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bug-localization

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

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

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
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    DOI references
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    Academic publication links
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (10.5%) to scientific vocabulary

Keywords

bug-localization bug-reports dataset paper textual-analysis
Last synced: 6 months ago · JSON representation ·

Repository

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

Basic Info
Statistics
  • Stars: 23
  • Watchers: 1
  • Forks: 14
  • Open Issues: 1
  • Releases: 0
Topics
bug-localization bug-reports dataset paper textual-analysis
Created over 8 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

How to Run

  1. Install Python 3.10 and clone this repository:

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

  2. Create a venv and install the dependencies:

    bash cd bug-localization python -m venv .venv .venv/Scripts/activate python -m pip install -U pip setuptools pip install -r requirements.txt

    Also, download and install the spaCy's en_core_web_lg pretrained model (You can download its whl file directly from GitHub releases) and NLTK data. From NLTK, only punkt and averaged_perceptron_tagger are needed that can be downloaded using NLTK Downloader GUI or a Python interpreter:

    ```python

    import nltk nltk.download('punkt') nltk.download('averagedperceptrontagger') ```

  3. Download the datasets file from here, and unzip it in the root directory of the cloned repository. You can also download these datasets from the BugLocator and BRTracer repositories. More datasets can be downloaded from the Bench4BL repository.

  4. Check the path of datasets in buglocalizer/datasets.py module and change the value of the DATASET variable to choose different datasets (default values can be aspectj, swt, and zxing, but you can add more).

    Run the main module:

    bash python buglocalizer/main.py

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

Owner

  • Name: Reza Gharibi
  • Login: h4iku
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Gharibi
  given-names: Reza
  orcid: https://orcid.org/0000-0001-6596-3658
- family-names: Rasekh
  given-names: Amir Hossein
- family-names: Sadreddini
  given-names: Mohammad Hadi
- family-names: Fakhrahmad
  given-names: Seyed Mostafa
title: "Leveraging textual properties of bug reports to localize relevant source files"
doi: 10.1016/j.ipm.2018.07.004
repository-code: https://github.com/h4iku/bug-localization
preferred-citation:
  type: article
  authors:
  - family-names: Gharibi
    given-names: Reza
    orcid: https://orcid.org/0000-0001-6596-3658
  - family-names: Rasekh
    given-names: Amir Hossein
  - family-names: Sadreddini
    given-names: Mohammad Hadi
  - family-names: Fakhrahmad
    given-names: Seyed Mostafa
  doi: 10.1016/j.ipm.2018.07.004
  journal: "Information Processing & Management"
  month: 11
  start: 1058
  end: 1076
  title: "Leveraging textual properties of bug reports to localize relevant source files"
  issue: 6
  volume: 54
  year: 2018
  url: https://www.sciencedirect.com/science/article/pii/S0306457318301092

GitHub Events

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Dependencies

requirements.txt pypi
  • Pygments ==2.12.0
  • inflection ==0.5.1
  • javalang ==0.13.0
  • nltk ==3.7
  • numpy ==1.22.3
  • scikit-learn ==1.0.2
  • scipy ==1.8.0
  • spacy ==3.2.4
  • xmltodict ==0.12.0