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 "arja automated repair of java programs via multi objective genetic programming"):
  Abstract: Recent empirical studies show that the performance of GenProg is not satisfactory, particularly for Java. In this paper, we propose ARJA, a new GP based repair approach for automated repair of Java programs. To be specific, we present a novel lower-granularity patch representation that properly decouples the search subspaces of likely-buggy locations, operation types and potential fix ingredients, enabling GP to explore the search space more effectively. Based on this new representation, we formulate automated program repair as a multi-objective search problem and use NSGA-II to look for simpler repairs. To reduce the computational effort and search space, we introduce a test filtering procedure that can speed up the fitness evaluation of GP and three types of rules that can be applied to avoid unnecessary manipulations of the code. Moreover, we also propose a type matching strategy that can create new potential fix ingredients by exploiting the syntactic patterns of the existing statements. We conduct a large-scale empirical evaluation of ARJA along with its variants on both seeded bugs and real-world bugs in comparison with several state-of-the-art repair approaches. Our results verify the effectiveness and efficiency of the search mechanisms employed in ARJA and also show its superiority over the other approaches. In particular, compared to jGenProg (an implementation of GenProg for Java), an ARJA version fully following the redundancy assumption can generate a test-suite adequate patch for more than twice the number of bugs (from 27 to 59), and a correct patch for nearly four times of the number (from 5 to 18), on 224 real-world bugs considered in Defects4J. Furthermore, ARJA is able to correctly fix several real multi-location bugs that are hard to be repaired by most of the existing repair approaches.

Includes members:
  Member "automatic software repair a bibliography":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a recurrent neural network based patch recommender for linux kernel bugs")
  Member "automatic repair of real bugs in java a large scale experiment on the defects4j dataset":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "e apr mapping the effectiveness of automated program repair")
  Member "an empirical analysis of the influence of fault space on search based automated program repair":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "tbar revisiting template based automated program repair")
  Member "nopol automatic repair of conditional statement bugs in java programs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "e apr mapping the effectiveness of automated program repair")
  Member "test case generation for program repair a study of feasibility and effectiveness":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "ifixr bug report driven program repair")
  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")
  Member "an analysis of the search spaces for generate and validate patch generation systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "encore ensemble learning using convolution neural machine translation for automatic program repair")
  Member "mining software repair models for reasoning on the search space of automated program fixing":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "e apr mapping the effectiveness of automated 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)