Mining Complex Temporal API Usage Patterns: An Evolutionary Approach
Samuel Huppe, Mohamed Aymen Saied, Houari A. Sahraoui · 2017
Learning to use existing or new software libraries is a difficult task for software developers, which would impede their productivity. Much existing work has provided different techniques to mine API usage patterns from client programs inorder to help developers on understanding and using existinglibraries. However, these techniques produce incomplete patterns, i.e., without temporal properties, or simple ones. In this paper, we propose a new formulation of the problem of API temporal pattern mining and a new approach to solve it. Indeed, we learn complex temporal patterns using a genetic programming approach. Our preliminary results show that across a considerable variability of client programs, our approach has been able to infer non-trivial patterns that reflect informative temporal properties.