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 bayesian network approach to assess and predict software quality using activity based quality models"):
  Abstract: Assessing and predicting the complex concept of software quality is still challenging in practice as well as research. Activity-based quality models break down this complex concept into more concrete definitions, more precisely facts about the system, process and environment and their impact on activities performed on and with the system. However, these models lack an operationalisation that allows to use them in assessment and prediction of quality. Bayesian Networks (BN) have been shown to be a viable means for assessment and prediction incorporating variables with uncertainty. This paper describes how activity-based quality models can be used to derive BN models for quality assessment and prediction. The proposed approach is demonstrated in a proof of concept using publicly available data.

Includes members:
  Member "a bayesian network approach to assess and predict software quality using activity based quality models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "operationalised product quality models and assessment")
  Member "tool support for continuous quality control":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "evaluating maintainability prejudices with a large scale study of open source projects")
  Member "a comprehensive model of usability":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the use of application scanners in software product quality assessment")
  Member "an activity based quality model for maintainability":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "evaluating maintainability prejudices with a large scale study of open source projects")
  Member "a literature survey of the quality economics of defect detection techniques":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a bayesian network approach to assess and predict software quality using activity based quality models")

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)