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cppminer produces a code2seq compatible datasets from C++ code bases.

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cppminer

cppminer produces a code2seq compatible datasets from C++ code bases.

Experimental C++ dataset mined from the Chromium project sources.

This tool consists from three scripts which should be run consistently.

1. Miner

The miner.py is the main utility which traverse c++ sources, parse them and produce raw dataset files.

It has following command line interface:

usage: miner.py [-h] [-c contexts-number] [-l path-length] [-d ast-depth] [-p processes-number] [-e libclang-path] path out

positional arguments:
  path                  the path sources directory
  out                   the output path

optional arguments:
  -h, --help            show this help message and exit
  -c contexts-number, --max_contexts_num contexts-number
                        maximum number of contexts per sample
  -l path-length, --max_path_len path-length
                        maximum path length (0 - no limit)
  -d ast-depth, --max_ast_depth ast-depth
                        maximum depth of AST (0 - no limit)
  -p processes-number, --processes_num processes-number
                        number of parallel processes
  -e libclang-path, --libclang libclang-path
                        path to libclang.so file

The input path is traversed recursively and all files with following extensions c, cc, cpp are parsed. It is recommended to use the c++ compilation database which provides all required compilation flags for project files.

These files have following format:

  • Each row is an example.

  • Each example is a space-delimited list of fields, where:

    1. The first field is the target label, internally delimited by the "|" character (for example: compare|ignore|case)
    2. Each of the following field are contexts, where each context has three components separated by commas (","). None of these components can include spaces nor commas.

Context's components are a token, a path, and another token.

Each token component is a token in the code, split to subtokens using the "|" character.

Each path is a path between two tokens, split to path nodes using the "|" character. Example for a context:

my|key,StringExression|MethodCall|Name,get|value

Here my|key and get|value are tokens, and StringExression|MethodCall|Name is the syntactic path that connects them.

2. Merge

The merge.py is the utility which concatenates all raw file, shuffles them and produce three files dataset.train.c2s, dataset.test.c2s and dataset.val.c2s into the given directory. Also it can clean source files after merging. The important settings is the map_file_size which defines the size of the database file used for merging, you should increase default value of 6Gb for large datasets.

It has following command line interface:

usage: merge.py [-h] [-c clear_resources_flag] [-m map_file_size] path

merge resources generated by cppminer to a code2seq dataset

positional arguments:
  path                  the dataset sources path

optional arguments:
  -h, --help            show this help message and exit
  -c clear_resources_flag, --clear_resources clear_resources_flag
                        if True clear resource files
  -m map_file_size, --map_size map_file_size
                        size of the DB file, default(6442450944 bytes)

3. Code2vec preprocess

The third utility is the preprocess.sh from the code2seq folder, this is modified script from the original project which generates dataset in format suitable for the code2seq model. in general it creates new files with truncated and padded number of paths for each example.

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cppminer produces a code2seq compatible datasets from C++ code bases.

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