Static-test - A playground to play with ideas related to testing the comparability of the code

Overview

Static test playground

⚠️ The code is just an experiment. Compiles and runs on Ubuntu 20.04. Work with other systems is not guaranteed. ⚠️

What is a static test

If we want to check that some code does not compile there is no way to write a test for it.

This repo aims at solving this problem.

How it looks to the user

The proposal for the user interface for this feature is to piggyback on GTest pipeline as follows:

#include <gtest/gtest.h>
#include "static_test.h"

STATIC_TEST(foo) {
  Foo foo;
  foo.bar();
  SHOULD_NOT_COMPILE(foo.stuff());
  SHOULD_NOT_COMPILE_WITH_MESSAGE(foo.stuff(), "has no member named 'stuff'");
}

The user is able to write a code to check that some code should not compile. All the code outside of the SHOULD_NOT_COMPILE or SHOULD_NOT_COMPILE_WITH_MESSAGE macros is compiled and run as expected. The compiler will happily report any errors back to the user if they should make any within the STATIC_TEST scope. If the code under SHOULD_NOT_COMPILE ends up actually compiling a runtime error will be issued with a description of this.

This test can be run within this repo as:

./bazelisk test --test_output=all //foo:test_foo

The approximate output of this test if nothing fails would be smth like this:

[----------] 1 test from StaticTest__foo
[ RUN      ] StaticTest__foo.foo
[ COMPILE STATIC TEST ] foo
[                  OK ] foo
[       OK ] StaticTest__foo.foo (966 ms)
[----------] 1 test from StaticTest__foo (966 ms total)

If there is a failure, the line that causes the failure will be printed like so:

[----------] 1 test from StaticTest__FooMixedCorrectAndWrongTest
[ RUN      ] StaticTest__SomeTest.SomeTest
[ COMPILE STATIC TEST ] SomeTest
ERROR: foo/test_foo.cpp:35: must fail to compile but instead compiled without error.
foo/test_foo.cpp:0: Failure
Some of the static tests failed. See above for error.
[              FAILED ] SomeTest
[  FAILED  ] StaticTest__SomeTest.SomeTest (1403 ms)
[----------] 1 test from StaticTest__SomeTest (1403 ms total)

Currently, the code expects to have a compilation database with at the root of the project. This can be generated from a bazel build using the following repository: https://github.com/grailbio/bazel-compilation-database. Just download it anywhere and call the generate.sh script in the folder of this project.

Eventually, we might want to plug this into the build system to make sure we have everything at hand when running the test.

How to check that something fails to compile

We obviously cannot write a normal unit test for this, as if we write code that does not compile it, well, does not compile. The only way I can think of here is to run an external tool.

So the STATIC_TEST macro would expand into a class that will do work in its constructor. It will essentially call an external tool providing it with the name of the static test and a path to the current file utilizing __FILE__. If we know the compilation flags for this file we can write a new temporary cpp file with the contents:

#include <gtest/gtest.h>

#include "foo/foo.h"
#include "static_test/static_test.h"

int main()
{
  Foo foo;
  foo.bar();
  foo.stuff();
  foo.baz();
  return 0;
}

We can then compile this file using all the same compilation flags and check if there is an error that matches the error message regex provided into the message. If there is an error, then we pass the test. If there is no error that matches, we fail the test.

Owner
Igor Bogoslavskyi
Researcher interested in LiDAR scene understanding, localization and mapping.
Igor Bogoslavskyi
Code for the CVPR2022 paper "Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity"

Introduction This is an official release of the paper "Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity" (arxiv link). Abstrac

Leo 21 Nov 23, 2022
code for EMNLP 2019 paper Text Summarization with Pretrained Encoders

PreSumm This code is for EMNLP 2019 paper Text Summarization with Pretrained Encoders Updates Jan 22 2020: Now you can Summarize Raw Text Input!. Swit

Yang Liu 1.2k Dec 28, 2022
Companion code for the paper "Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks" by Yatsura et al.

META-RS This is the companion code for the paper "Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks" by Yatsu

Bosch Research 7 Dec 09, 2022
HMLET (Hybrid-Method-of-Linear-and-non-linEar-collaborative-filTering-method)

Methods HMLET (Hybrid-Method-of-Linear-and-non-linEar-collaborative-filTering-method) Dynamically selecting the best propagation method for each node

Yong 7 Dec 18, 2022
Deep Learning (with PyTorch)

Deep Learning (with PyTorch) This notebook repository now has a companion website, where all the course material can be found in video and textual for

Alfredo Canziani 6.2k Jan 07, 2023
For AILAB: Cross Lingual Retrieval on Yelp Search Engine

Cross-lingual Information Retrieval Model for Document Search Train Phase CUDA_VISIBLE_DEVICES="0,1,2,3" \ python -m torch.distributed.launch --nproc_

Chilia Waterhouse 104 Nov 12, 2022
CodeContests is a competitive programming dataset for machine-learning

CodeContests CodeContests is a competitive programming dataset for machine-learning. This dataset was used when training AlphaCode. It consists of pro

DeepMind 1.6k Jan 08, 2023
Help you understand Manual and w/ Clutch point while driving.

简体中文 forza_auto_gear forza_auto_gear is a tool for Forza Horizon 5. It will help us understand the best gear shift point using Manual or w/ Clutch in

15 Oct 08, 2022
Prototype for Baby Action Detection and Classification

Baby Action Detection Table of Contents About Install Run Predictions Demo About An attempt to harness the power of Deep Learning to come up with a so

Shreyas K 30 Dec 16, 2022
Source code and Dataset creation for the paper "Neural Symbolic Regression That Scales"

NeuralSymbolicRegressionThatScales Pytorch implementation and pretrained models for the paper "Neural Symbolic Regression That Scales", presented at I

35 Nov 25, 2022
Must-read Papers on Physics-Informed Neural Networks.

PINNpapers Contributed by IDRL lab. Introduction Physics-Informed Neural Network (PINN) has achieved great success in scientific computing since 2017.

IDRL 330 Jan 07, 2023
The Self-Supervised Learner can be used to train a classifier with fewer labeled examples needed using self-supervised learning.

Published by SpaceML • About SpaceML • Quick Colab Example Self-Supervised Learner The Self-Supervised Learner can be used to train a classifier with

SpaceML 92 Nov 30, 2022
Tutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3

Python-for-Epidemiologists This repository is an introduction to epidemiology analyses in Python. Additionally, the tutorials for my library zEpid are

Paul Zivich 120 Nov 17, 2022
hySLAM is a hybrid SLAM/SfM system designed for mapping

HySLAM Overview hySLAM is a hybrid SLAM/SfM system designed for mapping. The system is based on ORB-SLAM2 with some modifications and refactoring. Raú

Brian Hopkinson 15 Oct 10, 2022
Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image (ICCV 2021)

Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color

75 Dec 02, 2022
[ACL-IJCNLP 2021] "EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets"

EarlyBERT This is the official implementation for the paper in ACL-IJCNLP 2021 "EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets" by

VITA 13 May 11, 2022
Qt-GUI implementation of the YOLOv5 algorithm (ver.6 and ver.5)

YOLOv5-GUI 🎉 YOLOv5算法(ver.6及ver.5)的Qt-GUI实现 🎉 Qt-GUI implementation of the YOLOv5 algorithm (ver.6 and ver.5). 基于YOLOv5的v5版本和v6版本及Javacr大佬的UI逻辑进行编写

EricFang 12 Dec 28, 2022
🔥 Cannlytics-powered artificial intelligence 🤖

Cannlytics AI 🔥 Cannlytics-powered artificial intelligence 🤖 🏗️ Installation 🏃‍♀️ Quickstart 🧱 Development 🦾 Automation 💸 Support 🏛️ License ?

Cannlytics 3 Nov 11, 2022
Code reproduce for paper "Vehicle Re-identification with Viewpoint-aware Metric Learning"

VANET Code reproduce for paper "Vehicle Re-identification with Viewpoint-aware Metric Learning" Introduction This is the implementation of article VAN

EMDATA-AILAB 23 Dec 26, 2022
For holding anime-related object classification and detection models

Animesion An end-to-end framework for anime-related object classification, detection, segmentation, and other models. Update: 01/22/2020. Due to time-

Edwin Arkel Rios 72 Nov 30, 2022