API usage pattern recommendation for software development

Application Programming Interfaces (APIs) facilitate pragmatic reuse and improve the productivity of software development. An API usage pattern documents a set of method calls from multiple API classes to achieve a reusable functionality. Existing approaches often use frequent-sequence mining to extract API usage patterns. However, as reported by earlier studies, frequent-sequence mining may not produce a complete set of usage patterns. In this paper, we explore the possibility of mining API usage patterns without relying on frequent-pattern mining. Our approach represents the source code as a network of object usages where an object usage is a set of method calls invoked on a single API class. We automatically extract usage patterns by clustering the data based on the co-existence relations between object usages. We conduct an empirical study using a corpus of 11,510 Android applications. The results demonstrate that our approach can effectively mine API usage patterns with high completeness and low redundancy. We observe 18% and 38% improvement on F-measure and response time respectively comparing to usage pattern extraction using frequent-sequence mining.