without sacrificing security.
  • Full nodes store the entire blockchain and validate transactions, ensuring the security and integrity of the network.
  • Blog nodes go further by storing historical states of the blockchain, which makes them useful for data recovery and deep analysis.

14. Light Client Support

Does the blockchain support light clients, allowing users to interact with the network without running a full node?

• Supporting light clients is essential for increasing blockchain accessibility, particularly for mobile or lightweight applications, without requiring users to run full nodes. In networks like Ethereum, client diversity is a key factor in maintaining decentralization and network resilience. By operating multiple clients, such as Geth and OpenEthereum, Ethereum ensures that even if the internal logic of each client differs, they all achieve the same final state, preserving consistency across the network. This diversity also allows for optimization in areas like Remote Procedure Call (RPC) performance, which is crucial for light clients that rely heavily on RPCs to retrieve state data.

• Light clients, while efficient, have limitations. For instance, they don't fully participate in consensus and rely on full nodes to provide updates on transaction statuses. This introduces a challenge, as there's typically no proof on the client side that the transaction was executed, as light clients depend on RPC communications or centralized databases (e.g., indexes from full nodes) to reflect state changes. In cases where deferred execution models are used, such as in certain consensus protocols, the need for real-time verification through trusted sources becomes even more important, underscoring the trade-off between efficiency and security.

• The current status quo is that without light client involvement, wallets receive state updates via RPC or centralized databases rather than directly proving execution, which poses a potential centralization risk. Supporting light clients effectively helps address this gap, enhancing decentralization by allowing users to verify states more independently.

15. Data Storage and Pruning

How is blockchain data stored? Does the blockchain support data pruning or light clients to reduce the burden on full nodes?

• Critical for long-term network sustainability and ease of running nodes.
• Example:
  • Blockchain data storage becomes a major challenge as networks grow, with full nodes needing to store vast amounts of historical data. Data pruning helps alleviate this by allowing nodes to discard old, unnecessary data while maintaining the current state and recent history. Ethereum supports pruning, making it easier for full nodes to manage storage while still validating transactions. Additionally, light clients further reduce the storage burden by only downloading minimal data like block headers, leaving the rest to full nodes.
  • However, not all blockchains handle this equally well. In projects like Cosmos and Polkadot, modular architectures allow nodes to handle data storage more flexibly, with some relying on full nodes or Blog nodes to store historical data. In contrast, more efficient models focus on the real-time state necessary for validation and operations.

16. Governance Mechanism

What governance mechanism does the blockchain use? Is it on-chain governance (e.g., Polkadot, Tezos), or is it off-chain (e.g., Bitcoin)?

• Governance has a crucial impact on blockchain decision-making and upgrade processes, with different models offering distinct trade-offs.
• Examples:
  • On-chain governance:
    • Polkadot and Cosmos use community-driven voting for network upgrades, enabling faster evolution but requiring careful validator coordination.
    • Algorand implements a hybrid model where Governors commit ALGO for 3-month periods to participate in voting. The xGov program adds an expert layer for grant allocation decisions, combining on-chain voting with off-chain proposal discussions on GitHub.
  • Off-chain governance:
    • Bitcoin and Ethereum (pre-Merge) rely on community consensus and developer discussions, prioritizing stability over speed of innovation.
    • Off-chain processes often include forum discussions, proposal drafting, and community feedback before formal voting occurs.
  • Key considerations:
    • Token concentration can affect voting integrity
    • Participation incentives are crucial for engagement
    • Delegation systems can improve participation but may lead to vote centralization
    • Transparency in both on-chain and off-chain processes is essential

17. Cryptographic Algorithms

What cryptographic algorithms are used for hashing (SHA-256, Keccak-256) and for digital signatures (ECDSA, Ed25519)?

• Determines security and compatibility with existing cryptographic libraries.
• Examples:

  Hashing Algorithms:

  • SHA-256: Used by Bitcoin, this hashing algorithm is known for its robustness and security but requires significant computational power, which contributes to the high energy consumption of Bitcoin's proof-of-work.
  • Keccak-256: Employed by Ethereum, it's a variation of SHA-3 and is slightly more efficient than SHA-256. Keccak-256 provides similar security but was chosen for its NIST standardization and to differentiate Ethereum's approach from Bitcoin.

  Digital Signature Algorithms:

  • ECDSA (Elliptic Curve Digital Signature Algorithm): Used in both Bitcoin and Ethereum, ECDSA offers strong security based on elliptic curve cryptography but can be slower in signature verification compared to other methods.
  • Ed25519: Used by blockchains like Solana and Algorand, Ed25519 provides faster verification times and is considered more secure against certain types of attacks, though it is less widely supported by legacy cryptographic libraries.

  Trade-Offs:

  • Security vs. Speed: Algorithms like SHA-256 and ECDSA offer time-tested security but are slower and computationally intensive. In contrast, Keccak-256 and Ed25519 provide faster operations and better scalability but are newer and might face less adoption or compatibility with older systems.

  Several blockchains use different cryptographic algorithms to meet their specific needs. Blake2b is used in Zcash and Filecoin for fast, secure hashing, with Zcash employing it for its privacy-focused zk-SNARKs. Monero uses Curve25519 for ring signatures, enhancing transaction privacy, while Dash leverages X11, a chained algorithm of 11 cryptographic functions, for mining security and energy efficiency. Chia opts for Argon2, a password hashing algorithm resistant to GPU attacks, aligning with its eco-friendly proof-of-space-and-time model. Each algorithm reflects trade-offs between security, efficiency, and the specific goals of the blockchain.

  Choosing the right cryptographic algorithm depends on the network's priorities regarding speed, security, and compatibility with existing cryptographic infrastructure.

18. Privacy Features

Does the blockchain support privacy features (e.g., zk-SNARKs, zk-Rollups, RingCT) for transactions?

• Privacy is a key consideration for certain use cases, especially in finance and identity management.

❓

If you want to know more about privacy features in a more technical way, cryptographic algorithms, the cryptography behind certain protocols, their trade-offs and what not, reach out to @Mario Yaksetig, he is your man.

19. Native Token Economics

What is the native token used for, and what is the tokenomics model (e.g., inflationary, deflationary, fixed supply)?

• Determines incentives for validators, miners, and developers, and impacts overall ecosystem growth.
• Examples:

  • It's famously known that Bitcoin has a fixed supply of 21M coins, with mining a block giving less rewards (what is known as a reward halving) the closer the total supply is to being reached. The miner of a block also receives all the transaction fees for transactions included in the block.

  • Ethereum also had block rewards when it was PoW but no fixed supply. After the move to PoS, rewards are given to stakers, but part of transaction fees are burned. This means that at times of low usage, Ethereum is inflationary, but can quickly become deflationary if there is a lot of activity on the network.

  • Avalanche has a fixed supply of 720M coins, with new coins being given as staking rewards to validators and their delegators. Transaction fees are burned, which means that there is a deflationary component that counteracts the inflationary rewards. However, since there is a fixed supply, this means that the more transactions are processed, the lower the total final amount of coins will be: currently almost 4.5M AVAX have already been burned.

  • Polkadot has fixed inflation set in yearly percentage. The same amount of coins gets minted daily, with 100% going to stakers if the total amount of coins staked is equal to a given ideal percentage which is set by Governance. If there are less or more coins staked than the ideal value, the difference in rewards is instead sent to the onchain Treasury. Funds from the Treasury can be accessed by onchain Governance and are used to fund projects in the ecosystem. Part of transaction fees is also sent to the Treasury, and 1% of the its funds are burned every 28 days, creating deflationary pressure on the supply.

• It's important to note that a blockchain's inflation rate doesn't always directly translate to staking yields. While inflation represents new token issuance, actual staking yields can be significantly different due to factors like:
  • The percentage of total supply being staked (participation rate)
  • Additional rewards from transaction fees
  • Validator commission rates
  • Slashing events or penalties
  You can check some staking yields across different Proof of Stake networks here: Staking Rewards.

20. Developer Tooling and Ecosystem

What development tools and libraries are available (e.g., Truffle, Hardhat for EVM; Anchor for Solana), and how robust is the ecosystem for third-party tools and integrations?

• Critical for developer onboarding, debugging, and building dApps.
• Examples:
  • The availability of developer tools and libraries is crucial for building and maintaining a thriving blockchain ecosystem. For EVM-compatible chains like Ethereum, tools such as Truffle, Hardhat and Foundry streamline smart contract development, testing, and deployment, while integrations like OpenZeppelin provide secure contract templates. Solana offers Anchor, a powerful framework for Rust-based development, and a growing set of libraries to simplify building on its high-performance chain. Chains like Polkadot and Cosmos leverage modular SDKs for custom blockchain development, while newer entrants like Aptos and Sui focus on Move-based frameworks for safety and scalability. The robustness of these ecosystems, including third-party integrations and debugging tools, directly impacts developer onboarding and the speed of dApp innovation.
  • Developer activity is another key indicator of ecosystem strength. According to the latest data from Developer Report, Ethereum continues to dominate in terms of active developers, followed by growing ecosystems like Solana, Polkadot, and Cosmos. The robustness of tools, third-party integrations, and active developer communities directly impacts onboarding, innovation, and the overall growth of dApps in these ecosystems.

21. Virtual Machine Efficiency

How efficient is the virtual machine in terms of gas/fee consumption and execution speed for smart contracts? Are there optimizations like Just-in-Time (JIT) compilation or others?

• Important for performance optimization when deploying resource-heavy smart contracts.

22. Randomness Generation

How is randomness handled in the blockchain? Is there a native Verifiable Random Function (VRF) or another decentralized method for generating secure randomness (e.g., Chainlink VRF)?

• Key for applications like lotteries, gaming, and secure protocol operations that rely on randomness.

23. Block Propagation Mechanism

What mechanism is used for block propagation? Does it use gossip protocols, or any optimizations like Compact Blocks (as seen in Bitcoin)?

• Impacts the network's speed and efficiency in transmitting new blocks to all nodes.

24. Oracles and Off-Chain Data

Does the blockchain natively support oracles, or is it dependent on third-party services (e.g., Chainlink, Band Protocol) for off-chain data integration?

• Essential for applications that require external data, such as DeFi protocols or dApps needing real-world information.

25. Layer 1 or Layer 2 Focus

Is the blockchain primarily designed as a Layer 1 solution (e.g., Ethereum, Bitcoin) or does it focus on Layer 2 solutions (e.g., Optimism, Arbitrum)? If Layer 2, how is security inherited from the Layer 1 chain?

• Important for understanding the blockchain's positioning in the ecosystem, scalability approach, and security guarantees.

26. State Trie Structure and Optimization

What data structure is used for storing the state (e.g., Merkle Patricia Trie in Ethereum)? How is state compression, pruning, or optimization handled to prevent state bloat?

• Understanding the state trie or DAG (Directed Acyclic Graph) structure gives insight into how efficiently the blockchain handles state growth over time.

27. Transaction Mempool Handling and Prioritization

How is the transaction mempool managed? What strategies are used for transaction prioritization, fee markets, and DoS attack prevention in the mempool?

• This addresses network efficiency and protection against spam attacks, focusing on the management of unconfirmed transactions.

28. BFT Consensus Optimizations

If the blockchain uses a Byzantine Fault Tolerant (BFT) consensus algorithm (e.g., Tendermint, HotStuff), what optimizations are made to reduce latency, improve validator throughput, or reduce communication complexity?

• Understanding the nuances of the BFT implementation gives insight into the security, performance, and fault tolerance of the network.

29. Gas Cost Determination for Smart Contracts

How are gas costs determined for different opcodes or contract functions, and what strategies are available to optimize gas usage during smart contract execution?

• Deep dives into opcode-level analysis, such as gas-guzzling operations like storage writes, help developers write more efficient smart contracts and improve blockchain throughput.

30. Cryptographic Upgradability

What level of cryptographic agility is built into the protocol? Can cryptographic algorithms (e.g., signature schemes, hashing algorithms) be upgraded over time, especially in response to advancements in quantum computing?

• A blockchain's ability to adapt to new cryptographic standards (e.g., post-quantum algorithms) ensures long-term security and resilience.

31. Inflationary vs Deflationary Model

Is the native token inflationary (e.g., continuous minting for rewards) or deflationary (e.g., token burns, capped supply), and how does this affect long-term token value and supply?

• Understanding the token's issuance model helps evaluate its future scarcity and value proposition for holders.

32. Token Distribution and Vesting

What is the initial token distribution (e.g., allocation for founders, developers, community) and are there vesting schedules to prevent early dumping or centralization of ownership?

• Token allocation transparency is critical for ensuring decentralization and fair participation in the ecosystem.

33. Reward Mechanism for Validators

How are rewards calculated for validators, and is there a slashing mechanism for misbehavior or inactivity? Are rewards based purely on staking amount or is there a performance/uptime consideration?

• This question digs into the economic incentives for securing the network and penalizing bad actors.

34. Staking Yield and Inflation Impact

What is the staking yield for participants, and how does inflation of new tokens affect the real yield over time? Is the inflation rate fixed or does it adjust dynamically based on network activity?

• Helps to understand how sustainable and attractive staking is over time in relation to inflationary pressure.

35. Token Utility Beyond Staking

Does the native token have utility beyond staking and governance (e.g., paying transaction fees, accessing dApps, collateral for loans)? How critical is the token for using the ecosystem?

• Evaluates how embedded the token is within the network's economy and whether it has a genuine use case beyond speculation.

36. On-Chain or Off-Chain Governance

Is the governance mechanism on-chain (e.g., proposals and votes on the blockchain) or off-chain (e.g., coordinated via forums or off-chain tools like Snapshot)?

• This is fundamental for understanding how transparent and decentralized decision-making processes are.

37. Governance Participation Thresholds

What are the minimum thresholds (e.g., token holdings or staked tokens) to propose a governance vote, and what voting weight mechanisms are used (1 token = 1 vote, quadratic voting)?

• Helps determine whether governance is accessible to a broad community or controlled by large holders.

38. Governance Proposal Lifecycle

How does the lifecycle of a governance proposal work? What are the stages from proposal to vote to implementation, and how long does each stage take?

• Critical for evaluating how responsive the governance system is to community needs and protocol upgrades.

39. Governance Voting Power

Is voting power based solely on token holdings, or are there mechanisms to prevent centralization of governance power (e.g., time-weighted voting, reputation systems)?

• Ensures that governance power isn't disproportionately skewed toward large holders or whales.

40. Veto and Emergency Powers

Are there any veto or emergency powers built into the governance system (e.g., core developers or councils)? How are they activated and what are the checks on these powers?

• Important for understanding the balance between decentralization and the ability to respond to critical situations.

41. Validator Selection Criteria

How are validators selected in the consensus mechanism? Is it purely based on the amount of staked tokens, or are other factors (e.g., uptime, geographic distribution, hardware capacity) considered?

• This sheds light on whether validator selection encourages decentralization and performance or simply favors large stakeholders.

42. Validator Slashing Conditions

What are the conditions under which validators are slashed (e.g., double-signing, downtime, malicious activity), and how are slashing penalties enforced?

• Critical for understanding the security and reliability of the network by penalizing misbehaving or negligent validators.

43. Validator Decentralization Metrics

How decentralized is the validator set? Are there any mechanisms to prevent centralization of validators (e.g., minimum staking caps, delegation incentives)?

• Ensures that the network is not dominated by a few large validators, which could impact security and governance.

44. Validator Performance Metrics

Are validators rewarded based purely on staking amount, or are there performance metrics like uptime, latency, or transaction validation efficiency that influence rewards?

• Encourages validators to maintain high performance and reliability, which directly impacts the network's overall health.

45. Delegation Mechanisms for Staking

Is there a delegation mechanism that allows token holders to delegate their stake to validators? If so, how are delegator rewards and validator fees structured?

• Helps assess how passive participants can engage in staking and what incentives exist for delegators and validators.

46. Token Sale Structure (ICO, IDO, Private Sale)

What token sale method was used (ICO, IDO, private sale, or a combination), and how were funds raised? Was the sale open to the public, or were there early rounds for private investors?

• This helps assess the transparency of the fundraising process, how early investors were incentivized, and the level of public access.

47. Token Lock-up and Vesting for Team and Investors

Are there token lock-up periods or vesting schedules for the founding team and early investors? How are these structured to prevent market dumping and ensure long-term commitment?

• Understanding vesting schedules is crucial for evaluating token supply dynamics and long-term team/investor alignment with the project.

48. Project Roadmap and Milestones

What is the detailed roadmap for the project? Are there clear technical milestones, and how has the team performed against past roadmap promises?

• A well-defined roadmap with technical milestones shows the project's vision and the team's ability to execute on promises.

49. Use of Raised Funds

How are the funds raised during the token sale allocated (e.g., development, marketing, partnerships, liquidity provision)? Is there transparency in how funds are being used post-launch?

• Proper allocation of funds impacts the project's growth and long-term sustainability. Transparency is key to building community trust.

50. Team Background and Development Capabilities

What is the background of the founding team and developers? Have they successfully launched projects before, and do they have the technical expertise required to execute the roadmap?

• A strong, experienced team is a critical indicator of the project's ability to deliver on its promises and handle challenges during development.