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Replication Package: Leveraging Large Language Models for Enhancing the Understandability of Generated Unit Tests

This is the replication package for the research project "Leveraging Large Language Models for Enhancing the Understandability of Generated Unit Tests". This guide will walk you through setting up and using the tools involved in our study, including a LLM server and the UTGen client.

Getting Started

This section provides instructions on how to prepare your environment for running the tools used in our research.

Prerequisites

  • Docker
  • Python 3.6 or newer
  • Java Development Kit (JDK) versions 8 and 11

Clone the Repository

To begin, clone this repository to your local machine and unzip all relevant files within.

git clone <repository-url>
cd <repository-folder>
cd LLM-Server
unzip LLM-server.zip

Setting Up the LLM Server

1. Install Docker: Ensure Docker is installed on your machine. Docker installation guides are available here

2. Run ollama as a Docker Container: Follow the official ollama Docker image guide to install and run ollama.

3. Create a Python Virtual Environment:

python -m venv .env
source .env/bin/activate

4. Install Requirements:

pip install -r requirements.txt

5. Start the Server:

./run-server

Setting Up UTGen

1. Install Java Versions: Use SDKMAN to install the required Java versions.

2. Prepare classes.csv: Ensure the target directory for UTGen contains a classes.csv file with project and class headers.

3. Project Requirements: Each project should contain at least the following structure

  • A .jar file of the project.
  • An evosuite-files directory with:
    • evosuite.properties file.
    • inheritance.xml.gz file.
  • A lib directory with all dependent libraries

4. Run UTGen:

./run-utestgen.sh <DIR-PATH> <JAVA-VERSION: 8 OR 11> <USE-INHERITANCE: true OR false>