论文标题
通过连续优化综合程序
Synthesizing Programs with Continuous Optimization
论文作者
论文摘要
基于某些规范的自动软件生成称为程序合成。大多数现有方法将程序合成作为带有离散参数的搜索问题。在本文中，我们介绍了程序合成作为连续优化问题的新颖表述，并使用最先进的进化方法，即称为协方差矩阵适应进化策略来解决该问题。然后，我们提出了一个映射方案，以将连续公式转换为实际程序。我们将我们的系统（称为Genesys）与最近的几种程序合成技术（在离散和连续域中）进行了比较，并表明Genesys在固定时间预算中综合了比现有方案更多的计划。例如，对于长度为10的计划，Genesys在同一时间预算中的现有计划比现有方案多28％。
Automatic software generation based on some specification is known as program synthesis. Most existing approaches formulate program synthesis as a search problem with discrete parameters. In this paper, we present a novel formulation of program synthesis as a continuous optimization problem and use a state-of-the-art evolutionary approach, known as Covariance Matrix Adaptation Evolution Strategy to solve the problem. We then propose a mapping scheme to convert the continuous formulation into actual programs. We compare our system, called GENESYS, with several recent program synthesis techniques (in both discrete and continuous domains) and show that GENESYS synthesizes more programs within a fixed time budget than those existing schemes. For example, for programs of length 10, GENESYS synthesizes 28% more programs than those existing schemes within the same time budget.
