• I. Introduction of IFixR
• II. Environment setup
• III. Run Step-by-Step
• IV. Evaluation Result
• V. Generated Patches
• VI. Structure of the project

IFixR a patch generation system for user-reported bugs

• OS: macOS Mojave (10.14.3)
• JDK7: Oracle jdk1.7 (important!)
• JDK8: Oracle jdk1.8 (important!)
• Defects4J: Clone and configure defects4j from its original repository

  git clone https://github.com/rjust/defects4j
  cd defects4j
  ./init.sh

• Download and configure Anaconda
• Create an python environment using the environment file

  conda env create -f environment.yml

• Update config file with corresponding user paths.

  Defects4J home path requires '/' at the end
  Example: /Users/projects/defects4j/

• Active the conda environment from shell

  source activate python36

• Launch startPy as follows:

  bash startPy.sh [OPTIONS]

IFixR needs three input options for running.

Usage: bash startPy.sh $1 $2 $3
where $1 is root
      $2 is job
      $3 is subject

• root : The full path of directory where startPy.sh is located

• subject : the project name of buggy program of benchmark. (MATH,LANG are expected values but can be specific for job)

• job : the name of the job in the pipeline , supports multiple steps which needs to executed in order:

  1.clone : Clone target project repository.

    Example: bash startPy.sh /home/user/mimic clone MATH
    Example: bash startPy.sh /home/user/mimic clone LANG

  2.collect : Collect all commit from repository.

    Example: bash startPy.sh /home/user/mimic collect MATH
    Example: bash startPy.sh /home/user/mimic collect LANG

  3.fix : Collect commits linked to a bug report.

    Example: bash startPy.sh /home/user/mimic fix MATH
    Example: bash startPy.sh /home/user/mimic fix LANG

  4.bugPoints : Identify the snapshot of the repository before the bug fixing commit introduced.

    Example: bash startPy.sh /home/user/mimic bugPoints MATH
    Example: bash startPy.sh /home/user/mimic bugPoints LANG

  5.brDownload : Download bug reports recovered from commit log

    Example: bash startPy.sh /home/user/mimic brDownload MATH
    Example: bash startPy.sh /home/user/mimic brDownload LANG

  6.brParser : Parse bug reports to select the bug report where type labeled as BUG and status as RESOLVED or CLOSED

    Example: bash startPy.sh /home/user/mimic brParser MATH
    Example: bash startPy.sh /home/user/mimic brParser LANG

  7.brFeatures : Extract bug report features

    Example: bash startPy.sh /home/user/mimic brFeatures MATH
    Example: bash startPy.sh /home/user/mimic brFeatures LANG

  8.verify : Extract source code features

    Example: bash startPy.sh /home/user/mimic verify MATH
    Example: bash startPy.sh /home/user/mimic verify LANG

  9.simi : Compute the similarity between bug reports and source code features

    Example: bash startPy.sh /home/user/mimic simi MATH
    Example: bash startPy.sh /home/user/mimic simi LANG

  10.features : Compute the features from similarity scores

    Example: bash startPy.sh /home/user/mimic features MATH
    Example: bash startPy.sh /home/user/mimic features LANG

  11.predict : Predict file level bug localization

    Example: bash startPy.sh /home/user/mimic predict ALL

  12.eval : Retrieve predictions for all bug reports and suspiciousness scores of files.

    Example: bash startPy.sh /home/user/mimic eval ALL

  13.stmt : Compute statement level bug localization

    Example: bash startPy.sh /home/user/mimic stmt ALL (!!! Clones all defects4j bugs and compile, may take significant amount of time)

  14.gv : Execute generate-validation step to produce patch candidates.

    Execute generate-validation step on a single defects4j bug (eg Lang_15, Math_34 case sensitive)
    
      Example: bash startPy.sh /home/user/mimic gv Math_34
    
    Execute generate-validation step on all dataset. (!!! Takes significant amount of time !!!)
    
      Example: bash startPy.sh /home/user/mimic gv ALL

The data provided with replication package is listed in directory data The data is stored in different formats. (e.g. pickle, db, csv, etc..)

The see content of the .pickle file the following script could be used.

 import pickle as p
 import gzip
 def load_zipped_pickle(filename):
    with gzip.open(filename, 'rb') as f:
        loaded_object = p.load(f)
        return loaded_object

Usage

result = load_zipped_pickle('code/LANGbugReportsComplete.pickle')
# Result is pandas object which can be exported to several formats
# Details on how to export is listed in offical library documentation
# https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html

MIMIC generates genuine/ plausible patches for 21/44 Defects4J bugs with its IR-based bug localizer.

  |--- README.md                    :  user guidance
  |--- code                         :  code
  |--- data                         :  replication data
  |--- doc                          :  document
  |--- OUTPUT/MIMIC/FixedBugs       :  generated patches