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Refining Fitness Functions for Searched-Based Program Repair

This repository contains the experiment scripts of the "Refining Fitness Functions for Searched-Based Program Repair" paper by Zhiqiang Bian, Aymeric Blot and Justyna Petke. The Gin repository used for this experiment is https://github.com/SOLAR-group/apr2021gin.

quixbugs

We use quixbugs dataset as the benchmark. quixbugs/ contains the refactored quixbugs java classes that suit our experiment scripts.

Get started

All data will be generated under output/<timestamp> folder.

  1. Update the config.py to configure the experiments.
  2. Execute fix.py to start the program repair process. Gin outputs will be generated and stored at /results/.
  3. Execute analyze.py to start the analysis. /analysis.csv will be generated. The fixed patches will be stored at /fixed_patches/.
  4. Execute integrate.py to generate integrated results for all experiments. /result.csv will be generated.
  5. Execute collect_all_edits.py and then compute_uniqueness.py to check the uniqueness of the fixed patches. /edits.csv and /uniqueness.csv will be generated.
  6. Execute collect_all_fitness.py and then compute_plateau.py to check the diversities of the fitness values. /fitness.csv and /plateaus.csvwill be generated.