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 "v2 fast detection of configuration drift in python"):
  Abstract: Code snippets are prevalent, but are hard to reuse because they often lack an accompanying environment configuration. Most are not actively maintained, allowing for drift between the most recent possible configuration and the code snippet as the snippet becomes out-of-date over time. Recent work has identified the problem of validating and detecting out-of-date code snippets as the most important consideration for code reuse. However, determining if a snippet is correct, but simply out-of-date, is a non-trivial task. In the best case, breaking changes are well documented, allowing developers to manually determine when a code snippet contains an out-of-date API usage. In the worst case, determining if and when a breaking change was made requires an exhaustive search through previous dependency versions. #R##N#We present V2, a strategy for determining if a code snippet is out-of-date by detecting discrete instances of configuration drift, where the snippet uses an API which has since undergone a breaking change. Each instance of configuration drift is classified by a failure encountered during validation and a configuration patch, consisting of dependency version changes, which fixes the underlying fault. V2 uses feedback-directed search to explore the possible configuration space for a code snippet, reducing the number of potential environment configurations that need to be validated. When run on a corpus of public Python snippets from prior research, V2 identifies 248 instances of configuration drift.

Includes members:
  Member "dockerizeme automatic inference of environment dependencies for python code snippets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning from understanding and supporting devops artifacts for docker")
  Member "finding faster configurations using flash":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning software configuration spaces a systematic literature review")
  Member "gistable evaluating the executability of python code snippets on github":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "conflict and cooperation ai research and development in terms of the economy of conventions")
  Member "how to design a program repair bot insights from the repairnator project":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ifixr bug report driven program repair")
  Member "tortoise interactive system configuration repair":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "smt based robot transition repair")
  Member "stack overflow in github any snippets there":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "code duplication on stack overflow")
  Member "from query to usable code an analysis of stack overflow code snippets":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "code duplication on stack overflow")
  Member "a quantitative study of java software buildability":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "gistable evaluating the executability of python code snippets on github")

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)