Statistical learning approach for mining API usage mappings for code migration

摘要: The same software product nowadays could appear in multiple platforms and devices. To address business needs, companies develop a programming language then migrate it to another one. support that process, semi-automatic migration tools have been proposed. However, they require users manually define the mappings between respective APIs of libraries used two languages. reduce such manual effort, we introduce StaMiner, novel data-driven approach statistically learns from corpus corresponding client code languages Java C#. Instead using heuristics on textual or structural similarity map API methods classes as existing mining approaches, StaMiner is based statistical model provides for with all possible arities. Our empirical evaluation several projects shows can detect usage higher accuracy than state-of-the-art approach. With resulting mined by Java2CSharp, an tool, achieve level accuracy.