Published January 20, 2023 | Version v2

Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study

Authors/Creators

Description

This is material for a work under review. If used, please cite accordingly.

This is a reproduction package for "Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study", where line and token completion performance of UniXcoder, CodeGPT, and InCoder is assessed over datasets containing different amounts of type annotations and comments.

Files

dataset-disclaimer.txt

Files (15.4 GB)

Name Size
md5:cae82e72776efeedc8279c8aed54ecf3
544 Bytes Preview Download
md5:3063f31bb8d66dd2f3eb978557fe5eec
12.6 GB Download
md5:998d9fed6d0141ccab43e6e75c871ad5
208 Bytes Preview Download
md5:3ae67f8ef0bf4fc2ef72986e4c51c84f
2.8 GB Download
md5:1cac03645297c2d08e9fc7a074ae17b8
132.1 kB Download