Mining Complex Temporal API Usage Patterns: An Evolutionary Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Huppe:2017:ICSE-C,

• author = "Samuel Huppe and Mohamed Aymen Saied and Houari Sahraoui",
• booktitle = "2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C)",
• title = "Mining Complex Temporal {API} Usage Patterns: An Evolutionary Approach",
• year = "2017",
• pages = "274--276",
• month = may,
• keywords = "genetic algorithms, genetic programming, SBSE, API documentation, API usage pattern Linear temporal logic",
• DOI = "doi:10.1109/ICSE-C.2017.147",
• size = "2.2 pages",
• abstract = "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 in order to help developers on understanding and using existing libraries. 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.",
• notes = "Also known as \cite{7965328}",

}

Genetic Programming entries for Samuel Huppe Mohamed Aymen Saied Houari Sahraoui

Citations