Natural language text is a common form of knowledge representation in various software artifacts. During the practice of software reuse, software developers usually need to search the large amount of textual resource. This paper presents a software text semantic search approach based on code structure knowledge. This approach extracts a code structure graph from software source code and leverages it as a domain-specific knowledge base to analyze the semantic meanings of natural language texts. The semantic information is combined with information retrieval technology to re-rank text search results semantically. Experimental results on StackOverflow dataset show that this approach achieves at least 13.77% improvement in mean average precision (MAP) comparing to several text retrieval approaches.