FSE 2016 All Events

24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE 2016), November 13–18, 2016, Seattle, WA, USA

Desktop Layout

Tool Demonstrations
Foyer 3rd/4th Floor
T2API: Synthesizing API Code Usage Templates from English Texts with Statistical Translation
Thanh Nguyen, Peter C. Rigby, Anh Tuan Nguyen, Mark Karanfil, and Tien N. Nguyen
(Iowa State University, USA; Concordia University, Canada; University of Texas at Dallas, USA)
Publisher's Version
Abstract: In this work, we develop T2API, a statistical machine translation-based tool that takes a given English description of a programming task as a query, and synthesizes the API usage template for the task by learning from training data. T2API works in two steps. First, it derives the API elements relevant to the task described in the input by statistically learning from a StackOverflow corpus of text descriptions and corresponding code. To infer those API elements, it also considers the context of the words in the textual input and the context of API elements that often go together in the corpus. The inferred API elements with their relevance scores are ensembled into an API usage by our novel API usage synthesis algorithm that learns the API usages from a large code corpus via a graph-based language model. Importantly, T2API is capable of generating new API usages from smaller, previously-seen usages.


Time stamp: 2019-06-24T21:26:28+02:00