Implementation of "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing".

Overview

DeepOrder

License: GPL v3

Implementation of DeepOrder for the paper "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing".

Installation

Clone the GitHub repository and install the dependencies.

  1. Clone the repo and go to the directory
$ git clone https://github.com/T3AS/DeepOrder-ICSME21/DeepOrder.git
$ cd DeepOrder

  1. Install Anaconda (for creating and activating a separate environment)
  2. Run:
$ conda create -n DeepOrder python==3.6
$ conda activate DeepOrder
  1. Inside the enviroment, run:
$ pip install -r requirements.txt

Instructions

Download the datasets from here.

There are 4 python scripts leading to 4 separate models of DeepOrder on their datasets respectively.

For running all the scripts together use:


$ ./scripts_all.sh

For extra visualization presented in the paper, run:


$ python Extra_Visualizations/APFD_NAPFD_test_history/Effect_of_test_history_APFD_NAPFD.py
$ python Extra_Visualizations/Comparison_with_RETECS/DeepOrder_Vs_RETECS.py

Citing

@INPROCEEDINGS{sharif2021deeporder,
  author    = {Sharif, Aizaz and Marijan, Dusica and Liaaen, Marius},
  title     = {DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing},
  journal   = {ICSME},
  year      = {2021},
}
Bu repo SAHI uygulamasını mantığını öğreniyoruz.

SAHI-Learn: SAHI'den Beraber Kodlamak İster Misiniz Herkese merhabalar ben Kadir Nar. SAHI kütüphanesine gönüllü geliştiriciyim. Bu repo SAHI kütüphan

Kadir Nar 11 Aug 22, 2022
Yolact-keras实例分割模型在keras当中的实现

Yolact-keras实例分割模型在keras当中的实现 目录 性能情况 Performance 所需环境 Environment 文件下载 Download 训练步骤 How2train 预测步骤 How2predict 评估步骤 How2eval 参考资料 Reference 性能情况 训练数

Bubbliiiing 11 Dec 26, 2022
Machine Learning automation and tracking

The Open-Source MLOps Orchestration Framework MLRun is an open-source MLOps framework that offers an integrative approach to managing your machine-lea

873 Jan 04, 2023
Official pytorch implementation of DeformSyncNet: Deformation Transfer via Synchronized Shape Deformation Spaces

DeformSyncNet: Deformation Transfer via Synchronized Shape Deformation Spaces Minhyuk Sung*, Zhenyu Jiang*, Panos Achlioptas, Niloy J. Mitra, Leonidas

Zhenyu Jiang 21 Aug 30, 2022
EMNLP 2021 - Frustratingly Simple Pretraining Alternatives to Masked Language Modeling

Frustratingly Simple Pretraining Alternatives to Masked Language Modeling This is the official implementation for "Frustratingly Simple Pretraining Al

Atsuki Yamaguchi 31 Nov 18, 2022
[ICCV 2021 (oral)] Planar Surface Reconstruction from Sparse Views

Planar Surface Reconstruction From Sparse Views Linyi Jin, Shengyi Qian, Andrew Owens, David F. Fouhey University of Michigan ICCV 2021 (Oral) This re

Linyi Jin 89 Jan 05, 2023
https://arxiv.org/abs/2102.11005

LogME LogME: Practical Assessment of Pre-trained Models for Transfer Learning How to use Just feed the features f and labels y to the function, and yo

THUML: Machine Learning Group @ THSS 149 Dec 19, 2022
QueryDet: Cascaded Sparse Query for Accelerating High-Resolution SmallObject Detection

QueryDet-PyTorch This repository is the official implementation of our paper: QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small O

Chenhongyi Yang 276 Dec 31, 2022
Object Detection with YOLOv3

Object Detection with YOLOv3 Bu projede YOLOv3-608 modeli kullanılmıştır. Requirements Python 3.8 OpenCV Numpy Documentation Yolo ile ilgili detaylı b

Ayşe Konuş 0 Mar 27, 2022
Ejemplo Algoritmo Viterbi - Example of a Viterbi algorithm applied to a hidden Markov model on DNA sequence

Ejemplo Algoritmo Viterbi Ejemplo de un algoritmo Viterbi aplicado a modelo ocul

Mateo Velásquez Molina 1 Jan 10, 2022
The Agriculture Domain of ERPNext comes with features to record crops and land

Agriculture The Agriculture Domain of ERPNext comes with features to record crops and land, track plant, soil, water, weather analytics, and even trac

Frappe 21 Jan 02, 2023
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].

OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr

Christoph Reich 23 Sep 21, 2022
All the code and files related to the MI-Lab of UE19CS305 course in sem 5

Machine-Intelligence-Lab-CS305 The compilation of all the code an drelated files from MI-Lab UE19CS305 (of batch 2019-2023) offered by PES University

Arvind Krishna 3 Nov 10, 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
DirectVoxGO reconstructs a scene representation from a set of calibrated images capturing the scene.

DirectVoxGO reconstructs a scene representation from a set of calibrated images capturing the scene. We achieve NeRF-comparable novel-view synthesis quality with super-fast convergence.

sunset 709 Dec 31, 2022
Cours d'Algorithmique Appliquée avec Python pour BTS SIO SISR

Course: Introduction to Applied Algorithms with Python (in French) This is the source code of the website for the Applied Algorithms with Python cours

Loic Yvonnet 0 Jan 27, 2022
Detail-Preserving Transformer for Light Field Image Super-Resolution

DPT Official Pytorch implementation of the paper "Detail-Preserving Transformer for Light Field Image Super-Resolution" accepted by AAAI 2022 . Update

50 Jan 01, 2023
POCO: Point Convolution for Surface Reconstruction

POCO: Point Convolution for Surface Reconstruction by: Alexandre Boulch and Renaud Marlet Abstract Implicit neural networks have been successfully use

valeo.ai 93 Dec 29, 2022
PoolFormer: MetaFormer is Actually What You Need for Vision

PoolFormer: MetaFormer is Actually What You Need for Vision (arXiv) This is a PyTorch implementation of PoolFormer proposed by our paper "MetaFormer i

Sea AI Lab 1k Dec 30, 2022
Implementation for paper "STAR: A Structure-aware Lightweight Transformer for Real-time Image Enhancement" (ICCV 2021).

STAR-pytorch Implementation for paper "STAR: A Structure-aware Lightweight Transformer for Real-time Image Enhancement" (ICCV 2021). CVF (pdf) STAR-DC

43 Dec 21, 2022