Automatic Generation of Text Descriptive Comments for Code Blocks
Table 4: Data Sets for Source Code Clustering
['[EMPTY]', 'Problem', 'Year', '# of methods']
The goal is to classify a given Java method (we only use the body block without name and parameters) into a predefined set of classes depending on its functionality. Our data set comes from the Google Code Jam contest (2008∼2016), which there are multiple problems, each associated with a number of correct solutions contributed by programmers. Each solution is a Java method. The set of solutions for the same problem are considered to function identically and belong to the same class in this work. We use the solutions (10,724 methods) of 6 problems as training set and the solutions (30 methods) of the other 6 problems as the test set. Notice that the problems in the training data and the ones in the test data do not overlap. We specifically design the data set this way because, many methods for the same problem tend to use the same or similar set of identifiers, which is not true in real world application.