human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "smart contract repair"):
  Abstract: Smart contracts are automated or self-enforcing contracts that can be used to exchange money, property, or anything of value without having to place trust in third parties. Many commercial transactions presently make use of smart contracts due to their potential benefits in enabling parties to engage in secure peer-to-peer transactions independent of external parties. They do so by transferring trust to computer programs (smart contracts), raising the question of whether these programs can be fully trusted. However, the code can be complex and may behave in many different unexpected or malicious ways due to poorly written or vulnerable smart contracts. Furthermore, in the case of smart contracts on the blockchain, they are typically open to (malicious) agents which can interact with it in various ways. Experience shows that many commonly used smart contracts are vulnerable to serious malicious attacks which may enable attackers to steal valuable assets of involved parties. There is therefore a need to apply analysis techniques to detect and repair bugs in smart contracts before being deployed. In this work, we present the first automated smart contracts repair approach that is gas-optimized and vulnerability-agnostic. Our repair method is search-based and considers the gas usage of the candidate patches via leveraging our novel notation of \emph{gas dominance relationship}. Our approach can be used to optimise the overall security and reliability of smart contracts against malicious attackers.

Includes members:
  Member "slither a static analysis framework for smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "smart contract development from the perspective of developers topics and issues discussed on social media")
  Member "mutation testing for ethereum smart contract":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mutation testing of smart contracts at scale")
  Member "online detection of effectively callback free objects with applications to smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "smacs smart contract access control service")
  Member "contractfuzzer fuzzing smart contracts for vulnerability detection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "smart contract development from the perspective of developers topics and issues discussed on social media")
  Member "a semantic framework for the security analysis of ethereum smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "ae gis shielding vulnerable smart contracts against attacks")
  Member "automatic software repair a bibliography":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a recurrent neural network based patch recommender for linux kernel bugs")
  Member "on the specification and verification of atomic swap smart contracts":
    also connected through other hyperedges:
      (none)
  Member "securify practical security analysis of smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an overview on smart contracts challenges advances and platforms")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SE(Software Engineering)