Classification of source code solutions based on the solved programming tasks

The programming is based on the source code. It is often difficult to determine from the source code what task was solved, due to the diversity of programming. For this reason, developers often do not recognize the functionality of existing codes and waste time by re-implementing the problem. This paper presents a machine-based model that can effectively identify and assign the source code to the solved task. Machine learning implements by a convolution network, which requires the presence of consistent (properly functioning, outputs the expected output for each input) source codes to the input. To convert the text data will be used for text processing using CBOW model, which model will be able to classify the source codes written in the same language.