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 "the remarkable role of similarity in redundancy based program repair"):
  Abstract: Recently, there have been original attempts to use the concept of "code similarity" in program repair, suggesting that similarity analysis has an important role in the repair process. However, there is no dedicated work to characterize and quantify the role of similarity in redundancy-based program repair, where the patch is composed from source code taken from somewhere else. This is where our paper makes a major contribution: we perform a deep and systematic analysis of the role of code similarity during the exploration of the repair search space. We define and set up a large-scale experiment based on four code similarity metrics that capture different similarities: character, token, semantic and structure similarity. Overall, we have computed 56 million similarity score over 15 million source code components. We show that with similarity analysis, at least 90% of search space can be ignored to find the correct patch. Code similarity is capable of ranking the correct repair ingredient first in 4 - 33 % of the considered cases.

Includes members:
  Member "astor exploring the design space of generate and validate program repair beyond genprog":
    also connected through other hyperedges:
      (none)
  Member "revisiting ssfix for better program repair":
    also connected through other hyperedges:
      (none)
  Member "sorting and transforming program repair ingredients via deep learning code similarities":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "checking smart contracts with structural code embedding")
  Member "the codrep machine learning on source code competition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sequencer sequence to sequence learning for end to end program repair")
  Member "code2seq generating sequences from structured representations of code":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "big code big vocabulary open vocabulary models for source code")
  Member "neural network based graph embedding for cross platform binary code similarity detection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "equivalence of dataflow graphs via rewrite rules using a graph to sequence neural model")
  Member "learning to represent programs with graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "adversarial robustness for code")
  Member "precise condition synthesis for program repair":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "encore ensemble learning using convolution neural machine translation for automatic program repair")

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)