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: "test case purification for improving fault localization"
  Abstract: Finding and fixing bugs are time-consuming activities in software development. Spectrum-based fault localization aims to identify the faulty position in source code based on the execution trace of test cases. Failing test cases and their assertions form test oracles for the failing behavior of the system under analysis. In this paper, we propose a novel concept of spectrum driven test case purification for improving fault localization. The goal of test case purification is to separate existing test cases into small fractions (called purified test cases) and to enhance the test oracles to further localize faults. Combining with an original fault localization technique (e.g., Tarantula), test case purification results in better ranking the program statements. Our experiments on 1800 faults in six open-source Java programs show that test case purification can effectively improve existing fault localization techniques.

Connected through hyperedge HE-1 (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-2 (induced by source paper "can automated program repair refine fault localization"):
  with members:
    - "getafix learning to fix bugs automatically"
    - "an empirical study of fault localization families and their combinations"
    - "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 fixing of programs with contracts"

Connected through hyperedge HE-3 (induced by source paper "automatic test improvement with dspot a study with ten mature open source projects"):
  with members:
    - "a snowballing literature study on test amplification"
    - "dspot test amplification for automatic assessment of computational diversity"
    - "learning natural coding conventions"

Connected through hyperedge HE-4 (induced by source paper "a snowballing literature study on test amplification"):
  with members:
    - "nopol automatic repair of conditional statement bugs in java programs"

Connected through hyperedge HE-5 (induced by source paper "amortising the cost of mutation based fault localisation using statistical inference"):
  with members:
    - "test set diameter quantifying the diversity of sets of test cases"

Connected through hyperedge HE-6 (induced by source paper "avatar fixing semantic bugs with fix patterns of static analysis violations"):
  with members:
    - "fixminer mining relevant fix patterns for automated program repair"
    - "automatic repair of real bugs in java a large scale experiment on the defects4j dataset"
    - "you cannot fix what you cannot find an investigation of fault localization bias in benchmarking automated program repair systems"
    - "learning quick fixes from code repositories"
    - "dissection of a bug dataset anatomy of 395 patches from defects4j"
    - "nopol automatic repair of conditional statement bugs in java programs"
    - "impact of tool support in patch construction"
    - "mining fix patterns for findbugs violations"

Connected through hyperedge HE-7 (induced by source paper "you cannot fix what you cannot find an investigation of fault localization bias in benchmarking automated program repair systems"):
  with members:
    - "fixminer mining relevant fix patterns for automated program repair"
    - "automatic repair of real bugs in java a large scale experiment on the defects4j dataset"
    - "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"
    - "impact of tool support in patch construction"
    - "automated correction for syntax errors in programming assignments using recurrent neural networks"

Connected through hyperedge HE-8 (induced by source paper "automatic repair of real bugs in java a large scale experiment on the defects4j dataset"):
  with members:
    - "nopol automatic repair of conditional statement bugs in java programs"
    - "an analysis of the search spaces for generate and validate patch generation systems"
    - "mining software repair models for reasoning on the search space of automated program fixing"
    - "a critical review of automatic patch generation learned from human written patches essay on the problem statement and the evaluation of automatic software repair"
    - "do the fix ingredients already exist an empirical inquiry into the redundancy assumptions of program repair approaches"
    - "automatic repair of buggy if conditions and missing preconditions with smt"
    - "automated fixing of programs with contracts"

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)