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 "type safety with json subschema"):
  Abstract: JSON is a popular data format used pervasively in web APIs, cloud computing, NoSQL databases, and increasingly also machine learning. JSON Schema is a language for declaring the structure of valid JSON data. There are validators that can decide whether a JSON document is valid with respect to a schema. Unfortunately, like all instance-based testing, these validators can only show the presence and never the absence of a bug. This paper presents a complementary technique: JSON subschema checking, which can be used for static type checking with JSON Schema. Deciding whether one schema is a subschema of another is non-trivial because of the richness of the JSON Schema specification language. Given a pair of schemas, our approach first canonicalizes and simplifies both schemas, then decides the subschema question on the canonical forms, dispatching simpler subschema queries to type-specific checkers. We apply an implementation of our subschema checking algorithm to 8,548 pairs of real-world JSON schemas from different domains, demonstrating that it can decide the subschema question for most schema pairs and is always correct for schema pairs that it can decide. We hope that our work will bring more static guarantees to hard-to-debug domains, such as cloud computing and artificial intelligence.

Includes members:
  Member "type driven automated learning with lale":
    also connected through other hyperedges:
      (none)
  Member "the machine learning bazaar harnessing the ml ecosystem for effective system development":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hamlet a learning curve enabled multi armed bandit for algorithm selection")
  Member "json data model query languages and schema specification":
    also connected through other hyperedges:
      (none)
  Member "api design for machine learning software experiences from the scikit learn project":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning to segment 3d point clouds in 2d image space")

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.PL(Programming Languages)