/code-snippets-dataset

Dataset builder for Code Snippets Dataset

Primary LanguagePython

code-snippets-dataset

Dataset builder for Code Snippets Dataset

Prerequisites

  1. Make sure that you have Java installed (suggested version jdk-11.0.2)
  2. Download and extract the SourceMeter tool from this website
  3. Download and extract the Readability tool from this website (direct link available here)
  4. Download and extract the CodeSearchNet Java corpus snippets from this repo (direct link available here)
  5. Edit file properties.py to set the path of Java, the path to SourceMeterJava.exe and rsm.jar, the path to the dataset, the path of the results folder, and a directory to be used as temporary directory.

Building the dataset

  1. Execute the script 1_run_all_metrics.py and the results folder will be populated with the metrics in CSV format.
  2. Execute the script 2_run_asts.py in order to create the files that contain the AST representations within the results folder.
  3. Execute the script 3_preclustering.py to split the code snippets into smaller groups, with respect to their cyclomatic complexity and number of operators.
  4. Execute the script 4_distance_matrices.py, which calculates the distance matrices between the snippets of each file and stores the results.
  5. Execute the script 5_clustering.py in order to make use of the generate distance matrices and perform the hierarchical clustering.

Migrating to MongoDB

  1. Create the file mongo/.env based on the file mongo/.env.sample to set the MongoDB uri and the path to the results folder, the path to the dataset, the path to the ASTs folder and the path to the generated clusters folder.
  2. Execute the nodejs script mongo/upload-metrics.js in order to parse all the generated files of the analysis and migrate the results to a MongoDB instance.