storm

@notnotstorm

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1) @samcm's xatu project is building public datasets of this for ethereum 2) @toniw.eth's https://reorg.pics/ visualizes some reorg metrics 3) etherscan shows this for some chains. not sure if complete. (e.g. https://polygonscan.com/blocks_forked) Ive never seen great data for non-eth chains. lmk if you find any

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and if on chain data interests you, check out our tools reth and cryo - reth https://github.com/paradigmxyz/reth - cryo https://github.com/paradigmxyz/cryo this tool combo uniquely enabled the analysis in this thread. it’s the only way to state diff all of base in a reasonable amount of time

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thanks for reading my broad mission the past couple months has been to use ultra high resolution data to help scale Ethereum more scaling data deep dives incoming

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sooner or later every chain will need to confront these storage spam issues I’ve been modeling some potential fixes but it’s still a WIP if you have ideas for how to improve storage spam or pricing hmu here or DM’s. I might be able to model it out

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why is pricing storage difficult? most of the operations within a transaction are easy to price because they happen instantaneously but storage is different…once you pay for storage, that data gets stored by the network *forever*. so it's like pricing a lifetime subscription

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what can be done? simply put, storage needs to be repriced to reflect the true burden that it imposes on the network there are many ways to do this, each with varying levels of impact to normal users but pricing storage is fundamentally difficult

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is XEN unique? XEN is just one example of a broader pattern when cheap computational resources are combined with speculation, those resources will be used in unintended ways blobscriptions, gas tokens, and Solana’s ORE can all be lumped in this category

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is this specific to Base? not at all. XEN has left a large mark on every major EVM chain for example, XEN is now the largest contract on Ethereum. it has been responsible for 8.8% of all Ethereum state growth over the past year and it now takes up 3.5% of all state

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is the problem fixed? so far there have been no mitigations enacted to prevent future abuse there’s nothing preventing one or ten new XEN-like protocols from emerging to fill the state with spam. especially as fees continue to fall

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how bad is this? in absolute terms the problem is still small. Base contract storage is only 53.4 GiB in size (compared to 245 GiB on Ethereum) the problem has also become less severe over time. XEN state share peaked at around 85% back in october

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how does this affect blockchain scaling? scaling blockchains to become 100x or 1000x larger will require efficient use of computational resources it is not viable for the majority of a network’s resources to be consumed so inefficiently

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what is the problem? 1) thanks to XEN, 0.3% of Base users are monopolizing 67.8% of the chain's resources 2) state is permanent. Base nodes now need to store + propagate this spam XEN data forever 3) storage abuse can continue until gas pricing is redesigned

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the chart above visualizes how Base’s state is currently being used. size of each rectangle = how much state is used by each type of contract the chart was generated using the same methodology as our recent blogpost looking at Ethereum. find it here: https://www.paradigm.xyz/2024/03/how-to-raise-the-gas-limit-1

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~70% of Base chain state has been taken over by a single protocol of questionable utility thanks to cheap fees + storage mispricing, a tiny number of users have monopolized the majority of network resources this has implications for every cheap fee blockchain. some thoughts 👇

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does anyone know of some good address label datasets for very old ethereum contracts? (pre-2018)

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Well… at least I’m not the *worst* offender First metamorphic contracts, now state bloat… surprised core devs haven’t put out a hit on me yet Thanks for pulling this data together @notnotstorm!

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top 20 deployers by amount of deployed contract state safe to assume some of those are you? 😎😎

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we received a ton of helpful feedback while writing this post major thank you to @tim @karalabe.eth Guillaume Ballet @banteg @ralexstokes @jessepollak @toniw.eth @patrickogrady @lightclient @ansgar.eth @frankieislost @danrobinson @matthuang Doug Feagin

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we have significantly more data to share in the coming weeks if you are excited about research in Ethereum scaling, reach out to me or georgios. we’d love to hear about how you are thinking about the problem and potentially collaborate

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however, state growth is NOT the only bottleneck that limits scaling Ethereum each bottleneck must be analyzed according to its own particular hardware constraints we intend to do just that in future work

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