BibTeX
CSL-JSON
MLA
Harvard
Predicate Generation for Learning-Based Quantifier-Free Loop Invariant
Inference
release_qyd2dlqcsbfbfcajuktujlqtni
by
Wonchan Lee, Yungbum Jung (Seoul National
University), Bow-yaw Wang, Kwangkuen Yi (Seoul National
University)
Released
as a article
.
2012
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.
In text/plain
format
Archived Files and Locations
application/pdf 490.6 kB
file_hpxvngcuc5gmnb5oznustq77jq
|
arxiv.org (repository) web.archive.org (webarchive) |
Read Archived PDF
Preserved and Accessible
arXiv
1207.7167v1
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
access all versions, variants, and formats of this works (eg, pre-prints)
Cite This
Lookup Links