This repository works with genetic programming to optimize metrics for code2vec method name prediction. For more information on the goals, concept and workflow refer to the overview
Make sure to clone with recursion:
git clone --recursive -j8 https://github.com/wubero/Guided-MT-Code2Vec.gitYou will also need a working Code2Vec Model, you find information In the Code2Vec-Readme.
And you need .java-files. We provide example-files via:
unzip Resources/minimal-sample-data.zip -d ./code2vecTo build the project, simply do:
mvn clean package verifyWe recommend to use Docker via:
docker-compose up --buildThis should run everything with a simple configuration.
It's highly recommended that new users start by looking at both other projects that are used here, code2vec and Lampion. Code2Vec is used for evaluating its trained model, besides that the Lampion project is used for the Java metamorphic transformers.
To get started with the project you
- Download a trained code2vec model
- Adjust paths and dataset names in preprocess.sh
- Adjust paths and dataset in PipelineSupport.java
- As a dataset you can you use the provided one in ./code2vec/data, or you can download your own. (The next sections describes how this projects got its test datasets.)
- If you do download your own dataset there might occur errors with the spoon library. These can be resolved by running the EditData.py script
For the datasets used in our experiments we randomly selected 30 from the java-small dataset provided by code2vec through the following link:
wget https://s3.amazonaws.com/code2vec/data/java-small_data.tar.gzAs mentioned the dataset we used is provided in ./code2vec/data. However, you can also generate your own random dataset by executing the file_picker.sh script located in ./scripts. To do this only the directory and target paths need to be changed.
- Maven
- Jdk 17
- Python 3.9
If the bash commands in the program are not working you might need to adjust the file endings of the shell scripts in the code2vec folder. You can do this by running the dos2unix command in something like git bash. This will readjust the file endings and make sure that the docker build runs smoothly.
If the project doesn't work consider any of the problems below before opening an issue on GitHub.
- Code2vec is missing from the repository because it wasn't cloned recursively.
- The Lampion core is missing. If you're running it locally it might mean that you don't have it build with the correct version or don't have it locally at all. To fix this, clone the Lampion repository and build it with the correct version. This should fix the problem.
There are two experiment folders for this project. These are the Experiments and Experiments_random folders. The Experiments folder uses the genetic algorithm and runs its respective configurations on it. The Experiments_random folder does the same with the random algorithm. There is a README.md in the Experiments folder that explains how to further run the experiments.
The experiments are designed to answer the problem mentioned in the problem introduction. The genetic algorithm and random algorithm are compared with each other through these experiments.
The scripts folder is used to pick the files for the dataset, as mentioned above under Dataset. It also has a python file that parses the experiments to csv files and creates the plots used in the thesis. There are multiple method in there with comments above for what they do. You can comment out the respective methods if you don't want them to run.