human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "Knowledge-Based Re-engineering of Legacy Programs for Robustness in Automated Design"
  Abstract: Systems for automated design optimization of complex real-world objects can, in principle, be constructed by combining domain-independent numerical routines with existing domain-specific analysis and simulation programs. Unfortunately, such legacy analysis codes are frequently unsuitable for use in automated design. They may crash for large classes of input, be numerically unstable or locally non-smooth, or be highly sensitive to control parameters. To be useful, analysis programs must be modified to reduce or eliminate only the undesired behaviors, without altering the desired computation. To do this by direct modification of the programs is labor-intensive, and necessitates costly revalidation. We have implemented a high-level language and run-time environment that allow failure-handling strategies to be incorporated into existing Fortran and C analysis programs while preserving their computational integrity. Our approach relies on globally managing the execution of these programs at the level of discretely callable functions so that the computation is only affected when problems are detected. Problem handling procedures are constructed from a knowledge base of generic problem management strategies. We show that our approach is effective in improving analysis program robustness and design optimization performance in the domain of conceptual design of jet engine nozzles.

Connected through hyperedge HE-1 (induced by source paper "A Transformation System for Interactive Reformulation of Design Optimization Strategies"):
  with members:
    - "Program Synthesis and Transformation Techniques for Simpuation, Optimization and Constraint Satisfaction Deductive Synthesis of Numerical"

Connected through hyperedge HE-2 (induced by source paper "A Computational Environment for Exhaust Nozzle Design"):
  with members:
    (none)

Question: Please tell me which class the center node belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Case_Based