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Automated Unit Testing in DevOps Pipeline - AWS Lambda using AWS CodeBuild
Chloe  Butler

Chloe Butler

1667425440

Pdf2gerb: Perl Script Converts PDF Files to Gerber format

pdf2gerb

Perl script converts PDF files to Gerber format

Pdf2Gerb generates Gerber 274X photoplotting and Excellon drill files from PDFs of a PCB. Up to three PDFs are used: the top copper layer, the bottom copper layer (for 2-sided PCBs), and an optional silk screen layer. The PDFs can be created directly from any PDF drawing software, or a PDF print driver can be used to capture the Print output if the drawing software does not directly support output to PDF.

The general workflow is as follows:

  1. Design the PCB using your favorite CAD or drawing software.
  2. Print the top and bottom copper and top silk screen layers to a PDF file.
  3. Run Pdf2Gerb on the PDFs to create Gerber and Excellon files.
  4. Use a Gerber viewer to double-check the output against the original PCB design.
  5. Make adjustments as needed.
  6. Submit the files to a PCB manufacturer.

Please note that Pdf2Gerb does NOT perform DRC (Design Rule Checks), as these will vary according to individual PCB manufacturer conventions and capabilities. Also note that Pdf2Gerb is not perfect, so the output files must always be checked before submitting them. As of version 1.6, Pdf2Gerb supports most PCB elements, such as round and square pads, round holes, traces, SMD pads, ground planes, no-fill areas, and panelization. However, because it interprets the graphical output of a Print function, there are limitations in what it can recognize (or there may be bugs).

See docs/Pdf2Gerb.pdf for install/setup, config, usage, and other info.


pdf2gerb_cfg.pm

#Pdf2Gerb config settings:
#Put this file in same folder/directory as pdf2gerb.pl itself (global settings),
#or copy to another folder/directory with PDFs if you want PCB-specific settings.
#There is only one user of this file, so we don't need a custom package or namespace.
#NOTE: all constants defined in here will be added to main namespace.
#package pdf2gerb_cfg;

use strict; #trap undef vars (easier debug)
use warnings; #other useful info (easier debug)


##############################################################################################
#configurable settings:
#change values here instead of in main pfg2gerb.pl file

use constant WANT_COLORS => ($^O !~ m/Win/); #ANSI colors no worky on Windows? this must be set < first DebugPrint() call

#just a little warning; set realistic expectations:
#DebugPrint("${\(CYAN)}Pdf2Gerb.pl ${\(VERSION)}, $^O O/S\n${\(YELLOW)}${\(BOLD)}${\(ITALIC)}This is EXPERIMENTAL software.  \nGerber files MAY CONTAIN ERRORS.  Please CHECK them before fabrication!${\(RESET)}", 0); #if WANT_DEBUG

use constant METRIC => FALSE; #set to TRUE for metric units (only affect final numbers in output files, not internal arithmetic)
use constant APERTURE_LIMIT => 0; #34; #max #apertures to use; generate warnings if too many apertures are used (0 to not check)
use constant DRILL_FMT => '2.4'; #'2.3'; #'2.4' is the default for PCB fab; change to '2.3' for CNC

use constant WANT_DEBUG => 0; #10; #level of debug wanted; higher == more, lower == less, 0 == none
use constant GERBER_DEBUG => 0; #level of debug to include in Gerber file; DON'T USE FOR FABRICATION
use constant WANT_STREAMS => FALSE; #TRUE; #save decompressed streams to files (for debug)
use constant WANT_ALLINPUT => FALSE; #TRUE; #save entire input stream (for debug ONLY)

#DebugPrint(sprintf("${\(CYAN)}DEBUG: stdout %d, gerber %d, want streams? %d, all input? %d, O/S: $^O, Perl: $]${\(RESET)}\n", WANT_DEBUG, GERBER_DEBUG, WANT_STREAMS, WANT_ALLINPUT), 1);
#DebugPrint(sprintf("max int = %d, min int = %d\n", MAXINT, MININT), 1); 

#define standard trace and pad sizes to reduce scaling or PDF rendering errors:
#This avoids weird aperture settings and replaces them with more standardized values.
#(I'm not sure how photoplotters handle strange sizes).
#Fewer choices here gives more accurate mapping in the final Gerber files.
#units are in inches
use constant TOOL_SIZES => #add more as desired
(
#round or square pads (> 0) and drills (< 0):
    .010, -.001,  #tiny pads for SMD; dummy drill size (too small for practical use, but needed so StandardTool will use this entry)
    .031, -.014,  #used for vias
    .041, -.020,  #smallest non-filled plated hole
    .051, -.025,
    .056, -.029,  #useful for IC pins
    .070, -.033,
    .075, -.040,  #heavier leads
#    .090, -.043,  #NOTE: 600 dpi is not high enough resolution to reliably distinguish between .043" and .046", so choose 1 of the 2 here
    .100, -.046,
    .115, -.052,
    .130, -.061,
    .140, -.067,
    .150, -.079,
    .175, -.088,
    .190, -.093,
    .200, -.100,
    .220, -.110,
    .160, -.125,  #useful for mounting holes
#some additional pad sizes without holes (repeat a previous hole size if you just want the pad size):
    .090, -.040,  #want a .090 pad option, but use dummy hole size
    .065, -.040, #.065 x .065 rect pad
    .035, -.040, #.035 x .065 rect pad
#traces:
    .001,  #too thin for real traces; use only for board outlines
    .006,  #minimum real trace width; mainly used for text
    .008,  #mainly used for mid-sized text, not traces
    .010,  #minimum recommended trace width for low-current signals
    .012,
    .015,  #moderate low-voltage current
    .020,  #heavier trace for power, ground (even if a lighter one is adequate)
    .025,
    .030,  #heavy-current traces; be careful with these ones!
    .040,
    .050,
    .060,
    .080,
    .100,
    .120,
);
#Areas larger than the values below will be filled with parallel lines:
#This cuts down on the number of aperture sizes used.
#Set to 0 to always use an aperture or drill, regardless of size.
use constant { MAX_APERTURE => max((TOOL_SIZES)) + .004, MAX_DRILL => -min((TOOL_SIZES)) + .004 }; #max aperture and drill sizes (plus a little tolerance)
#DebugPrint(sprintf("using %d standard tool sizes: %s, max aper %.3f, max drill %.3f\n", scalar((TOOL_SIZES)), join(", ", (TOOL_SIZES)), MAX_APERTURE, MAX_DRILL), 1);

#NOTE: Compare the PDF to the original CAD file to check the accuracy of the PDF rendering and parsing!
#for example, the CAD software I used generated the following circles for holes:
#CAD hole size:   parsed PDF diameter:      error:
#  .014                .016                +.002
#  .020                .02267              +.00267
#  .025                .026                +.001
#  .029                .03167              +.00267
#  .033                .036                +.003
#  .040                .04267              +.00267
#This was usually ~ .002" - .003" too big compared to the hole as displayed in the CAD software.
#To compensate for PDF rendering errors (either during CAD Print function or PDF parsing logic), adjust the values below as needed.
#units are pixels; for example, a value of 2.4 at 600 dpi = .0004 inch, 2 at 600 dpi = .0033"
use constant
{
    HOLE_ADJUST => -0.004 * 600, #-2.6, #holes seemed to be slightly oversized (by .002" - .004"), so shrink them a little
    RNDPAD_ADJUST => -0.003 * 600, #-2, #-2.4, #round pads seemed to be slightly oversized, so shrink them a little
    SQRPAD_ADJUST => +0.001 * 600, #+.5, #square pads are sometimes too small by .00067, so bump them up a little
    RECTPAD_ADJUST => 0, #(pixels) rectangular pads seem to be okay? (not tested much)
    TRACE_ADJUST => 0, #(pixels) traces seemed to be okay?
    REDUCE_TOLERANCE => .001, #(inches) allow this much variation when reducing circles and rects
};

#Also, my CAD's Print function or the PDF print driver I used was a little off for circles, so define some additional adjustment values here:
#Values are added to X/Y coordinates; units are pixels; for example, a value of 1 at 600 dpi would be ~= .002 inch
use constant
{
    CIRCLE_ADJUST_MINX => 0,
    CIRCLE_ADJUST_MINY => -0.001 * 600, #-1, #circles were a little too high, so nudge them a little lower
    CIRCLE_ADJUST_MAXX => +0.001 * 600, #+1, #circles were a little too far to the left, so nudge them a little to the right
    CIRCLE_ADJUST_MAXY => 0,
    SUBST_CIRCLE_CLIPRECT => FALSE, #generate circle and substitute for clip rects (to compensate for the way some CAD software draws circles)
    WANT_CLIPRECT => TRUE, #FALSE, #AI doesn't need clip rect at all? should be on normally?
    RECT_COMPLETION => FALSE, #TRUE, #fill in 4th side of rect when 3 sides found
};

#allow .012 clearance around pads for solder mask:
#This value effectively adjusts pad sizes in the TOOL_SIZES list above (only for solder mask layers).
use constant SOLDER_MARGIN => +.012; #units are inches

#line join/cap styles:
use constant
{
    CAP_NONE => 0, #butt (none); line is exact length
    CAP_ROUND => 1, #round cap/join; line overhangs by a semi-circle at either end
    CAP_SQUARE => 2, #square cap/join; line overhangs by a half square on either end
    CAP_OVERRIDE => FALSE, #cap style overrides drawing logic
};
    
#number of elements in each shape type:
use constant
{
    RECT_SHAPELEN => 6, #x0, y0, x1, y1, count, "rect" (start, end corners)
    LINE_SHAPELEN => 6, #x0, y0, x1, y1, count, "line" (line seg)
    CURVE_SHAPELEN => 10, #xstart, ystart, x0, y0, x1, y1, xend, yend, count, "curve" (bezier 2 points)
    CIRCLE_SHAPELEN => 5, #x, y, 5, count, "circle" (center + radius)
};
#const my %SHAPELEN =
#Readonly my %SHAPELEN =>
our %SHAPELEN =
(
    rect => RECT_SHAPELEN,
    line => LINE_SHAPELEN,
    curve => CURVE_SHAPELEN,
    circle => CIRCLE_SHAPELEN,
);

#panelization:
#This will repeat the entire body the number of times indicated along the X or Y axes (files grow accordingly).
#Display elements that overhang PCB boundary can be squashed or left as-is (typically text or other silk screen markings).
#Set "overhangs" TRUE to allow overhangs, FALSE to truncate them.
#xpad and ypad allow margins to be added around outer edge of panelized PCB.
use constant PANELIZE => {'x' => 1, 'y' => 1, 'xpad' => 0, 'ypad' => 0, 'overhangs' => TRUE}; #number of times to repeat in X and Y directions

# Set this to 1 if you need TurboCAD support.
#$turboCAD = FALSE; #is this still needed as an option?

#CIRCAD pad generation uses an appropriate aperture, then moves it (stroke) "a little" - we use this to find pads and distinguish them from PCB holes. 
use constant PAD_STROKE => 0.3; #0.0005 * 600; #units are pixels
#convert very short traces to pads or holes:
use constant TRACE_MINLEN => .001; #units are inches
#use constant ALWAYS_XY => TRUE; #FALSE; #force XY even if X or Y doesn't change; NOTE: needs to be TRUE for all pads to show in FlatCAM and ViewPlot
use constant REMOVE_POLARITY => FALSE; #TRUE; #set to remove subtractive (negative) polarity; NOTE: must be FALSE for ground planes

#PDF uses "points", each point = 1/72 inch
#combined with a PDF scale factor of .12, this gives 600 dpi resolution (1/72 * .12 = 600 dpi)
use constant INCHES_PER_POINT => 1/72; #0.0138888889; #multiply point-size by this to get inches

# The precision used when computing a bezier curve. Higher numbers are more precise but slower (and generate larger files).
#$bezierPrecision = 100;
use constant BEZIER_PRECISION => 36; #100; #use const; reduced for faster rendering (mainly used for silk screen and thermal pads)

# Ground planes and silk screen or larger copper rectangles or circles are filled line-by-line using this resolution.
use constant FILL_WIDTH => .01; #fill at most 0.01 inch at a time

# The max number of characters to read into memory
use constant MAX_BYTES => 10 * M; #bumped up to 10 MB, use const

use constant DUP_DRILL1 => TRUE; #FALSE; #kludge: ViewPlot doesn't load drill files that are too small so duplicate first tool

my $runtime = time(); #Time::HiRes::gettimeofday(); #measure my execution time

print STDERR "Loaded config settings from '${\(__FILE__)}'.\n";
1; #last value must be truthful to indicate successful load


#############################################################################################
#junk/experiment:

#use Package::Constants;
#use Exporter qw(import); #https://perldoc.perl.org/Exporter.html

#my $caller = "pdf2gerb::";

#sub cfg
#{
#    my $proto = shift;
#    my $class = ref($proto) || $proto;
#    my $settings =
#    {
#        $WANT_DEBUG => 990, #10; #level of debug wanted; higher == more, lower == less, 0 == none
#    };
#    bless($settings, $class);
#    return $settings;
#}

#use constant HELLO => "hi there2"; #"main::HELLO" => "hi there";
#use constant GOODBYE => 14; #"main::GOODBYE" => 12;

#print STDERR "read cfg file\n";

#our @EXPORT_OK = Package::Constants->list(__PACKAGE__); #https://www.perlmonks.org/?node_id=1072691; NOTE: "_OK" skips short/common names

#print STDERR scalar(@EXPORT_OK) . " consts exported:\n";
#foreach(@EXPORT_OK) { print STDERR "$_\n"; }
#my $val = main::thing("xyz");
#print STDERR "caller gave me $val\n";
#foreach my $arg (@ARGV) { print STDERR "arg $arg\n"; }

Download Details:

Author: swannman
Source Code: https://github.com/swannman/pdf2gerb

License: GPL-3.0 license

#perl 

Automated Unit Testing in DevOps Pipeline - AWS Lambda using AWS CodeBuild

Learn to automated unit testing in AWS DevOps Pipeline using AWS CodeBuild, including demo in python.

#aws #lambda #aws lambda #pipeline

Aurelie  Block

Aurelie Block

1598916060

Top 10 Automation Testing Tools: 2020 Edition

The demand for delivering quality software faster — or “Quality at Speed” — requires organizations to search for solutions in Agile, continuous integration (CI), and DevOps methodologies. Test automation is an essential part of these aspects. The latest World Quality Report 2018–2019 suggests that test automation is the biggest bottleneck to deliver “Quality at Speed,” as it is an enabler of successful Agile and DevOps adoption.

Test automation cannot be realized without good tools; as they determine how automation is performed and whether the benefits of automation can be delivered. Test automation tools is a crucial component in the DevOps toolchain. The current test automation trends have increased in applying artificial intelligence and machine learning (AI/ML) to offer advanced capabilities for test optimization, intelligent test generation, execution, and reporting. It will be worthwhile to understand which tools are best poised to take advantage of these trends.****

#automation-testing #automation-testing-tools #testing #testing-tools #selenium #open-source #test-automation #automated-testing

Alayna  Rippin

Alayna Rippin

1597161600

Accelerate Test Execution With Self-Healing Mechanism

In recent years, the testing community has witnessed a steady rise in automation testing. Although it has proved significant advantages compared to manual testing, flakiness in locating objects for WebUI testing is still a constant problem that restrains the transition to automated testing for teams. Testers have to spend unnecessary time and effort to manually update the object locators whenever they make new changes to the application.

The Self-healing mechanism is one of the most promising factors to completely change the automation Web testing. By eliminating unnecessary repetitive tasks in execution, this mechanism creates the foundation for test automation to perform at its full potential.

Object Locator Flakiness — A Constant Challenge in Test Automation

Object locator flakiness comes from the root of automation itself: fragile test scripts. Object locators, most often, can no longer identify the target element after the application under test (AUT) changes. Pre-written scripts then will fail to run the test correctly, which results in a false failed result. The QA team has to detect whether their tests fail because they actually have a problem, or the scripts cannot adapt to new element changes. Web testing, in which UI changes happen over and over, appears to suffer the most from this flakiness.

To maximize the speed advantage of automation testing, automation testers demand a mechanism that can recognize and skip these UI changes to keep the scripts running seamlessly. For automation testers, Self-healing function has turned out to be the optimal solution for this pain point.

What Is Self-Healing Automation? Why Is it Important?

Self-Healing Capability: A Definition

The human body is a perfect example to explain the self-healing mechanism. Whenever a human gets injured, the human self-healing function is triggered to find the wound and heal it without any action needed. For any minor injuries, this mechanism can quickly heal wounds without human intervention.

Back to self-healing automation in software testing, it functions exactly like the way the human body works. Based on the object changes in properties, the self-healing mechanism actively studies the characteristics and properties of all available objects, removing similar objects on the page and comparing their historical data. Then, the test engine will automatically pick up an alternative that best assembles the changed locator to keep the test running.

How Does Self-Healing Capability Benefit Test Automation?

Self-healing has been a desirable solution to solve one major challenge of automation testing: Quality at speed.

By identifying new changes and replacing them with similar objects, the self-healing mechanism reduces downtime and significantly speeds up the deployment process. With this capability, QA teams can release the burden of intense script maintenance, and save time and resources.

Additionally, a well-built self-healing mechanism gives QA teams the ability to create generic test frameworks that can apply to a broad range of software, improving the benefits of automation.

More and more automation tools have developed self-healing as an essential part of the tool in response to this enormous demand. Many experts expect that self-healing will become less of a nice-to-have function but a must-have for all automation tools in the near future.

In their latest update — version 7.6 — Katalon Studio company has introduced the new self-healing mechanism to its users. This function allows users to speed up processes and maximize automation efforts for the whole team.

See what’s new in Katalon Studio.

How Katalon Studio’s Self-Healing Capability Enhances Automation Processes

Before the updated version was released, Katalon Studio users were familiar with its Auto-healing Smart XPath. This plugin assists in recovering broken default locators by trying other available XPath alternatives. However, in case there are no suitable alternatives available, the execution will stop running.

To advance its process and provide users with more efficient test maintenance, Katalon Studio developed the Self-healing mechanism that has been released lately. Following the positive impacts of Smart XPath, the self-healing mechanism is made to be more robust and comprehensive to tackle broken locators during each execution.

Get to Know the Self-Healing Mechanism in Katalon Studio

During the execution, if Katalon Studio fails to identify an object with its default locator, the tool tries other pre-configured locators associated with that object. With 4 selection methods, including XPath, Attributes CSS, and image, users can opt to set the object locating priority to ensure accuracy and continuity of the execution.

If Katalon finds a suitable object within the selectors, the test keeps running to completion. With approval from the tester, the locator that is selected to replace the broken object will then be saved for that particular Test Object in future executions. By doing so, Katalon Studio creates a database to make the self-healing mechanism even more efficient by avoiding analyzing one same broken object repeatedly.

Once the execution is over, Katalon Studio will suggest replacing all broken locators with the locators having found the objects. If Katalon Studio cannot find the target objects, the test will either continue or stop running, depending on how users designed the failure handling option.

How to Execute Tests Using Self-Healing Mechanism in Katalon Studio

Requirements:

  • Katalon Studio version 7.6 onwards
  • An active Katalon Studio Enterprise license

In a Katalon Studio project, you can find a screen in project settings dedicated to Self-healing. You can change the default settings to make the utility better suit your needs.

The self-healing mode is activated by default whenever users run the application. To open the Self-healing window, go to Project/Settings/Self-Healing/Web UI.

Configure Test Design

To start with Katalon Studio’s self-healing, users need to set initial settings to decide the default selection method used during spying and recording. Please note that for Image selection, screenshots for the objects are mandatory.

Go to Project/Settings/Self-healing/Web UI/Test Design to set the default selection method.

test design

Configure Self-Healing Execution

Users can decide which alternative locators to be used in terms of selection methods and their priorities in Project/Settings/Self-Healing/Web UI/ Test Execution.

test execution

This predefined order will be applied when Katalon fails to locate the target objects.

All the replacements are recorded in Self-healing Insights when the execution is over. Katalon Studio allows users to decide which alternative locators to be used in terms of selection methods and their priorities.

To read the full tutorial and sample project using the self-healing mechanism, you can visit Katalon’s Document hub here.

Conclusion

With this upgraded Self-healing mechanism, Web testing is made faster and easier as it reduces human efforts on script maintenance with less interruption. This is a valuable addition for Katalon users to have a more powerful automation experience with consistent results.

To try out this new functionality, sign up on the Katalon website with your business email and get a 30-day free trial with full functions in the latest Katalon Studio!

#devops #software testing #automated testing #automation testing #update #software test automation #xpath #automation tools #software testing 2020 #object locator

Mikel  Okuneva

Mikel Okuneva

1596793726

Where To Learn Test Programming — July 2020 Edition

What do you do when you have lots of free time on your hands? Why not learn test programming strategies and approaches?

When you’re looking for places to learn test programming, Test Automation University has you covered. From API testing through visual validation, you can hone your skills and learn new approaches on TAU.

We introduced five new TAU courses from April through June, and each of them can help you expand your knowledge, learn a new approach, and improve your craft as a test automation engineer. They are:

These courses add to the other three courses we introduced in January through March 2020:

  • IntelliJ for Test Automation Engineers (3 hrs 41 min)
  • Cucumber with JavaScript (1 hr 22 min)
  • Python Programming (2 hrs)

Each of these courses can give you a new set of skills.

Let’s look at each in a little detail.

Mobile Automation With Appium in JavaScript

Orane Findley teaches Mobile Automation with Appium in JavaScript. Orane walks through all the basics of Appium, starting with what it is and where it runs.

javascript

“Appium is an open-source tool for automating native, web, and hybrid applications on different platforms.”

In the introduction, Orane describes the course parts:

  • Setup and Dependencies — installing Appium and setting up your first project
  • Working with elements by finding them, sending values, clicking, and submitting
  • Creating sessions, changing screen orientations, and taking screenshots
  • Timing, including TimeOuts and Implicit Waits
  • Collecting attributes and data from an element
  • Selecting and using element states
  • Reviewing everything to make it all make sense

The first chapter, broken into five parts, gets your system ready for the rest of the course. You’ll download and install a Java Developer Kit, a stable version of Node.js, Android Studio and Emulator (for a mobile device emulator), Visual Studio Code for an IDE, Appium Server, and a sample Appium Android Package Kit. If you get into trouble, you can use the Test Automation University Slack channel to get help from Orane. Each subchapter contains the links to get to the proper software. Finally, Orane has you customize your configuration for the course project.

Chapter 2 deals with elements and screen interactions for your app. You can find elements on the page, interact with those elements, and scroll the page to make other elements visible. Orane breaks the chapter into three distinct subchapters so you can become competent with each part of finding, scrolling, and interacting with the app. The quiz comes at the end of the third subchapter.

The remaining chapters each deal with specific bullets listed above: sessions and screen capture, timing, element attributes, and using element states. The final summary chapter ensures you have internalized the key takeaways from the course. Each of these chapters includes its quiz.

When you complete this course successfully, you will have both a certificate of completion and the code infrastructure available on your system to start testing mobile apps using Appium.

Selenium WebDriver With Python

Andrew Knight, who blogs as The Automation Panda, teaches the course on Selenium WebDriver with Python. As Andrew points out, Python has become a popular language for test automation. If you don’t know Python at all, he points you to Jess Ingrassellino’s great course, Python for Test Programming, also on Test Automation University.

Se

In the first chapter, Andrew has you write your first test. Not in Python, but Gherkin. If you have never used Gherkin syntax, it helps you structure your tests in pseudocode that you can translate into any language of your choice. Andrew points out that it’s important to write your test steps before you write test code — and Gherkin makes this process straightforward.

first test case

The second chapter goes through setting up a pytest, the test framework Andrew uses. He assumes you already have Python 3.8 installed. Depending on your machine, you may need to do some work (Macs come with Python 2.7.16 installed, which is old and won’t work. Andrew also goes through the pip package manager to install pipenv. He gives you a GitHub link to his test code for the project. And, finally, he creates a test using the Gherkin codes as comments to show you how a test runs in pytest.

In the third chapter, you set up Selenium Webdriver to work with specific browsers, then create your test fixture in the pytest. Andrew reminds you to download the appropriate browser driver for the browser you want to test — for example, chromedriver to drive Chrome and geckodriver to drive Firefox. Once you use pipenv to install Selenium, you begin your test fixture. One thing to remember is to call an explicit quit for your webdriver after a test.

Chapter 4 goes through page objects, and how you abstract page object details to simplify your test structure. Chapter 5 goes through element locator structures and how to use these in Python. And, in Chapter 6, Andrew goes through some common webdriver calls and how to use them in your tests. These first six chapters cover the basics of testing with Python and Selenium.

Now that you have the basics down, the final three chapters review some advanced ideas: testing with multiple browsers, handling race conditions, and running your tests in parallel. This course gives you specific skills around Python and Selenium on top of what you can get from the Python for Test Programming course.

#tutorial #performance #testing #automation #test automation #automated testing #visual testing #visual testing best practices #testing tutorial