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
The pytorch implementation of the paper "text-guided neural image inpainting" at MM'2020

TDANet: Text-Guided Neural Image Inpainting, MM'2020 (Oral) MM | ArXiv This repository implements the paper "Text-Guided Neural Image Inpainting" by L

LisaiZhang 75 Dec 22, 2022
某学校选课系统GIF验证码数据集 + Baseline模型 + 上下游相关工具

elective-dataset-2021spring 某学校2021春季选课系统GIF验证码数据集（29338张） + 准确率98.4%的Baseline模型 + 上下游相关工具。 数据集采用 知识共享署名-非商业性使用 4.0 国际许可协议 进行许可。 Baseline模型和上下游相关工具采用

xmcp 27 Sep 17, 2021
Block Sparse movement pruning

Movement Pruning: Adaptive Sparsity by Fine-Tuning Magnitude pruning is a widely used strategy for reducing model size in pure supervised learning; ho

Hugging Face 54 Dec 20, 2022
CVPR 2021 - Official code repository for the paper: On Self-Contact and Human Pose.

selfcontact This repo is part of our project: On Self-Contact and Human Pose. [Project Page] [Paper] [MPI Project Page] It includes the main function

Lea Müller 68 Dec 06, 2022
Code for Massive-scale Decoding for Text Generation using Lattices

Massive-scale Decoding for Text Generation using Lattices Jiacheng Xu, Greg Durrett TL;DR: a new search algorithm to construct lattices encoding many

Jiacheng Xu 37 Dec 18, 2022
[ICLR2021oral] Rethinking Architecture Selection in Differentiable NAS

DARTS-PT Code accompanying the paper ICLR'2021: Rethinking Architecture Selection in Differentiable NAS Ruochen Wang, Minhao Cheng, Xiangning Chen, Xi

Ruochen Wang 86 Dec 27, 2022
A GUI to automatically create a TOPAS-readable MLC simulation file

Python script to create a TOPAS-readable simulation file descriring a Multi-Leaf-Collimator. Builds the MLC using the data from a 3D .stl file.

Sebastian Schäfer 0 Jun 19, 2022
This is the offical website for paper ''Category-consistent deep network learning for accurate vehicle logo recognition''

The Pytorch Implementation of Category-consistent deep network learning for accurate vehicle logo recognition This is the offical website for paper ''

Wanglong Lu 28 Oct 29, 2022
Disentangled Lifespan Face Synthesis

Disentangled Lifespan Face Synthesis Project Page | Paper Demo on Colab Preparation Please follow this github to prepare the environments and dataset.

何森 50 Sep 20, 2022
Turning SymPy expressions into PyTorch modules.

sympytorch A micro-library as a convenience for turning SymPy expressions into PyTorch Modules. All SymPy floats become trainable parameters. All SymP

Patrick Kidger 89 Dec 13, 2022
A library to inspect itermediate layers of PyTorch models.

A library to inspect itermediate layers of PyTorch models. Why? It's often the case that we want to inspect intermediate layers of a model without mod

archinet.ai 380 Dec 28, 2022
PyoMyo - Python Opensource Myo library

PyoMyo Python module for the Thalmic Labs Myo armband. Cross platform and multithreaded and works without the Myo SDK. pip install pyomyo Documentati

PerlinWarp 81 Jan 08, 2023
Awesome-AI-books - Some awesome AI related books and pdfs for learning and downloading

Awesome AI books Some awesome AI related books and pdfs for downloading and learning. Preface This repo only used for learning, do not use in business

luckyzhou 1k Jan 01, 2023
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain

Unity Technologies 187 Dec 24, 2022
[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

Anycost GAN video | paper | website Anycost GANs for Interactive Image Synthesis and Editing Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zh

MIT HAN Lab 726 Dec 28, 2022
TransCD: Scene Change Detection via Transformer-based Architecture

TransCD: Scene Change Detection via Transformer-based Architecture

wangzhixue 29 Dec 11, 2022
Official repository of "DeepMIH: Deep Invertible Network for Multiple Image Hiding", TPAMI 2022.

DeepMIH: Deep Invertible Network for Multiple Image Hiding (TPAMI 2022) This repo is the official code for DeepMIH: Deep Invertible Network for Multip

Junpeng Jing 67 Nov 22, 2022
A set of tools for converting a darknet dataset to COCO format working with YOLOX

darknet格式数据→COCO darknet训练数据目录结构（详情参见dataset/darknet）： darknet ├── class.names ├── gen_config.data ├── gen_train.txt ├── gen_valid.txt └── images

RapidAI-NG 148 Jan 03, 2023
DimReductionClustering - Dimensionality Reduction + Clustering + Unsupervised Score Metrics

Dimensionality Reduction + Clustering + Unsupervised Score Metrics Introduction

11 Nov 15, 2022
Implementation of Change-Based Exploration Transfer (C-BET)

Implementation of Change-Based Exploration Transfer (C-BET), as presented in Interesting Object, Curious Agent: Learning Task-Agnostic Exploration.

Simone Parisi 29 Dec 04, 2022