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- To review existing examples and approaches of automated programming for smart contracts of other platforms (i.e., Solidity).
- To explore the technically feasible options of automated chaincode programming for Hyperledger Fabric (incl. chatGPTChatGPT) and select one for further work.
- To formulate a chaincode specification style which “seems to work well enough” on a set of representative examples with automated programming.
(We don’t know yet what will work – ; One-shot /or iterative? Requirement set or Behavior-Driven Development (BDD)? Conversational or formal specification? EtcAnd so on.) - To create support for translating the specification partially or fully to runtime verification code, which can wrap the chaincode implementation. (Starting
On the last point: starting from a specification is a tried and tested way to create verifier code either manually or automatically and is much easier to do correctly than creating the implementation correctly from a specification. We plan to keep this
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last point “classic”: i.e., no
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ChatGPT here. Specification-based verification criteria are usually
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amenable to development time verification, too (with static analysis, model checking, etc.).
Additional Information
Ask ChatGPT for papers, which deal with using neural networks for generating Solidity code! No, really.
And ask it to write you an ERC-20 equivalent chaincode.
And ask it to introduce Fabric MSP-based ownership management.
(Try not to think of Asimov's robopsychology.)
It's not a coding wizard yet, but definitely uncanny.
On the other handFurthermore, we expect to experiment with Behavior-Driven Development; this means Gherkin/Cucumber.
Technology/approach for runtime verification (https://en.wikipedia.org/wiki/Runtime_verification) will depend heavily on the results on the "constructive" side - we do not want to make a commitment on this at this point.
Learning Objectives
- Hyperledger Fabric chaincode programming (if that's not already in the candidate's toolbox)
- Experiment planning and evaluation
- Working under guidance and collaborating using open-source tools
- Analytic thinking - and also thinking a bit out of outside the box
Expected Outcome
- A representative ("towards a benchmark") set of smart contract functionality and their key variations, defined in natural language (various token contracts, cross-organizational processes, data recording, etc.).
- A set of (possibly branching) natural language conversation scripts, and a report on evaluating the capabilities and shortcomings of a selected (expected to be best-of-breed) generative approach.
- A set of functionally equivalent specifications in a structured approach (we expect this to be a variant of BDD, but there are other options to try).
- A report on evaluating the capabilities and shortcomings of the structured approach on the selected (expected to be best-of-breed) generative approach, and comparison with the "conversational" approach.
- At least expected: specification-compliance runtime checking code for the cases of the structured approach (determining the checked properties and a coverage goal is part of the work).
- In optimal caseOptimally: automatically generated checker code.
Relation to Hyperledger
Hyperledger Fabric.
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Mentor(s) Names and Contact Info
Bertalan Zoltán Péter, PhD student, bpeter@edu.bme.hu, PhD student, Budapest University of Technology and Economics, Dept. of Measurement and Inf. Systems, Critical Systems Research Group
Imre Kocsis, assistant professor, kocsis.imre@vik.bme.hu, assistant professor, Budapest University of Technology and Economics, Dept. of Measurement and Inf. Systems, Critical Systems Research Group
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