human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "mining software repair models for reasoning on the search space of automated program fixing"
  Abstract: This paper is about understanding the nature of bug fixing by analyzing thousands of bug fix transactions of software repositories. It then places this learned knowledge in the context of automated program repair. We give extensive empirical results on the nature of human bug fixes at a large scale and a fine granularity with abstract syntax tree differencing. We set up mathematical reasoning on the search space of automated repair and the time to navigate through it. By applying our method on 14 repositories of Java software and 89,993 versioning transactions, we show that not all probabilistic repair models are equivalent.

Connected through hyperedge HE-1 (induced by source paper "e apr mapping the effectiveness of automated program repair"):
  with members:
    - "learning the relation between code features and code transforms with structured prediction"
    - "how different is it between machine generated and developer provided patches an empirical study on the correct patches generated by automated program repair techniques"
    - "bears an extensible java bug benchmark for automatic program repair studies"
    - "alleviating patch overfitting with automatic test generation a study of feasibility and effectiveness for the nopol repair system"
    - "empirical review of java program repair tools a large scale experiment on 2 141 bugs and 23 551 repair attempts"
    - "automatic repair of real bugs in java a large scale experiment on the defects4j dataset"
    - "ultra large repair search space with automatically mined templates the cardumen mode of astor"
    - "arja automated repair of java programs via multi objective genetic programming"

Connected through hyperedge HE-2 (induced by source paper "tbar revisiting template based automated program repair"):
  with members:
    - "bears an extensible java bug benchmark for automatic program repair studies"
    - "sorting and transforming program repair ingredients via deep learning code similarities"
    - "avatar fixing semantic bugs with fix patterns of static analysis violations"
    - "on reliability of patch correctness assessment"
    - "fixminer mining relevant fix patterns for automated program repair"
    - "automatic software repair a bibliography"
    - "ultra large repair search space with automatically mined templates the cardumen mode of astor"
    - "you cannot fix what you cannot find an investigation of fault localization bias in benchmarking automated program repair systems"

Connected through hyperedge HE-3 (induced by source paper "sorting and transforming program repair ingredients via deep learning code similarities"):
  with members:
    - "on learning meaningful code changes via neural machine translation"
    - "automatic software repair a bibliography"
    - "automatic repair of real bugs in java a large scale experiment on the defects4j dataset"
    - "nopol automatic repair of conditional statement bugs in java programs"
    - "automated correction for syntax errors in programming assignments using recurrent neural networks"
    - "sk_p a neural program corrector for moocs"
    - "learning api usages from bytecode a statistical approach"
    - "on the naturalness of buggy code"

Connected through hyperedge HE-4 (induced by source paper "astor exploring the design space of generate and validate program repair beyond genprog"):
  with members:
    - "a comprehensive study of automatic program repair on the quixbugs benchmark"
    - "alleviating patch overfitting with automatic test generation a study of feasibility and effectiveness for the nopol repair system"
    - "automatic repair of real bugs in java a large scale experiment on the defects4j dataset"
    - "ultra large repair search space with automatically mined templates the cardumen mode of astor"
    - "arja automated repair of java programs via multi objective genetic programming"
    - "an empirical analysis of the influence of fault space on search based automated program repair"
    - "identifying patch correctness in test based program repair"
    - "nopol automatic repair of conditional statement bugs in java programs"

Connected through hyperedge HE-5 (induced by source paper "smart contract repair"):
  with members:
    - "slither a static analysis framework for smart contracts"
    - "mutation testing for ethereum smart contract"
    - "online detection of effectively callback free objects with applications to smart contracts"
    - "contractfuzzer fuzzing smart contracts for vulnerability detection"
    - "a semantic framework for the security analysis of ethereum smart contracts"
    - "automatic software repair a bibliography"
    - "on the specification and verification of atomic swap smart contracts"
    - "securify practical security analysis of smart contracts"

Connected through hyperedge HE-6 (induced by source paper "using sequence to sequence learning for repairing c vulnerabilities"):
  with members:
    - "maybe deep neural networks are the best choice for modeling source code"
    - "sentencepiece a simple and language independent subword tokenizer and detokenizer for neural text processing"
    - "learning to repair software vulnerabilities with generative adversarial networks"
    - "attention is all you need"
    - "opennmt open source toolkit for neural machine translation"
    - "neural machine translation of rare words with subword units"
    - "on the properties of neural machine translation encoder decoder approaches"
    - "sequence to sequence learning with neural networks"

Connected through hyperedge HE-7 (induced by source paper "getafix learning to fix bugs automatically"):
  with members:
    - "learning to represent edits"
    - "deepbugs a learning approach to name based bug detection"
    - "coming a tool for mining change pattern instances from git commits"
    - "learning quick fixes from code repositories"
    - "semantic code repair using neuro symbolic transformation networks"
    - "a survey of machine learning for big code and naturalness"
    - "learning syntactic program transformations from examples"
    - "npefix automatic runtime repair of null pointer exceptions in java"

Connected through hyperedge HE-8 (induced by source paper "analyzing the context of bug fixing changes in the openstack cloud computing platform"):
  with members:
    - "learning how to mutate source code from bug fixes"
    - "fixminer mining relevant fix patterns for automated program repair"
    - "refdiff detecting refactorings in version histories"
    - "automatically extracting instances of code change patterns with ast analysis"

Question: Please tell me which class the center node 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)