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: "active inductive logic programming for code search"
  Abstract: Modern search techniques either cannot efficiently incorporate human feedback to refine search results or to express structural or semantic properties of desired code. The key insight of our interactive code search technique ALICE is that user feedback could be actively incorporated to allow users to easily express and refine search queries. We design a query language to model the structure and semantics of code as logic facts. Given a code example with user annotations, ALICE automatically extracts a logic query from features that are tagged as important. Users can refine the search query by labeling one or more examples as desired (positive) or irrelevant (negative). ALICE then infers a new logic query that separates the positives from negative examples via active inductive logic programming. Our comprehensive and systematic simulation experiment shows that ALICE removes a large number of false positives quickly by actively incorporating user feedback. Its search algorithm is also robust to noise and user labeling mistakes. Our choice of leveraging both positive and negative examples and the nested containment structure of selected code is effective in refining search queries. Compared with an existing technique, Critics, ALICE does not require a user to manually construct a search pattern and yet achieves comparable precision and recall with fewer search iterations on average. A case study with users shows that ALICE is easy to use and helps express complex code patterns.

Connected through hyperedge HE-1 (induced by source paper "trans 3 a transformer based framework for unifying code summarization and code search"):
  with members:
    - "coacor code annotation for code retrieval with reinforcement learning"
    - "ernie enhanced representation through knowledge integration"
    - "a neural model for generating natural language summaries of program subroutines"
    - "characterizing and detecting cuda program bugs"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "aroma code recommendation via structural code search"
    - "deepbillboard systematic physical world testing of autonomous driving systems"
    - "deep reinforcement learning for sequence to sequence models"

Connected through hyperedge HE-2 (induced by source paper "code clone matching a practical and effective approach to find code snippets"):
  with members:
    - "sourcerercc scaling code clone detection to big code"

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)