human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "how to design a program repair bot insights from the repairnator project"
  Abstract: Program repair research has made tremendous progress over the last few years, and software development bots are now being invented to help developers gain productivity. In this paper, we investigate the concept of a "program repair bot" and present Repairnator. The Repairnator bot is an autonomous agent that constantly monitors test failures, reproduces bugs, and runs program repair tools against each reproduced bug. If a patch is found, Repairnator bot reports it to the developers. At the time of writing, Repairnator uses three different program repair systems and has been operating since February 2017. In total, it has studied 11 523 test failures over 1 609 open-source software projects hosted on GitHub, and has generated patches for 15 different bugs. Over months, we hit a number of hard technical challenges and had to make various design and engineering decisions. This gives us a unique experience in this area. In this paper, we reflect upon Repairnator in order to share this knowledge with the automatic program repair community.

Connected through hyperedge HE-1 (induced by source paper "ifixr bug report driven program repair"):
  with members:
    - "d c a divide and conquer approach to ir based bug localization"
    - "tbar revisiting template based automated program repair"
    - "sorting and transforming program repair ingredients via deep learning code similarities"
    - "alleviating patch overfitting with automatic test generation a study of feasibility and effectiveness for the nopol repair system"
    - "getafix learning to fix bugs automatically"
    - "avatar fixing semantic bugs with fix patterns of static analysis violations"
    - "on reliability of patch correctness assessment"
    - "fixminer mining relevant fix patterns for automated program repair"

Connected through hyperedge HE-2 (induced by source paper "validation of automatically generated patches an appetizer"):
  with members:
    - "metamorphic testing a new approach for generating next test cases"
    - "alleviating patch overfitting with automatic test generation a study of feasibility and effectiveness for the nopol repair system"
    - "getafix learning to fix bugs automatically"
    - "predicting metamorphic relation for matrix calculation programs"
    - "using semi supervised learning for predicting metamorphic relations"
    - "identifying patch correctness in test based program repair"
    - "nopol automatic repair of conditional statement bugs in java programs"
    - "precise condition synthesis for program repair"

Connected through hyperedge HE-3 (induced by source paper "v2 fast detection of configuration drift in python"):
  with members:
    - "dockerizeme automatic inference of environment dependencies for python code snippets"
    - "finding faster configurations using flash"
    - "gistable evaluating the executability of python code snippets on github"
    - "tortoise interactive system configuration repair"
    - "stack overflow in github any snippets there"
    - "from query to usable code an analysis of stack overflow code snippets"
    - "a quantitative study of java software buildability"

Connected through hyperedge HE-4 (induced by source paper "msrbot using bots to answer questions from software repositories"):
  with members:
    - "explainable software bot contributions case study of automated bug fixes"
    - "repairnator patches programs automatically"
    - "an additional set of automated eyes chatbots for agile retrospectives"
    - "understanding chatbot mediated task management"
    - "programming bots by synthesizing natural language expressions into api invocations"
    - "distributed representations of words and phrases and their compositionality"
    - "introduction to the conll 2003 shared task language independent named entity recognition"

Connected through hyperedge HE-5 (induced by source paper "suggestions on test suite improvements with automatic infection and propagation analysis"):
  with members:
    - "automatic test improvement with dspot a study with ten mature open source projects"
    - "a snowballing literature study on test amplification"
    - "a comprehensive study of pseudo tested methods"
    - "is the stack distance between test case and method correlated with test effectiveness"
    - "will my tests tell me if i break this code"

Connected through hyperedge HE-6 (induced by source paper "repairnator patches programs automatically"):
  with members:
    - "explainable software bot contributions case study of automated bug fixes"
    - "automatic software repair a bibliography"
    - "automatic repair of real bugs in java a large scale experiment on the defects4j dataset"
    - "nopol automatic repair of conditional statement bugs in java programs"
    - "dynamic patch generation for null pointer exceptions using metaprogramming"

Connected through hyperedge HE-7 (induced by source paper "an approach and benchmark to detect behavioral changes of commits in continuous integration"):
  with members:
    - "automatic test improvement with dspot a study with ten mature open source projects"
    - "bears an extensible java bug benchmark for automatic program repair studies"
    - "a comprehensive study of pseudo tested methods"
    - "shadow symbolic execution with java pathfinder"
    - "reinforcement learning for automatic test case prioritization and selection in continuous integration"

Connected through hyperedge HE-8 (induced by source paper "bears an extensible java bug benchmark for automatic program repair studies"):
  with members:
    - "automatic software repair a bibliography"
    - "dissection of a bug dataset anatomy of 395 patches from defects4j"
    - "nopol automatic repair of conditional statement bugs in java programs"
    - "dynamic patch generation for null pointer exceptions using metaprogramming"

Question: Please tell me which class the center node 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)