Provenance-guided synthesis of Datalog programs
Provenance-guided synthesis of Datalog programs
复制标题
数据记录程序的来源引导综合
DOI：
10.1145/3371130
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发表时间：
2019
影响因子：
--
通讯作者：
Bernhard Scholz
中科院分区：
文献类型：
--
作者：
Mukund Raghothaman;Jonathan Mendelson;David Zhao;M. Naik;Bernhard Scholz
我们提出了一种从输入输入规格中综合数据的新方法。程序，数据求解器评估所提出的程序，以确定是否满足所需的规范。我们提出了有效的算法，以从数据求解器获得的“为什么”和“为什么不”的预期信息来学习这些约束。在合成中，包括谓词，减少运行时间，并减少合成性能的差异。不同的域，Prosynth能够在平均每个任务（比基线方法快的数量级）中在10秒内综合所需的程序，并且在其中28个方向只有一秒钟。
We propose a new approach to synthesize Datalog programs from input-output specifications. Our approach leverages query provenance to scale the counterexample-guided inductive synthesis (CEGIS) procedure for program synthesis. In each iteration of the procedure, a SAT solver proposes a candidate Datalog program, and a Datalog solver evaluates the proposed program to determine whether it meets the desired specification. Failure to satisfy the specification results in additional constraints to the SAT solver. We propose efficient algorithms to learn these constraints based on “why” and “why not” provenance information obtained from the Datalog solver. We have implemented our approach in a tool called ProSynth and present experimental results that demonstrate significant improvements over the state-of-the-art, including in synthesizing invented predicates, reducing running times, and in decreasing variances in synthesis performance. On a suite of 40 synthesis tasks from three different domains, ProSynth is able to synthesize the desired program in 10 seconds on average per task—an order of magnitude faster than baseline approaches—and takes only under a second each for 28 of them.
PUG：为什么和为什么不起源的框架和实际实施
DOI：
10.1007/s00778-018-0518-5
发表时间：
2018
期刊：
The VLDB Journal
影响因子：
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作者：
Lee, Seokki;Ludäscher, Bertram;Glavic, Boris
通讯作者：
Glavic, Boris
基于约束的数据记录程序综合
DOI：
10.1007/978-3-319-66158-2_44
发表时间：
2017
期刊：
International Conference on Principles and Practice of Constraint Programming
影响因子：
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作者：
Albarghouthi, Aws;Koutris, Paraschos;Naik, Mayur;Smith, Calvin
通讯作者：
Smith, Calvin