QueryFuzz implements a metamorphic testing approach to test Datalog engines.

Related tags

Deep LearningqueryFuzz
Overview

Python package Python application

Datalog is a popular query language with applications in several domains. Like any complex piece of software, Datalog engines may contain bugs. The most critical ones manifest as incorrect results when evaluating queries (query bugs). Given the wide applicability of the language, query bugs may have detrimental consequences, for instance, by compromising the soundness of a program analysis that is implemented and formalized in Datalog.

QueryFuzz implements the metamorphic testing approach for Datalog engines described in:

M. N. Mansur, M. Christakis, V. Wüstholz - Metamorphic Testing of Datalog Engines -
In Proceedings of the 29th Joint European Software Engineering Conference and Symposium on 
the Foundations of Software Engineering (ESEC/FSE'21).

Installation:

Ubuntu/Debian:

Support for C++17 is required, which is supported in g++ 7/clang++ 7 on.

sudo apt-get install autoconf automake bison build-essential clang doxygen flex g++ git libffi-dev libncurses5-dev libtool libsqlite3-dev make mcpp python sqlite zlib1g-dev
git clone https://github.com/numairmansur/queryFuzz
virtualenv --python=/usr/bin/python3.7 venv
source venv/bin/activate
cd queryFuzz
python setup.py install

Usage:

Testing Soufflé:

You can immediately start testing Soufflé by just typing the following command:

queryfuzz

When you run this command for the first time, it will download and install Soufflé. We use Soufflé as our backend tool to compare and find discrepancies in the results of two Datalog programs. After successfully installing Soufflé, the above command will start the fuzzing procedure on the latest revision of Soufflé.

If you want to test a different version of Soufflé, please build and install that version and paste the path to Soufflé executable in the path_to_souffle_engine field in file /path/to/queryFuzz/params.json.

Testing µZ:

If you want to run queryFuzz on µZ, please first build and install the appropriate version of z3. Then paste the path to z3 executable in the path_to_z3_engine field in file /path/to/queryFuzz/params.json. You can then begin the fuzzing procedure by running:

queryfuzz --engine=z3

Testing DDlog:

If you want to run queryFuzz on DDlog, please first build and install the appropriate version of DDlog. Then paste the path to DDlog executable in the path_to_ddlog_engine field in file /path/to/queryFuzz/params.json. You would also have to add path to DDlog home directory in the path_to_ddlog_home_dir field in /path/to/queryFuzz/params.json. You can then begin the fuzzing procedure by running:

queryfuzz --engine=ddlog

Want to test your own Datalog engine?

If you want to use QueryFuzz to test your own Datalog engine, please get in touch at [email protected].

Running on multiple cores:

If you wish to run parallel instances of Queryfuzz on n cores, use the --cores flag. For example:

queryfuzz --cores=n

Reproducing query bugs reported in our ESEC/FSE'21 paper:

Please follow the instructions here.

You might also like...
Implements MLP-Mixer: An all-MLP Architecture for Vision.
Implements MLP-Mixer: An all-MLP Architecture for Vision.

MLP-Mixer-CIFAR10 This repository implements MLP-Mixer as proposed in MLP-Mixer: An all-MLP Architecture for Vision. The paper introduces an all MLP (

Sayak Paul 51 Jan 4, 2023
This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of Coordinate Independent Convolutional Networks.
This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of Coordinate Independent Convolutional Networks.

Orientation independent Möbius CNNs This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of

Maurice Weiler 59 Dec 9, 2022
This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong Poisons
This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong Poisons

Adversarial poison generation and evaluation. This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong

null 31 Nov 1, 2022
Implements an infinite sum of poisson-weighted convolutions

An infinite sum of Poisson-weighted convolutions Kyle Cranmer, Aug 2018 If viewing on GitHub, this looks better with nbviewer: click here Consider a v

Kyle Cranmer 26 Dec 7, 2022
Recall Loss for Semantic Segmentation (This repo implements the paper: Recall Loss for Semantic Segmentation)
Recall Loss for Semantic Segmentation (This repo implements the paper: Recall Loss for Semantic Segmentation)

Recall Loss for Semantic Segmentation (This repo implements the paper: Recall Loss for Semantic Segmentation) Download Synthia dataset The model uses

null 32 Sep 21, 2022
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
FastReID is a research platform that implements state-of-the-art re-identification algorithms.

FastReID is a research platform that implements state-of-the-art re-identification algorithms.

JDAI-CV 2.8k Jan 7, 2023
A mini lib that implements several useful functions binding to PyTorch in C++.

Torch-gather A mini library that implements several useful functions binding to PyTorch in C++. What does gather do? Why do we need it? When dealing w

maxwellzh 8 Sep 7, 2022
This implements one of result networks from Large-scale evolution of image classifiers
This implements one of result networks from Large-scale evolution of image classifiers

Exotic structured image classifier This implements one of result networks from Large-scale evolution of image classifiers by Esteban Real, et. al. Req

null 54 Nov 25, 2022
Implements pytorch code for the Accelerated SGD algorithm.

AccSGD This is the code associated with Accelerated SGD algorithm used in the paper On the insufficiency of existing momentum schemes for Stochastic O

null 205 Jan 2, 2023
Releases(fse_repl)
Owner
Maria Christakis' research group at MPI-SWS
GitHub Repository
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales

IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales. In this case, we ended up using XGBoost because it was the o

1 Jan 04, 2022
*ObjDetApp* deploys a pytorch model for object detection

*ObjDetApp* deploys a pytorch model for object detection

Will Chao 1 Dec 26, 2021
a reccurrent neural netowrk that when trained on a peice of text and fed a starting prompt will write its on 250 character text using LSTM layers

RNN-Playwrite a reccurrent neural netowrk that when trained on a peice of text and fed a starting prompt will write its on 250 character text using LS

Arno Barton 1 Oct 29, 2021
PaSST: Efficient Training of Audio Transformers with Patchout

PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa

165 Dec 26, 2022
Selecting Parallel In-domain Sentences for Neural Machine Translation Using Monolingual Texts

DataSelection-NMT Selecting Parallel In-domain Sentences for Neural Machine Translation Using Monolingual Texts Quick update: The paper got accepted o

Javad Pourmostafa 6 Jan 07, 2023
MINERVA: An out-of-the-box GUI tool for offline deep reinforcement learning

MINERVA is an out-of-the-box GUI tool for offline deep reinforcement learning, designed for everyone including non-programmers to do reinforcement learning as a tool.

Takuma Seno 80 Nov 06, 2022
Food recognition model using convolutional neural network & computer vision

Food recognition model using convolutional neural network & computer vision. The goal is to match or beat the DeepFood Research Paper

Hemanth Chandran 1 Jan 13, 2022
AI pipelines for Nvidia Jetson Platform

Jetson Multicamera Pipelines Easy-to-use realtime CV/AI pipelines for Nvidia Jetson Platform. This project: Builds a typical multi-camera pipeline, i.

NVIDIA AI IOT 96 Dec 23, 2022
This is the repository of the NeurIPS 2021 paper "Curriculum Disentangled Recommendation withNoisy Multi-feedback"

Curriculum_disentangled_recommendation This is the repository of the NeurIPS 2021 paper "Curriculum Disentangled Recommendation with Noisy Multi-feedb

14 Dec 20, 2022
A Fast and Accurate One-Stage Approach to Visual Grounding, ICCV 2019 (Oral)

One-Stage Visual Grounding ***** New: Our recent work on One-stage VG is available at ReSC.***** A Fast and Accurate One-Stage Approach to Visual Grou

Zhengyuan Yang 118 Dec 05, 2022
Source code related to the article submitted to the International Conference on Computational Science ICCS 2022 in London

POTHER: Patch-Voted Deep Learning-based Chest X-ray Bias Analysis for COVID-19 Detection Source code related to the article submitted to the Internati

Tomasz Szczepański 1 Apr 29, 2022
Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

François Chollet 16.2k Dec 30, 2022
Privacy-Preserving Machine Learning (PPML) Tutorial Presented at PyConDE 2022

PPML: Machine Learning on Data you cannot see Repository for the tutorial on Privacy-Preserving Machine Learning (PPML) presented at PyConDE 2022 Abst

Valerio Maggio 10 Aug 16, 2022
Automated detection of anomalous exoplanet transits in light curve data.

Automatically detecting anomalous exoplanet transits This repository contains the source code for the paper "Automatically detecting anomalous exoplan

1 Feb 01, 2022
This is the implementation of the paper "Self-supervised Outdoor Scene Relighting"

Self-supervised Outdoor Scene Relighting This is the implementation of the paper "Self-supervised Outdoor Scene Relighting". The model is implemented

Ye Yu 24 Dec 17, 2022
Code for ACL 2019 Paper: "COMET: Commonsense Transformers for Automatic Knowledge Graph Construction"

To run a generation experiment (either conceptnet or atomic), follow these instructions: First Steps First clone, the repo: git clone https://github.c

Antoine Bosselut 575 Jan 01, 2023
Get a Grip! - A robotic system for remote clinical environments.

Get a Grip! Within clinical environments, sterilization is an essential procedure for disinfecting surgical and medical instruments. For our engineeri

Jay Sharma 1 Jan 05, 2022
This project is a loose implementation of paper "Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach"

Stock Market Buy/Sell/Hold prediction Using convolutional Neural Network This repo is an attempt to implement the research paper titled "Algorithmic F

Asutosh Nayak 136 Dec 28, 2022
Adabelief-Optimizer - Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"

AdaBelief Optimizer NeurIPS 2020 Spotlight, trains fast as Adam, generalizes well as SGD, and is stable to train GANs. Release of package We have rele

Juntang Zhuang 998 Dec 29, 2022
Intrusion Detection System using ensemble learning (machine learning)

IDS-ML implementation of an intrusion detection system using ensemble machine learning methods Data set This project is carried out using the UNSW-15

4 Nov 25, 2022