anonymou123dl/dlanalysis

This repo contains the dataset and the implementation of the NeuralState analysis paper.

Please read below to understand repo Organization:

In the paper, we use two benchmarks:
- The first benchmark we used from NeuraLint can be found under the director name Benchmark1/SOSamples
- The second benchmark we used from Humbatova et al. can be found under the director name Benchmark2/SOSamples

To reproduce the results in the paper:
- Download the NeuralStateAnalysis Zip file.
- Extract the file and go to the NeuralStateAnlaysis directory.
- ( Optional ) Install the requirements by running 'Pip install requirements.txt.' N.B: The requirements.txt file is already in this repo.
- To run NeuralState on Benchmark1:
- Go to Benchmark1/SOSamples directory,
- Open any of the programs you want to run,
- Set the path: Path-to-folder/NeuralStateAnalysis/
- Then, do 'python program_id.' Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you'll be able to reproduce results.
- To run NeuralState on Benchmark2:
- Go to Benchmark1/SOSamples directory,
- Open any of the programs you want to run,
- Set the path: Path-to-folder/NeuralStateAnalysis/
- Then, do 'python program_id.' Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you'll be able to reproduce results.
- To reproduce RQ4:
- Go to the RQ4 directory,
- Open any of the programs you want to run,
- Set the path: Path-to-folder/NeuralStateAnalysis/
- Then, do 'python program_id.' Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you'll be able to reproduce results.
- To reproduce Motivating Example results:
- Go to the RQ4 directory,
- Open MotivatingExample.py,
- Set the path: Path-to-folder/NeuralStateAnalysis/
- Then, do 'python program_id.' Since the 'NeuralStateAnalysis(model).debug()' call is already present in all programs, you'll be able to reproduce results.
- To reproduce Motivating Example results:
- Go to the program,
- Add path to NeuralStateAnlaysis folder,
- Add 'NeuralStateAnalysis(model_name).debug().'
- Then, do 'python program_id.'

原始信息汇总

数据集概述

数据集内容

• 该数据集包含两个基准数据：
  • 第一个基准数据来自NeuraLint，位于目录Benchmark1/SOSamples下。
  • 第二个基准数据来自Humbatova et al.，位于目录Benchmark2/SOSamples下。

数据集使用

• 为了复现论文中的结果，需要执行以下步骤：
  • 下载NeuralStateAnalysis压缩文件并解压。
  • 进入NeuralStateAnalysis目录。
  • （可选）通过运行pip install requirements.txt安装依赖。

复现Benchmark1结果

• 进入Benchmark1/SOSamples目录。
• 打开任意一个程序文件。
• 设置路径为Path-to-folder/NeuralStateAnalysis/。
• 运行python program_id，因为所有程序中已包含NeuralStateAnalysis(model).debug()调用，可以复现结果。

复现Benchmark2结果

• 进入Benchmark2/SOSamples目录。
• 打开任意一个程序文件。
• 设置路径为Path-to-folder/NeuralStateAnalysis/。
• 运行python program_id，因为所有程序中已包含NeuralStateAnalysis(model).debug()调用，可以复现结果。

复现RQ4结果

• 进入RQ4目录。
• 打开任意一个程序文件。
• 设置路径为Path-to-folder/NeuralStateAnalysis/。
• 运行python program_id，因为所有程序中已包含NeuralStateAnalysis(model).debug()调用，可以复现结果。

复现Motivating Example结果

• 进入RQ4目录。
• 打开MotivatingExample.py文件。
• 设置路径为Path-to-folder/NeuralStateAnalysis/。
• 运行python program_id，因为所有程序中已包含NeuralStateAnalysis(model).debug()调用，可以复现结果。