Automatically inferring loop invariants via algorithmic learning

@article{Jung2015AutomaticallyIL,
  title={Automatically inferring loop invariants via algorithmic learning},
  author={Yungbum Jung and Soonho Kong and Cristina David and Bow-Yaw Wang and Kwangkeun Yi},
  journal={Mathematical Structures in Computer Science},
  year={2015},
  volume={25},
  pages={892-915}
}
By combining algorithmic learning, decision procedures, predicate abstraction, and simple templates for quantified formulae, we present an automated technique for finding loop invariants. Theoretically, this technique can find arbitrary first-order invariants (modulo a fixed set of atomic propositions and an underlying SMT solver) in the form of the given template and exploit the flexibility in invariants by a simple randomized mechanism. In our study, the proposed technique was able to find… CONTINUE READING

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