Probabilistic Synthesis for Program with Non-API Operations

Yating Zhang, Wei Dong, Daiyan Wang, Jiaxin Liu, Binbin Liu
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Abstract

The current approaches to program synthesis focus more on works that contain only API methods. However, our survey shows that the ratio of non-API operations to API calls is very close in Java programs. Although non-API operations are difficult to obtain specific information from user intent, those operations in such as mathematics and logic are frequent and important, and that is an indispensable key in practical development tasks. We present Cana (Capsulate Non-API), an improved approach of probabilistic synthesis for non-API operations. Cana synthesizes programs with non-API operations through two main ideas. One is to encapsulate non-API operations into API calls, and the user also can provide related information when describing incomplete specifications. The other is heuristic strategies to solve the difficult problems that select variables with the same type. Experiments show that Cana can synthesize programs contains combinations of non-API operations in seconds.
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非api操作程序的概率综合
当前的程序合成方法更多地关注于只包含API方法的工作。然而,我们的调查显示,在Java程序中,非API操作与API调用的比例非常接近。虽然非api操作很难从用户意图中获取具体的信息,但数学、逻辑等操作频繁且重要,是实际开发任务中不可或缺的关键。我们提出了Cana(荚膜非api),一种改进的非api操作的概率合成方法。Cana通过两个主要思想将程序与非api操作结合起来。一种是将非API操作封装到API调用中,用户在描述不完整的规范时也可以提供相关信息。另一种是启发式策略,用于解决选择同类型变量的难题。实验表明,Cana可以在几秒内合成包含非api操作组合的程序。
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