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Impact Analysis of Neutering SELFDESTRUCT - Dev Update #3

This is the third update for my CDAP Project, which is about analyzing the existing uses of the SELFDESTRUCT opcode in Ethereum.

Progress since last update

Based on my analysis of the usage of SELFDESTRUCT, which revealed that neutering SELFDESTRUCT could damage certain DeFi users, I am leaning towards trying to preserve the functionality of SELFDESTRUCT when switching the Ethereum State to Verkle Tries. To that end, I have modified the current Verkle tree proposal to support SELFDESTRUCT. My version is hosted here.

My version attempts to be the simplest possible modification that supports SELFDESTRUCT. The gas usage by contracts that are only deployed once should be almost unchanged, except that an additional slot incarnation_number in the contract header needs to be accessed. Gas usage by contracts that have reincarnated at least once is a bit higher, since each contract call needs to access at least two branches.

In addition to implementing support for SELFDESTRUCT, I also simplified the original specification somewhat by performing the splitting of the least significant byte of each sub-tree index with the rest as part of the function get_tree_key. This allowed for removing multiple instances of // 256 and % 256 in the spec, and also shortened the syntax of the access events from the form (address, sub_key, leaf_key) to the form (address, sub_key).

What to do next

I'm a bit unsure where to go next from here on this project. It seems that the other details about Verkle Tries needs to be finalized and implemented before adding support for SELFDESTRUCT will be considered. In the mean time, I will try to learn more about what remains to be done about Verkle tries, and see if I can find something to work on in that area.

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Albus Dompeldorius CDAP - Dev Update #7

This is the seventh update for my work in the CDAP. What I have done since last update I have been working on Springrollup. First, I managed to implement two circuits. One for adding pending transactions, and one for processing pending transactions. Then I realized that the rollup could be simplified a lot; instead of having pending transactions, we could simply require that the operator sends witnesses to all senders in a rollup block, who then confirm their transactions, before the operator publishes the block. Only transactions whose senders have confirmed, are processed. With this new mechanism, there is no longer any need for maintaining pending transactions. Another challange I faced was that I learned that circuits are very strict about the sizes of their inputs. This means that for instance the number of transactions in a block must be hard-coded in the circuit. One solution to allow dynamically adjusted block sizes is to create several circuits for different sizes and allowing the operator to pick one circuit each time they want to publish a block. However, this challenge is even more difficult in our case, since not only is the number of transactions variable, but also the number of senders. One solution for this is to have two circuits that are processed after one another. The first circuit processes all balance updates, and the second circuit processes all senders (checks their signature, and checks that their account index is part of the calldata). The first circuit could compute a hash of all senders (along with the new state root), which is fed as an input to the second circuit. What I will do next

Nov 9, 2021
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Oct 26, 2021
Springrollup: A zk-rollup that allows a sender to batch an unlimited number of transfers with only 6 bytes of calldata per batch

(The newest version of this document can always be found on hackmd or GitHub) We introduce Springrollup: a Layer 2 solution which has the same security assumptions as existing zk-rollups, but uses much less on-chain data. In this rollup, a sender can batch an arbitrary number of transfers to other accounts while only having to post their address as calldata, which is 6 bytes if we want to support up to 2^48 ~ 300 trillion accounts. As a by-product we also achieve increased privacy, since less user data is posted on-chain. General framework We start by introducing the general framework that we will use to describe the rollup. The rollup state is divided in two parts: On-chain available state: State with on-chain data availability. All changes to this state must be provided as calldata by the operator.

Oct 20, 2021
Albus Dompeldorius CDAP - Dev Update #5

This is the fifth update for my work in the CDAP. What I have done since last update Since my last update, I have been working on my zk-rollup concept, which allows for greatly reduced calldata usage while still preserving the same security of zk-rollups. The document is now expanded with more details about deposits, withdrawals, calldata estimates and examples. Anyone familiar with how zk-rollups work should now hopefully be able to grasp the main idea in my proposal. The reason I haven't posted to ethresear.ch yet, is that I want to implement an optimization first. (see below) What I will do next I am currently working on an optimization which would allow even less calldata usage. The current proposal uses 8 bytes of calldata for a batch of up to 65536 transfers from the same sender, but with the extra optimization this will be reduced to 6 bytes for a batch of an unlimited amount of transfers from the same sender. Once this is done, I will post the proposal on ethresear.ch to get some feedback on the proposal. I will reach out to zk-people to try to collaborate on an implementation.

Oct 12, 2021
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