overte-JulianGro/tools/nitpick

nitpick

Nitpick is a stand alone application that provides a mechanism for regression testing. The general idea is simple:

• Each test folder has a script that produces a set of snapshots.
• The snapshots are compared to a 'canonical' set of images that have been produced beforehand.
• The result, if any test failed, is a zipped folder describing the failure.

Nitpick has 5 functions, separated into 4 tabs:

1. Creating tests, MD files and recursive scripts
2. Windows task bar utility (Windows only)
3. Running tests
4. Evaluating the results of running tests
5. Web interface

Build

Nitpick is built as part of the High Fidelity build.

Creating installers

Windows

1. Verify that 7Zip is installed.
2. cd to the build\tools\nitpick\Release directory
3. Delete any existing installers (named nitpick-installer-###.exe)
4. Select all, right-click and select 7-Zip->Add to archive...
5. Set Archive format to 7z
6. Check "Create SFX archive
7. Enter installer name (i.e. nitpick-installer-v1.1.exe)
8. Click "OK"
9. Copy created installer to https://hifi-qa.s3.amazonaws.com/nitpick/Windows/nitpick-installer-v1.1.exe: aws s3 cp nitpick-installer-v1.1.exe s3://hifi-qa/nitpick/Mac/nitpick-installer-v1.1.exe

Mac

These steps assume the hifi repository has been cloned to ~/hifi.

1. (First time) install create-dmg: brew install create-dmg
2. cd to the build/tools/nitpick/Release folder
3. Copy the quazip dynamic library (note final period): cp ~/hifi/build/ext/Xcode/quazip/project/lib/libquazip5.1.dylib .
4. Change the loader instruction to find the dynamic library locally install_name_tool -change ~/hifi/build/ext/Xcode/quazip/project/lib/libquazip5.1.dylib libquazip5.1.dylib nitpick
5. Delete any existing disk images: rm *.dmg
6. Create installer (note final period): create-dmg --volname nitpick-installer-v1.1 nitpick-installer-v1.1.dmg . Make sure to wait for completion.
7. Copy created installer to AWS: ~/Library/Python/3.7/bin/aws s3 cp nitpick-installer-v1.1.dmg s3://hifi-qa/nitpick/Mac/nitpick-installer-v1.1.dmg

Installation

Windows

1. (First time) download and install vc_redist.x64.exe (available at https://hifi-qa.s3.amazonaws.com/nitpick/Windows/nitpick-installer-v1.1.exe)

2. (First time) download and install Python 3 from https://hifi-qa.s3.amazonaws.com/nitpick/Windows/python-3.7.0-amd64.exe (also located at https://www.python.org/downloads/)

   1. After installation - create an environment variable called PYTHON_PATH and set it to the folder containing the Python executable.

3. (First time) download and install AWS CLI from https://hifi-qa.s3.amazonaws.com/nitpick/Windows/AWSCLI64PY3.msi (also available at https://aws.amazon.com/cli/

   1. Open a new command prompt and run aws configure
   2. Enter the AWS account number
   3. Enter the secret key
   4. Leave region name and ouput format as default [None]
   5. Install the latest release of Boto3 via pip: pip install boto3

4. Download the installer by browsing to here

5. Double click on the installer and install to a convenient location
   

6. To run nitpick, double click nitpick.exe

Mac

1. (First time) install Python from https://www.python.org/downloads/release/python-370/ (macOS 64-bit installer or macOS 64-bit/32-bit installer)

   1. After installation - run open "/Applications/Python 3.6/Install Certificates.command". This is needed because the Mac Python supplied no longer links with the deprecated Apple-supplied system OpenSSL libraries but rather supplies a private copy of OpenSSL 1.0.2 which does not automatically access the system default root certificates.
   2. Verify that /usr/local/bin/python3 exists.

2. (First time - AWS interface) Install pip with the script provided by the Python Packaging Authority:
   $ curl -O https://bootstrap.pypa.io/get-pip.py
   $ python3 get-pip.py --user

   1. Use pip to install the AWS CLI.
      $ pip3 install awscli --upgrade --user
      This will install aws in your user. For user XXX, aws will be located in ~/Library/Python/3.7/bin
   2. Open a new command prompt and run aws configure
   3. Enter the AWS account number
   4. Enter the secret key
   5. Leave region name and ouput format as default [None]
   6. Install the latest release of Boto3 via pip: pip3 install boto3

3. Download the installer by browsing to here.

4. Double-click on the downloaded image to mount it

5. Create a folder for the nitpick files (e.g. ~/nitpick) If this folder exists then delete all it's contents.

6. Copy the downloaded files to the folder
   cp -r /Volumes/nitpick-installer-v1.1/* .

7. To run nitpick, cd to the folder that you copied to and run ./nitpick #Use

Create

The Create tab provides functions to create tests from snapshots, MD files, a test outline and recursive scripts.

Create Tests

Usage

This function is used to create/update Expected Images after a successful run of a test, or multiple tests.

The user will be asked for the snapshot folder and then the tests root folder. All snapshots located in the snapshot folder will be used to create or update the expected images in the relevant tests.

Details

As an example - if the snapshots folder contains an image named tests.content.entity.zone.zoneOrientation.00003.png, then this file will be copied to tests/contente/enity/zone/zoneOrientation/ExpectedImage0003.png.

Create Tests Outline

Usage

This function creates an MD file in the (user-selected) tests root folder. The file provides links to both the tests and the MD files.

Create MD file

Usage

This function creates a file named test.md from a test.js script. The user will be asked for the folder containing the test script:

Details

The process to produce the MD file is a simplistic parse of the test script.

• The string in the nitpick.perform(...) function call will be the title of the file

• Instructions to run the script are then provided:

Run this script URL: Manual Auto(from menu/Edit/Open and Run scripts from URL...).

• The step description is the string in the addStep/addStepStepSnapshot commands

• Image links are provided where applicable to the local Expected Images files

Create all MD files

Usage

This function creates all MD files recursively from the user-selected root folder. This can be any folder in the tests hierarchy (e.g. all engine\material tests).

The file provides a hierarchal list of all the tests

Create testAuto script

Usage

This function creates a script named testAuto.js in a user-selected test folder.

Details

The script created runs the test.js script in the folder in automatic mode. The script is the same for all tests.

Create all testAuto scripts

Usage

This function creates all testAuto scripts recursively from the user-selected root folder. This can be any folder in the tests hierarchy (e.g. all engine\material tests).

The file provides a hierarchical list of all the tests

Create Recursive Script

Usage

After the user selects a folder within the tests hierarchy, a script is created, named testRecursive.js. This script calls all test.js scripts in the sub-folders.

Details

The various scripts are called in alphabetical order.

An example of a recursive script is as follows:

// This is an automatically generated file, created by nitpick on Jul 5 2018, 10:19

PATH_TO_THE_REPO_PATH_UTILS_FILE = "https://raw.githubusercontent.com/highfidelity/hifi_tests/master/tests/utils/branchUtils.js";
Script.include(PATH_TO_THE_REPO_PATH_UTILS_FILE);
var nitpick = createNitpick(Script.resolvePath("."));

var testsRootPath = nitpick.getTestsRootPath();

if (typeof Test !== 'undefined') {
    Test.wait(10000);
};

nitpick.enableRecursive();
nitpick.enableAuto();

Script.include(testsRootPath + "content/overlay/layer/drawInFront/shape/test.js");
Script.include(testsRootPath + "content/overlay/layer/drawInFront/model/test.js");
Script.include(testsRootPath + "content/overlay/layer/drawHUDLayer/test.js");

nitpick.runRecursive();

Create all Recursive Scripts

Usage

In this case all recursive scripts, from the selected folder down, are created.

Running this function in the tests root folder will create (or update) all the recursive scripts.

Windows

This tab is Windows-specific. It provides buttons to hide and show the task bar.

The task bar should be hidden for all tests that use the primary camera. This is required to ensure that the snapshots are the right size.

Run

The run tab is used to run tests in automatic mode. The tests require the location of a folder to store files in; this folder can safely be re-used for any number of runs (the "Working Folder"). The test script that is run is https://github.com/highfidelity/hifi_tests/blob/master/tests/testRecursive.js. The user can use a different branch' or even repository, if required.
Tests can be run server-less, or with the local host. In the second case, the domain-server and assignment-clients are run before starting Interface.
The default is to run the latest build. The user can select a specific build or PR if desired. Testing can be started immediately, or run on a schedule.

A test run is performed in a number of steps:

1. If the latest run has been selected then the dev-builds.xml file is downloaded to identify the latest build.
2. The installer is then downloaded.
3. After downloading the High Fidelity application is installed. This requires that UAC be disabled!
4. Any instances of the server-console, assignment-client, domain-server or Interface are killed before running the tests.
5. Interface is run with the appropriate command line parameters.
6. The expected images are then downloaded from GitHub and compared to the actual images from the tests.

The working folder will ultimately contain the following:

1. A folder named High Fidelity. This is where High Fidelity is installed.
2. A folder named snapshots. This folder contains the zipped results folders (one for each run). It also contains both the actual images and the expected images from the last run; note that these are deleted before running tests (All PNG files in the folder are deleted. In addition - a text file named tests_completed.txt is created at the end of the test script - this signals that Interface did not crash during the test run.
3. The dev-builds.xml file, if it was downloaded.
4. The HighFidelity installer. Note that this is always named HighFidelity-Beta-latest-dev so as not to store too many installers over time.
5. A log file describing the runs. This file is appended to after each run.

Evaluate

The Evaluate tab provides a single function - evaluating the results of a test run.

A checkbox (defaulting to checked) runs the evaluation in interactive mode. In this mode - every failure is shown to the user, who can then decide whether to pass the test, fail it or abort the whole evaluation.

If any tests have failed, then a zipped folder will be created in the snapshots folder, with a description of each failed step in each test.

Usage

Before starting the evaluation, make sure the GitHub user and branch are set correctly. The user should not normally be changed, but the branch may need to be set to the appropriate RC.

After setting the check-box as required and pressing Evaluate - the user will be asked for the snapshots folder.

Details

Evaluation proceeds in a number of steps:

1. A folder is created to store any failures

2. The expected images are download from GitHub. They are named slightly differently from the snapshots (e.g. tests.engine.render.effect.highlight.coverage.00000.png and tests.engine.render.effect.highlight.coverage.00000_EI.png).

3. The images are then pair-wise compared, using the SSIM algorithm. A fixed threshold is used to define a mismatch.

4. In interactive mode - a window is opened showing the expected image, actual image, difference image and error:

5. If not in interactive mode, or the user has defined the results as an error, an error is written into the error folder. The error itself is a folder with the 3 images and a small text file containing details.

6. At the end of the test, the folder is zipped and the original folder is deleted. If there are no errors then the zipped folder will be empty.

Web Interface

This tab has two functions: updating the TestRail cases, runs and results, and creating web page reports that are stored on AWS.

Before updating TestRail, make sure the GitHub user and branch are set correctly. The user should not normally be changed, but the branch may need to be set to the appropriate RC.

Any access to TestRail will require the TestRail account (default is High Fidelity's account), a user-name and a password:

• The default test rail user is shown, and can be changed as needed.
• The user-name is usually the user's email.
• The Project ID defaults to 14 - Interface.
• The Suite ID defaults to 1147 - Rendering.
• The TestRail page provides 3 functions for writing to TestRail.

Create Test Cases

Usage

This function can either create an XML file that can then be imported into TestRail through TestRail itself, or automatically create the appropriate TestRail Sections.

The user will be first asked for the tests root folder and a folder to store temporary files (this is the output folder).

If XML has been selected, then the XML file will be created in the output folder.

If Python is selected, the user will then be prompted for TestRail data. After pressing Accept - the Release combo will be populated (as it needs to be read from TestRail).

After selecting the appropriate Release, press OK. The Python script will be created in the output folder, and the user will be prompted to run it.

A busy window will appear until the process is complete.

Details

A number of Python scripts are created:

• testrail.py is the TestRail interface code.
• stack.py is a simple stack class
• getReleases.py reads the release names from TestRail
• addTestCases is the script that writes to TestRail.

In addition - a file containing all the releases will be created - releases.txt

Create Run

A Run is created from previously created Test Cases.

The user will first be prompted for a temporary folder (for the Python scripts).

After entering TestRail data and pressing Accept - the Sections combo will be populated (as it needs to be read from TestRail).

After selecting the appropriate Section, press OK. The Python script will be created in the output folder, and the user will be prompted to run it.

A busy window will appear until the process is complete.

Details

A number of Python scripts are created:

• testrail.py is the TestRail interface code.
• stack.py is a simple stack class
• getSections.py reads the release names from TestRail
• addRun is the script that writes to TestRail.

In addition - a file containing all the releases will be created - sections.txt

Update Run Results

This function updates a Run with the results of an automated test.

The user will first be prompted to enter the zipped results folder and a folder to store temporary files (this is the output folder).

After entering TestRail data and pressing Accept - the Run combo will be populated (as it needs to be read from TestRail).

After selecting the appropriate Run, press OK. The Python script will be created in the output folder, and the user will be prompted to run it.

A busy window will appear until the process is complete.

Details

A number of Python scripts are created:

• testrail.py is the TestRail interface code.
• getRuns.py reads the release names from TestRail
• addRun is the script that writes to TestRail.

In addition - a file containing all the releases will be created - runs.txt.

Create Web Page

This function requests a zipped results folder and converts it to a web page. The page is created in a user-selecetd working folder.
If the Update AWS checkbox is checked then the page will also be copied to AWS, and the appropriate URL will be displayed in the window below the button.