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AxProf

A framework for accuracy profiling of randomized approximate algorithm implementations. See ICSE-2019-Paper.pdf for a full description of AxProf (to appear in ICSE 2019).

Directory structure

  • AxProf contains the source of AxProf.
  • AxProf/checkerGen contains the checker function generator component of AxProf.
  • tutorial contains a tutorial script that uses AxProf.
  • examples contains example scripts for testing some of the benchmarks from the conference paper.

Setup

First, install the required dependencies. Assuming your system is running Ubuntu 20.04 and Python 3.8, run the following commands:

sudo apt update
sudo apt install build-essential default-jdk python3-pip
sudo python3 -m pip install numpy==1.24.3 scipy==1.10.1 matplotlib==3.7.1 minepy==1.2.6

Note that newer versions of Python 3 (e.g., 3.11) may not support AxProf. Use pyenv if necessary to run AxProf in a Python 3.8 environment. Next, run the following commands from the root directory of this repository:

cd AxProf/checkerGen
make

Tutorial

A tutorial for using AxProf is available in tutorial/tutorial.py.

Example

An example script for testing ekzhu/datasketch is provided in examples/hllEkzhu.py. To run the script, you must first clone the datasketch repository. Run the following commands from the root directory of this repository:

cd examples
git clone https://github.com/ekzhu/datasketch.git

Now you can run examples/hllEkzhu.py to test the library.