Hierarchical Learning of Cross-Language Mappings through Distributed Vector Representations for Code
Table 2. Average MAP scores for element mappings at various granularity levels
['Levels', 'Expressions', 'Statements', 'Methods']
Element mappings We extract all the expressions, the statements and the methods of each project in our data set by traversing the AST representation to identify the element type, then we manually defined ground truth elements pairs. We treat each element in Java as a query to retrieve the top-k elements of C#. Then we use Mean Average Precision (MAP) as the metric to evaluate this task. Due to the limitation of pages, instead of showing the MAP score for each type of element of each project, we calculate the average MAP of all project for each type of element.