Mining unit tests for code recommendation

Abstract

Developers spend a significant portion of their time understanding and learning the correct usage of the APIs of libraries they want to integrate in their projects. However, learning how to effectively use APIs is complex and time consuming. Code recommendation systems play a crucial role facilitating developers in this task by providing to them relevant examples while they code. This paper proposes a novel approach to code recommendation in which code examples are automatically obtained by mining and manipulating unit tests. In this paper we discuss the theoretical and practical implications that underpin this idea. The discussion leads to a series of fascinating research challenges that we organized in a research agenda.