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 "a proof of strong normalisation using domain theory"):
  Abstract: In 1961, Spector presented an extension of Godel's system T by a new schema of definition called bar recursion. With this new schema, he was able to give an interpretation of Analysis, extending Godel's Dialectica interpretation of Arithmetic, and completing preliminary results of Kreisel. Tait proved a normalisation theorem for Spector's bar recursion, by embedding it in a system with infinite terms. In a paper by Berardi, Bezem and Coquand, an alternative form of bar recursion was introduced. This allowed to give an interpretation of Analysis by modified realisability, instead of Dialectica interpretation. It presented also a normalisation proof for this new schema, but this proof, which used Tait's method of introducing infinite terms, was quite complex. It was simplified significantly by U. Berger, who used instead a modification of Plotkin's computational adequacy theorem, and could prove strong normalisation. In a way, the idea is to replace infinite terms by elements of a domain interpretation. This domain has the property that a term is strongly normalisable if its semantics is not ⊥. The main contribution of this paper is to show that, using ideas from intersection types and Martin-Lof's domain interpretation of type theory, one can in turn simplify further U. Berger's argument. Contrary to him, we build a domain model for an untyped programming language. Compared to other works, there is no need of an extra hypothesis to deduce strong normalisation from the domain interpretation. A noteworthy feature of this domain model is that it is in a natural way a complete lattice, and in particular it has a top element which can be seen as the interpretation of a top-level exception in programming language. We think that this model can be the basis of modular proofs of strong normalisation for various type systems. As a main application, we show that Martin-Lof dependent type theory extended with a program for Spector double negation shift, similar to bar recursion, has the strong normalisation property.

Includes members:
  Member "strong normalization for applied lambda calculi":
    also connected through other hyperedges:
      (none)
  Member "on equivalence and canonical forms in the lf type theory":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a cubical language for bishop sets")

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.LO(Logic in Computer Science)