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 "practical predictive race detection"):
  Abstract: Widely used data race detectors, including the state-of-the-art FastTrack algorithm, incur performance costs that are acceptable for regular in-house testing, but miss races detectable from the analyzed execution. Predictive analyses detect more data races in an analyzed execution than FastTrack does, but at significantly higher cost. #R##N#This paper presents SmartTrack, an algorithm that optimizes predictive race detection analyses, including two analyses from prior work and a new analysis introduced in this paper. SmartTrack's algorithm incorporates two main optimizations: epoch and ownership optimizations from prior work, applied to predictive analysis for the first time; and novel conflicting critical section optimizations introduced by this paper. Our evaluation shows that SmartTrack achieves performance competitive with FastTrack-a qualitative improvement to the state-of-the-art in data race detection.

Includes members:
  Member "fast sound and effectively complete dynamic race detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dependence aware unbounded sound predictive race detection")
  Member "ireplayer in situ and identical record and replay for multithreaded applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient and deterministic record replay for actor languages")
  Member "dynamic race prediction in linear time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "atomicity checking in linear time using vector clocks")

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.SE(Software Engineering)