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Proceedings of the ACM on Programming Languages
Article . 2020 . Peer-reviewed
License: CC BY
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DBLP
Article . 2020
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Incremental predicate analysis for regression verification

Authors: Qianshan Yu; Fei He 0001; Bow-Yaw Wang;

Incremental predicate analysis for regression verification

Abstract

Software products are evolving during their life cycles. Ideally, every revision need be formally verified to ensure software quality. Yet repeated formal verification requires significant computing resources. Verifying each and every revision can be very challenging. It is desirable to ameliorate regression verification for practical purposes. In this paper, we regard predicate analysis as a process of assertion annotation. Assertion annotations can be used as a certificate for the verification results. It is thus a waste of resources to throw them away after each verification. We propose to reuse the previously-yielded assertion annotation in regression verification. A light-weight impact-analysis technique is proposed to analyze the reusability of assertions. A novel assertion strengthening technique is furthermore developed to improve reusability of annotation. With these techniques, we present an incremental predicate analysis technique for regression verification. Correctness of our incremental technique is formally proved. We performed comprehensive experiments on revisions of Linux kernel device drivers. Our technique outperforms the state-of-the-art program verification tool CPAchecker by getting 2.8x speedup in total time and solving additional 393 tasks.

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
Published in a Diamond OA journal