QueryFuzz implements a metamorphic testing approach to test Datalog engines.

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 (

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

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

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

 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

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.

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

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

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

Releases(fse_repl)
Owner
Maria Christakis' research group at MPI-SWS
AITUS - An atomatic notr maker for CYTUS

AITUS an automatic note maker for CYTUS. 利用AI根据指定乐曲生成CYTUS游戏谱面。 效果展示:https://www

GradiusTwinbee 6 Feb 24, 2022
KDD CUP 2020 Automatic Graph Representation Learning: 1st Place Solution

KDD CUP 2020: AutoGraph Team: aister Members: Jianqiang Huang, Xingyuan Tang, Mingjian Chen, Jin Xu, Bohang Zheng, Yi Qi, Ke Hu, Jun Lei Team Introduc

96 May 30, 2022
PSTR: End-to-End One-Step Person Search With Transformers (CVPR2022)

PSTR (CVPR2022) This code is an official implementation of "PSTR: End-to-End One-Step Person Search With Transformers (CVPR2022)". End-to-end one-step

Jiale Cao 28 Dec 13, 2022
Unofficial implementation of the paper: PonderNet: Learning to Ponder in TensorFlow

PonderNet-TensorFlow This is an Unofficial Implementation of the paper: PonderNet: Learning to Ponder in TensorFlow. Official PyTorch Implementation:

1 Oct 23, 2022
An implementation of based on pytorch and mmcv

FisherPruning-Pytorch An implementation of Group Fisher Pruning for Practical Network Compression based on pytorch and mmcv Main Functions Pruning f

Peng Lu 15 Dec 17, 2022
A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval

CLIP4CMR A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval The original data and pre-calculate

24 Dec 26, 2022
Styled text-to-drawing synthesis method. Featured at the 2021 NeurIPS Workshop on Machine Learning for Creativity and Design

Styled text-to-drawing synthesis method. Featured at the 2021 NeurIPS Workshop on Machine Learning for Creativity and Design

Peter Schaldenbrand 247 Dec 23, 2022
Backend code to use MCPI's python API to make infinite worlds with custom generation

inf-mcpi Backend code to use MCPI's python API to make infinite worlds with custom generation Does not save player-placed blocks! Generation is still

5 Oct 04, 2022
Algorithm to texture 3D reconstructions from multi-view stereo images

MVS-Texturing Welcome to our project that textures 3D reconstructions from images. This project focuses on 3D reconstructions generated using structur

Nils Moehrle 766 Jan 04, 2023
Implementation of the state of the art beat-detection, downbeat-detection and tempo-estimation model

The ISMIR 2020 Beat Detection, Downbeat Detection and Tempo Estimation Model Implementation. This is an implementation in TensorFlow to implement the

Koen van den Brink 1 Nov 12, 2021
Bayesian algorithm execution (BAX)

Bayesian Algorithm Execution (BAX) Code for the paper: Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mut

Willie Neiswanger 38 Dec 08, 2022
Fast image augmentation library and an easy-to-use wrapper around other libraries

Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc

11.4k Jan 09, 2023
Self-Supervised Multi-Frame Monocular Scene Flow (CVPR 2021)

Self-Supervised Multi-Frame Monocular Scene Flow 3D visualization of estimated depth and scene flow (overlayed with input image) from temporally conse

Visual Inference Lab @TU Darmstadt 85 Dec 22, 2022
This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Con

401 Dec 16, 2022
Deep Learning Datasets Maker is a QGIS plugin to make datasets creation easier for raster and vector data.

Deep Learning Dataset Maker Deep Learning Datasets Maker is a QGIS plugin to make datasets creation easier for raster and vector data. How to use Down

deepbands 25 Dec 15, 2022
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod

20.5k Jan 08, 2023
A Dying Light 2 (DL2) PAKFile Utility for Modders and Mod Makers.

Dying Light 2 PAKFile Utility A Dying Light 2 (DL2) PAKFile Utility for Modders and Mod Makers. This tool aims to make PAKFile (.pak files) modding a

RHQ Online 12 Aug 26, 2022
Godot RL Agents is a fully Open Source packages that allows video game creators

Godot RL Agents The Godot RL Agents is a fully Open Source packages that allows video game creators, AI researchers and hobbiest the opportunity to le

Edward Beeching 326 Dec 30, 2022
Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight

Second-order Neural ODE Optimizer (NeurIPS 2021 Spotlight) [arXiv] ✔️ faster convergence in wall-clock time | ✔️ O(1) memory cost | ✔️ better test-tim

Guan-Horng Liu 39 Oct 22, 2022
Fashion Landmark Estimation with HRNet

HRNet for Fashion Landmark Estimation (Modified from deep-high-resolution-net.pytorch) Introduction This code applies the HRNet (Deep High-Resolution

SVIP Lab 91 Dec 26, 2022