Understanding developers' natural language queries with interactive clarification

When performing software maintenance tasks, developers often need to understand a series of background knowledge based on information distributed in different software repositories such as source codes, version control systems and bug tracking systems. An effective way to support developers to understand such knowledge is to provide an integrated knowledge base and allow them to ask questions using natural language. Existing approaches cannot well support natural language questions that involve a series of conceptual relationships and are phrased in a flexible way. In this paper, we propose an interactive approach for understanding developers' natural language queries. The approach can understand a developer's natural language questions phrased in different ways by generating a set of ranked and human-readable candidate questions and getting feedback from the developer. Based on the candidate question confirmed by the developer, the approach can then synthesize an answer by constructing and executing a structural query to the knowledge base. We have implemented a tool following the proposed approach and conducted a user study using the tool. The results show that our approach can help developers get the desired answers more easily and accurately.