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.

该文提出了一种将程序合成作为连续优化问题的新型方法，并使用现代演化方法解决问题，同时提出了一种映射方案将连续形式转换为实际的程序。通过比较 GENESYS 和其他程序综合技术，证明 GENESYS 在相同的时间预算内综合出更多程序。