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Description
We can split our tasks to the following Task of d6tflow
framework
Task1 -> open Java file with correct encoding
Task2 -> remove all spaces and comments in it and save to another file
Task3 -> open file, find all method which can be inlined. Save target, extracted, full_ast, text_file, filename, row_csv from Task2
Task4 -> Task3 get target, extracted and filter it. Save target, extracted, full_ast, text_file, filename, row_csv from Task3
Task5 -> get result from Task3 and filter limited cases. Save target, extracted, full_ast, text_file, filename, row_csv from Task4
Task6 -> Inline Method, save file, row_csv
Task 7 -> save row_csv to global DataFrame
Possible problems:
- We have to save our
preprocessed
files to external memory, since we will have lots of files and it won't have enough memory to keep them in cache. Also, we have to keep them also in external memory since, it's our dataset which will be validated.
Seems, it cannot be done due to Reconfigure save() option to point to external store d6t/d6tflow#6 - We need to save different types of objects: ast tree, text. Seems, it's difficult:
Support for Tasks that outputs different types and other extensions... d6t/d6tflow#26
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