Predicate Generation for Learning-Based Quantifier-Free Loop Invariant Inference
Logic in Computer Science
2015-07-01 v2 Machine Learning
Abstract
We address the predicate generation problem in the context of loop invariant inference. Motivated by the interpolation-based abstraction refinement technique, we apply the interpolation theorem to synthesize predicates implicitly implied by program texts. Our technique is able to improve the effectiveness and efficiency of the learning-based loop invariant inference algorithm in [14]. We report experiment results of examples from Linux, SPEC2000, and Tar utility.
Keywords
Cite
@article{arxiv.1207.7167,
title = {Predicate Generation for Learning-Based Quantifier-Free Loop Invariant Inference},
author = {Wonchan Lee and Yungbum Jung and Bow-yaw Wang and Kwangkuen Yi},
journal= {arXiv preprint arXiv:1207.7167},
year = {2015}
}