@inproceedings{10.1145/3460537.3460565,
  author    = {Bodorik, Peter and G. Liu, Christian and Julta, Dawn},
  title     = {Using FSMs to Find Patterns for Off-Chain Computing: Finding Patterns for Off-Chain Computing with FSMs},
  year      = {2021},
  isbn      = {9781450389624},
  address   = {New York, NY, USA},
  url       = {https://doi.org/10.1145/3460537.3460565},
  doi       = {10.1145/3460537.3460565},
  abstract  = {One of the problems arising in using blockchains is their size-constraints regarding performance. This paper proposes a new algorithm for blockchain software developers and architects to use for determining what computations of a smart contract can be effectively done off-chain without loss of trust. Our algorithm uses FSMs or HSMs in order to create smart contract patterns using graphs and then uses pattern recognition to identify which parts of the smart contracts should be considered for moving off-chain. The pattern recognition property used is that once software execution transits into the pattern's entry state, off-chain execution continues until the execution transits into the pattern's exit state, when execution continues on-chain. The software developer reviews each pattern together with information, such as anticipated overhead cost due to off-chain execution, and she is provided with guidance on decision making whether to execute the smart contract pattern under consideration off-chain. Expert software developer inspection, in the context of a Trade Finance use case, validates that our algorithm finds optimal patterns for moving computations off-chain and improve blockchain software performance.},
  booktitle = {2021 The 3rd ACM International Conference on Blockchain Technology},
  pages     = {28–34},
  numpages  = {7},
  keywords  = {FSM and HSM modeling, Blockchain developer productivity, Smart contract, Off-chain computation, Blockchain},
  location  = {Shanghai, China},
  series    = {ICBCT '21}
}

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