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Source code of the paper "Leveraging textual properties of bug reports to localize relevant source files"

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How to run:

  1. Install Python 3.6+ and required dependencies:

    pip install xmltodict javalang pygments inflection nltk numpy scipy scikit-learn spacy
    

    Also, download and install the GloVe word vectors en_vectors_web_lg for spaCy and NLTK data.

  2. Clone this repository:

    git clone https://github.com/h4iku/bug-localization.git
    

    Download the datasets file from here, and unzip it in the root directory of the cloned repository.

  3. Check the path of datasets in the datasets.py module and change the value of the DATASET variable to choose different datasets (values can be aspectj, swt, and zxing). Run the main module:

    python main.py
    

    All the modules are also independently runnable if it was needed to run them one by one.

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Source code of the paper "Leveraging textual properties of bug reports to localize relevant source files"

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