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 "tbar revisiting template based automated program repair"):
  Abstract: We revisit the performance of template-based APR to build comprehensive knowledge about the effectiveness of fix patterns, and to highlight the importance of complementary steps such as fault localization or donor code retrieval. To that end, we first investigate the literature to collect, summarize and label recurrently-used fix patterns. Based on the investigation, we build TBar, a straightforward APR tool that systematically attempts to apply these fix patterns to program bugs. We thoroughly evaluate TBar on the Defects4J benchmark. In particular, we assess the actual qualitative and quantitative diversity of fix patterns, as well as their effectiveness in yielding plausible or correct patches. Eventually, we find that, assuming a perfect fault localization, TBar correctly/plausibly fixes 74/101 bugs. Replicating a standard and practical pipeline of APR assessment, we demonstrate that TBar correctly fixes 43 bugs from Defects4J, an unprecedented performance in the literature (including all approaches, i.e., template-based, stochastic mutation-based or synthesis-based APR).

Includes members:
  Member "bears an extensible java bug benchmark for automatic program repair studies":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "e apr mapping the effectiveness of automated program repair")
  Member "sorting and transforming program repair ingredients via deep learning code similarities":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "checking smart contracts with structural code embedding")
  Member "avatar fixing semantic bugs with fix patterns of static analysis violations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ifixr bug report driven program repair")
  Member "on reliability of patch correctness assessment":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ifixr bug report driven program repair")
  Member "fixminer mining relevant fix patterns for automated program repair":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "encore ensemble learning using convolution neural machine translation for automatic program repair")
  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 "ultra large repair search space with automatically mined templates the cardumen mode of astor":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "e apr mapping the effectiveness of automated program repair")
  Member "you cannot fix what you cannot find an investigation of fault localization bias in benchmarking automated program repair systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "explaining deep neural networks using spectrum based fault localization")

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)