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: "sygus comp 2016 results and analysis"
  Abstract: Syntax-Guided Synthesis (SyGuS) is the computational problem of finding an implementation f that meets both a semantic constraint given by a logical formula $\varphi$ in a background theory T, and a syntactic constraint given by a grammar G, which specifies the allowed set of candidate implementations. Such a synthesis problem can be formally defined in SyGuS-IF, a language that is built on top of SMT-LIB. #R##N#The Syntax-Guided Synthesis Competition (SyGuS-Comp) is an effort to facilitate, bring together and accelerate research and development of efficient solvers for SyGuS by providing a platform for evaluating different synthesis techniques on a comprehensive set of benchmarks. In this year's competition we added a new track devoted to programming by examples. This track consisted of two categories, one using the theory of bit-vectors and one using the theory of strings. This paper presents and analyses the results of SyGuS-Comp'16.

Connected through hyperedge HE-1 (induced by source paper "learning to infer program sketches"):
  with members:
    - "ain t nobody got time for coding structure aware program synthesis from natural language"
    - "neural guided deductive search for real time program synthesis from examples"
    - "automatic program synthesis of long programs with a learned garbage collector"
    - "neural program search solving programming tasks from description and examples"
    - "coarse to fine decoding for neural semantic parsing"
    - "leveraging grammar and reinforcement learning for neural program synthesis"
    - "neural guided constraint logic programming for program synthesis"
    - "robustfill neural program learning under noisy i o"

Connected through hyperedge HE-2 (induced by source paper "write execute assess program synthesis with a repl"):
  with members:
    - "learning to infer program sketches"
    - "learning to infer and execute 3d shape programs"
    - "neural guided deductive search for real time program synthesis from examples"
    - "automatic program synthesis of long programs with a learned garbage collector"
    - "synthesizing programs for images using reinforced adversarial learning"
    - "program synthesis through reinforcement learning guided tree search"
    - "selecting representative examples for program synthesis"
    - "robustfill neural program learning under noisy i o"

Connected through hyperedge HE-3 (induced by source paper "proving unrealizability for syntax guided synthesis"):
  with members:
    - "connecting program synthesis and reachability automatic program repair using test input generation"
    - "what s decidable about syntax guided synthesis"

Connected through hyperedge HE-4 (induced by source paper "program synthesis using abstraction refinement"):
  with members:
    - "robustfill neural program learning under noisy i o"
    - "synthesis of data completion scripts using finite tree automata"
    - "component based synthesis of table consolidation and transformation tasks from examples"
    - "program synthesis from polymorphic refinement types"
    - "using program synthesis for social recommendations"

Connected through hyperedge HE-5 (induced by source paper "sound and automated synthesis of digital stabilizing controllers for continuous plants"):
  with members:
    - "using program synthesis for program analysis"
    - "counter example guided synthesis of control lyapunov functions for switched systems"
    - "swati synthesizing wordlengths automatically using testing and induction"

Connected through hyperedge HE-6 (induced by source paper "sygus techniques in the core of an smt solver"):
  with members:
    - "results and analysis of sygus comp 15"
    - "smt based model checking for recursive programs"

Connected through hyperedge HE-7 (induced by source paper "programming not only by example"):
  with members:
    - "program synthesis from polymorphic refinement types"

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)