Boosting Component-based Synthesis with API Usage Knowledge

Abstract

Component-based synthesis is one of the hottest research areas in automated software engineering. It aims to generate programs from a collection of components like Java library. However, the program space constituted by all the components in the library is fairly large, which leads to a vast number of candidate programs generated for a long time. The intractability of the program space affects the synthesis efficiency of the program and the size of the program generated. In this paper, we propose ITAs, a framework of iterative program synthesis via API usage knowledge from the Internet, which can significantly improve the efficiency of program synthesis. ITAs aims to constrain the program space by combining two main ideas. First, narrow down the program space from the outside via the guidance of API usage knowledge. Second, expand the program space from the inside via iterative strategy based on knowledge. For evaluation, we collect a set of programming tasks and compare our approach with a program synthesis tool on synthesizing these tasks. The experiment results show that Itas can significantly improve the efficiency of program synthesis, which can reduce the synthesis time by 97.1 % than the original synthesizer.