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: "synthesizing bijective lenses"
  Abstract: Bidirectional transformations between different data representations occur frequently in modern software systems. They appear as serializers and deserializers, as database views and view updaters, and more. Manually building bidirectional transformations---by writing two separate functions that are intended to be inverses---is tedious and error prone. A better approach is to use a domain-specific language in which both directions can be written as a single expression. However, these domain-specific languages can be difficult to program in, requiring programmers to manage fiddly details while working in a complex type system. #R##N#To solve this, we present Optician, a tool for type-directed synthesis of bijective string transformers. The inputs to Optician are two ordinary regular expressions representing two data formats and a few concrete examples for disambiguation. The output is a well-typed program in Boomerang (a bidirectional language based on the theory of lenses). The main technical challenge involves navigating the vast program search space efficiently enough. Unlike most prior work on type-directed synthesis, our system operates in the context of a language with a rich equivalence relation on types (the theory of regular expressions). We synthesize terms of a equivalent language and convert those generated terms into our lens language. We prove the correctness of our synthesis algorithm. We also demonstrate empirically that our new language changes the synthesis problem from one that admits intractable solutions to one that admits highly efficient solutions. We evaluate Optician on a benchmark suite of 39 examples including both microbenchmarks and realistic examples derived from other data management systems including Flash Fill, a tool for synthesizing string transformations in spreadsheets, and Augeas, a tool for bidirectional processing of Linux system configuration files.

Connected through hyperedge HE-1 (induced by source paper "the geometry of syntax and semantics for directed file transformations"):
  with members:
    - "dire a neural approach to decompiled identifier naming"
    - "tree edit distance cannot be computed in strongly subcubic time unless apsp can"
    - "a language theoretic view on network protocols"
    - "de bruijn entropy and string similarity"
    - "an optimal decomposition algorithm for tree edit distance"

Connected through hyperedge HE-2 (induced by source paper "visualization by example"):
  with members:
    - "program synthesis using abstraction refinement"
    - "program synthesis using conflict driven learning"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "structuring the synthesis of heap manipulating programs"):
  with members:
    - "structuring the synthesis of heap manipulating programs"
    - "synthesizing imperative programs from examples guided by static analysis"
    - "neural sketch learning for conditional program generation"
    - "component based synthesis of table consolidation and transformation tasks from examples"
    - "program synthesis from polymorphic refinement types"

Connected through hyperedge HE-4 (induced by source paper "program synthesis through reinforcement learning guided tree search"):
  with members:
    - "adaptive neural compilation"
    - "deepcoder learning to write programs"
    - "component based synthesis of table consolidation and transformation tasks from examples"
    - "terpret a probabilistic programming language for program induction"
    - "prioritized experience replay"
    - "dueling network architectures for deep reinforcement learning"
    - "deep reinforcement learning with double q learning"

Connected through hyperedge HE-5 (induced by source paper "structuring the synthesis of heap manipulating programs"):
  with members:
    - "structuring the synthesis of heap manipulating programs"
    - "synthesizing imperative programs from examples guided by static analysis"
    - "neural sketch learning for conditional program generation"
    - "component based synthesis of table consolidation and transformation tasks from examples"
    - "program synthesis from polymorphic refinement types"

Connected through hyperedge HE-6 (induced by source paper "narcissus deriving correct by construction decoders and encoders from binary formats"):
  with members:
    - "certified context free parsing a formalisation of valiant s algorithm in agda"
    - "trx a formally verified parser interpreter"
    - "formal derivation of concurrent garbage collectors"

Connected through hyperedge HE-7 (induced by source paper "bidirectional evaluation with directmanipulation"):
  with members:
    - "automatic software repair a bibliography"
    - "programmatic and direct manipulation together at last"
    - "semi automated svg programming via direct manipulation"

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.PL(Programming Languages)