Synthesis of Parametric Programs using Genetic Programming and Model Checking

Infinity Pub Date : 2014-02-26 DOI:10.4204/EPTCS.140.5
Gal Katz, D. Peled
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引用次数: 10

Abstract

Formal methods apply algorithms based on mathematical principles to enhance the reliability of systems. It would only be natural to try to progress from verification, model checking or testing a system against its formal specification into constructing it automatically. Classical algorithmic synthesis theory provides interesting algorithms but also alarming high complexity and undecidability results. The use of genetic programming, in combination with model checking and testing, provides a powerful heuristic to synthesize programs. The method is not completely automatic, as it is fine tuned by a user that sets up the specification and parameters. It also does not guarantee to always succeed and converge towards a solution that satisfies all the required properties. However, we applied it successfully on quite nontrivial examples and managed to find solutions to hard programming challenges, as well as to improve and to correct code. We describe here several versions of our method for synthesizing sequential and concurrent systems.
基于遗传规划和模型检验的参数规划综合
形式化方法应用基于数学原理的算法来提高系统的可靠性。尝试从验证、模型检查或根据正式规范测试系统到自动构建它是很自然的。经典的算法综合理论提供了有趣的算法,但也令人担忧的高复杂性和不可确定的结果。遗传规划的使用,结合模型检查和测试,提供了一个强大的启发式来综合程序。该方法不是完全自动的,因为它是由设置规范和参数的用户进行微调的。它也不能保证总是成功并收敛于满足所有必需属性的解决方案。然而,我们成功地将其应用于相当重要的示例中,并设法找到解决困难编程挑战的解决方案,以及改进和纠正代码。我们在这里描述了几个版本的合成顺序和并发系统的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
26
审稿时长
10 weeks
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