Decision Tree Learning in CEGIS-Based Termination Analysis
Decision Tree Learning in CEGIS-Based Termination Analysis
复制标题
基于 CEGIS 的终止分析中的决策树学习
DOI:
10.1007/978-3-030-81688-9_4
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发表时间:
2021
期刊:
影响因子:
--
通讯作者:
Hasuo Ichiro
中科院分区:
文献类型:
--
作者:
Kura Satoshi;Unno Hiroshi;Hasuo Ichiro
We present a novel decision tree-based synthesis algorithm of ranking functions for verifying program termination. Our algorithm is integrated into the workflow of CounterExample Guided Inductive Synthesis (CEGIS). CEGIS is an iterative learning model where, at each iteration, (1) a synthesizer synthesizes a candidate solution from the current examples, and (2) a validator accepts the candidate solution if it is correct, or rejects it providing counterexamples as part of the next examples. Our main novelty is in the design of a synthesizer: building on top of a usual decision tree learning algorithm, our algorithm detectscyclesin a set of example transitions and uses them for refining decision trees. We have implemented the proposed method and obtained promising experimental results on existing benchmark sets of (non-)termination verification problems that require synthesis of piecewise-defined lexicographic affine ranking functions.
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DOI:
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发表时间:
2014
期刊:
European Symposium on Programming
影响因子:
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作者:
Caterina Urban;A. Miné
通讯作者:
A. Miné
DOI:
--
发表时间:
2015
期刊:
arXiv.org
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DOI:
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2007
期刊:
International Conference on Rewriting Techniques and Applications
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作者:
C. Marché;H. Zantema
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DOI:
10.1145/2737924.2737976
发表时间:
2015
期刊:
Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation
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作者:
L. Gonnord;D. Monniaux;Gabriel Radanne
通讯作者:
Gabriel Radanne
DOI:
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发表时间:
2020
期刊:
arXiv.org
影响因子:
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作者:
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通讯作者:
Eric Koskinen