mBERT

mBERT is a mutation testing tool that uses CodeBERT, a pre-trained language model, to generate mutants.

Requirements

• Maven
• CodeBERT dependencies:
  • pip install torch
  • pip install transformers

Installation

1. Run mkdir -p pre-trained/codebert-base-mlm to create the folder where CodeBERT pre-trained model will be saved.
2. Run python3 download-codebert.py to download CodeBERT pre-trained model.
3. Try CodeBERT by running: python3 run-codebert.py "int <mask> = b;"

{'score': 0.23396340012550354, 'token': 740, 'token_str': 'c', 'sequence': 'int c= b;'}

{'score': 0.05450829118490219, 'token': 939, 'token_str': 'i', 'sequence': 'int i= b;'}

{'score': 0.05004948750138283, 'token': 741, 'token_str': 'b', 'sequence': 'int b= b;'}

{'score': 0.04164685681462288, 'token': 10, 'token_str': 'a', 'sequence': 'int a= b;'}

{'score': 0.023635799065232277, 'token': 181, 'token_str': 'p', 'sequence': 'int p= b;'}

4. Compile mBERT: mvn compile.
5. Done! Try mBERT by running: ./mBERT.sh

Executing mBERT

mBERT provides some flags that you can configure:

• -in=source_file_name
• -out=mutants_directory
• -N=max_num_of_mutants
• -m=method_name
• -m=method_name:method_definition_line
• -l=line_to_mutate

Compile Mutants Generated

You can use script compile-mutants.sh to compile the mutants generated by mBERT.

• Usage: ./compile-mutants.sh mutants_dir subject_name
• Information: After compiling the mutants, you will find the details in files mutants_dir/subject_name.csv and mutants_dir/subject_name.log
• Example: ./compile-mutants.sh examples/generated-mutants/gcd/ gcd

Examples

Forlder examples provide the examples discussed in the paper.

Inside examples/generated-mutants you can find the mutants generated by mBERT.