Tag: Test Automation

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Expediting Web Testing with Puppeteer and Instant Test Automation Technology

The digital landscape has significantly advanced over the past 1-2 years. The new normal in web applications include a shift toward progressive web apps (PWAs), advanced responsive websites, and Flutter apps.

Ensuring both functional as well as API testing of such advance web applications is becoming harder and harder. While there are valid test automation frameworks like Selenium and Cypress, these are covering only a subset of what is needed to complete the entire quality aspects across multiple environments.

New Normal: Instant Test Automation

To address the testing challenge over time, across multiple environments, and with big and dynamic data, tools need to be more intelligent, and utilize AI/ML to really track trends, predict issues prior to them becoming more serious, and guide the developers and testers in real-time.

An instant test automation technology that can leverage a standard test automation framework such as Puppeteer to auto generate both functional as well as API tests on the fly and as things change is a game changer for app developers. This provides alerts and insights in real time that the team can act upon and move much faster.

The way sch solution works is through modeling the website under test, auto generate based on traffic and AI proper tests and runs them to provide the proper insights.

Setting up such solution is easy and needs to be done only once. Also, such tool fits systems that are built atop cloud-native, containers and Amazon ECS.

Benefits of Shifting into Instant and Intelligent Test Automation

With the need to shift left, release faster with confidence, and handle large and complex environment, teams can benefit from a self-generating testing solution that really covers more grounds that a typical code-based framework would. This does not mean that there are no benefits or need for such frameworks like Selenium and others, however, with tools like UP9, teams can complement the code related functional tests with an additional layer of quality validation that touches reliability, APIs, services, security and much more.

Case Study: Quick Tour of Puppeteer & UP9

I took the Google puppeteer framework and connected it with UP9 to try generating a nice model and test automation assets on my local machine.

After following the basic NPM installation instructions, it was easy to launch a local browser and record traffic using the tool.

From my terminal I would then run this command (‘my.new.workspace’ could be any name that the developer selects):

up9 tap:start my.new.workspace

Once I ran that command, using puppeteer, UP9 launches a chrome browser that I can start using to navigate to my website for recording all traffic, actions, API calls and other services. Upon closing the browser, the tool will process all of the flows and generate the model.

Here is the auto generated workspace that was created based on a quick tour I ran with UP9 on the Perforce and Perfecto websites:

The workspace consists of few views:

  1. The generic workspace with all the high-level services model (diagram),
  2. The contracts that were used in my recording,
  3. A detailed traffic analysis with the entire API calls,
  4. Tests that were created and mocks to be used across different environments.

These views were perceived and constructed based on service-traffic, following from the observers of UP9 that were assigned to my designated workspace.

As part of my journey, I landed on the Perfecto free-trial website, and the tool was able to generate the API calls (Request/Response) and allow me to validate that is was working as expected (see below)

If I wanted to also run my auto-generated tests, I have within the UP9 portal (fully SaaS and web-based) a tests area from where I could launch my tests as well.

Bottom Line

As the DevOps market mature towards more intelligent testing using AI and ML, and as the systems under tests (SUTs) are also progressing, there needs to be a realization within the teams that their processes could be improved dramatically using such technologies. Developers productivity together with consistent app quality were a CIO/IT manager top of mind for a long while, and with the recent advancements in the market, teams can really enjoy a new era of smarter ways of working.

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Most Recommended Software Testing Books to Read in 2020 and Beyond

As we kick of a new decade of software development and testing, and as digital continuous to challenge test automation engineers that are trying to fit the testing within shorter then ever cycles, here are the top recommended software testing books to consider – the order isn’t the priority, they are all awesome books and equally recommended:

#1 Agile Testing – Lisa Crispin and Janet Gregory

Readers will come away from this book understanding

  • How to get testers engaged in agile development
  • Where testers and QA managers fit on an agile team
  • What to look for when hiring an agile tester
  • How to transition from a traditional cycle to agile development
  • How to complete testing activities in short iterations
  • How to use tests to successfully guide development
  • How to overcome barriers to test automation

#2 More Agile Testing – Lisa Crispin and Janet Gregory

Main learning objectives from the book:

  • How to clarify testing activities within the team
  • Ways to collaborate with business experts to identify valuable features and deliver the right capabilities
  • How to design automated tests for superior reliability and easier maintenance
  • How agile team members can improve and expand their testing skills
  • How to plan “just enough,” balancing small increments with larger feature sets and the entire system
  • How to use testing to identify and mitigate risks associated with your current agile processes and to prevent defects
  • How to address challenges within your product or organizational context
  • How to perform exploratory testing using “personas” and “tours”
  • Exploratory testing approaches that engage the whole team, using test charters with session- and thread-based techniques
  • How to bring new agile testers up to speed quickly–without overwhelming them

#3 Hands on Mobile App Testing – Daniel Knott

Readers will learn how to

  • Establish your optimal mobile test and launch strategy
  • Create tests that reflect your customers, data networks, devices, and business models
  • Choose and implement the best Android and iOS testing tools
  • Automate testing while ensuring comprehensive coverage
  • Master both functional and nonfunctional approaches to testing
  • Address mobile’s rapid release cycles
  • Test on emulators, simulators, and actual devices
  • Test native, hybrid, and Web mobile apps
  • Gain value from crowd and cloud testing (and understand their limitations)
  • Test database access and local storage
  • Drive value from testing throughout your app life-cycle
  • Start testing wearables, connected homes/cars, and Internet of Things devices

#4 Enterprise Continuous Testing – Wolfgang Platz

Enterprise Continuous Testing: Transforming Testing for Agile and DevOps introduces a Continuous Testing strategy that helps enterprises accelerate and prioritize testing to meet the needs of fast-paced Agile and DevOps initiatives. Software testing has traditionally been the enemy of speed and innovation—a slow, costly process that delays releases while delivering questionable business value. This new strategy helps you test smarter, so testing provides rapid insight into what matters most to the business.

#5 Continuous Testing for DevOps Professionals – Eran Kinsbruner and Leading Market Experts

Continuous Testing for DevOps Professionals is the definitive guide for DevOps teams and covers the best practices required to excel at Continuous Testing (CT) at each step of the DevOps pipeline. It was developed in collaboration with top industry experts from across the DevOps domain from leading companies such as CloudBees, Tricentis, Testim.io, Test.ai, Perfecto, and many more.The book is aimed at all DevOps practitioners, including software developers, testers, operations managers, and IT/business executives

#6 Accelerate –The Science of Lean Software and DevOps, Nicole Forsgren

How can we apply technology to drive business value? For years, we’ve been told that the performance of software delivery teams doesn’t matter―that it can’t provide a competitive advantage to our companies. Through four years of groundbreaking research to include data collected from the State of DevOps reports conducted with Puppet, Dr. Nicole Forsgren, Jez Humble, and Gene Kim set out to find a way to measure software delivery performance―and what drives it―using rigorous statistical methods. This book presents both the findings and the science behind that research, making the information accessible for readers to apply in their own organizations.

#7 Complete Guide to Test Automation, Arnon Axelrod

  • Know the real value to be expected from test automation
  • Discover the key traits that will make your test automation project succeed
  • Be aware of the different considerations to take into account when planning automated tests vs. manual tests
  • Determine who should implement the tests and the implications of this decision
  • Architect the test project and fit it to the architecture of the tested application
  • Design and implement highly reliable automated tests
  • Begin gaining value from test automation earlier
  • Integrate test automation into the business processes of the development team
  • Leverage test automation to improve your organization’s performance and quality, even without formal authority
  • Understand how different types of automated tests will fit into your testing strategy, including unit testing, load and performance testing, visual testing, and more

#8 The DevOps Handbook, Gene Kim, Jez Humble, Patrick Debois, John Willis

More than ever, the effective management of technology is critical for business competitiveness. For decades, technology leaders have struggled to balance agility, reliability, and security. The consequences of failure have never been greater―whether it’s the healthcare.gov debacle, cardholder data breaches, or missing the boat with Big Data in the cloud. And yet, high performers using DevOps principles, such as Google, Amazon, Facebook, Etsy, and Netflix, are routinely and reliably deploying code into production hundreds, or even thousands, of times per day. Following in the footsteps of The Phoenix Project, The DevOps Handbook shows leaders how to replicate these incredible outcomes, by showing how to integrate Product Management, Development, QA, IT Operations, and Information Security to elevate your company and win in the marketplace

#9 The Digital Quality Handbook – Eran Kinsbruner and Industry Experts

As mobile and web technologies continue to expand and basically drives large organizational business in virtually every vertical or industry, it is critical to understand how to take existing release practices for mobile and web apps to the next level, including software development life cycle (SDLC), tools, quality, etc. Organizations which are already enjoying the power of digital are still struggling with various challenges that can be related to many factors, such as:

  • SDLC and processes maturity
  • Expanding test coverage to include more non-functional testing, user condition testing, etc.
  • Coping with existing limitations of open source tools and frameworks
  • Sustaining correctly sized and up-to-date mobile test labs
  • Getting proper quality insights upon each test cycle prior and post production
  • Branching wisely cross-platform and cross-feature test suites

#10 Specification by Example , How Successful Teams Deliver the Right Software, Gojko Adzic

Gojko has a list of great books, this is one of the great ones, but check out other of his books as well.

Specification by Example is an emerging practice for creating software based on realistic examples, bridging the communication gap between business stakeholders and the dev teams building the software. In this book, author Gojko Adzic distills interviews with successful teams worldwide, sharing how they specify, develop, and deliver software, without defects, in short iterative delivery cycles.

#11 Clean Code,  A Handbook of Agile Software Craftsmanship, Robert C. Martin

Readers will come away from this book understanding

  • How to tell the difference between good and bad code
  • How to write good code and how to transform bad code into good code
  • How to create good names, good functions, good objects, and good classes
  • How to format code for maximum readability
  • How to implement complete error handling without obscuring code logic
  • How to unit test and practice test-driven development

#12 Continuous Delivery,  Reliable Software Releases through Build, Test, and Deployment Automation, Jez Humble and David Farley

The authors introduce state-of-the-art techniques, including automated infrastructure management and data migration, and the use of virtualization. For each, they review key issues, identify best practices, and demonstrate how to mitigate risks. Coverage includes

  • Automating all facets of building, integrating, testing, and deploying software
  • Implementing deployment pipelines at team and organizational levels
  • Improving collaboration between developers, testers, and operations
  • Developing features incrementally on large and distributed teams
  • Implementing an effective configuration management strategy
  • Automating acceptance testing, from analysis to implementation
  • Testing capacity and other non-functional requirements
  • Implementing continuous deployment and zero-downtime releases
  • Managing infrastructure, data, components and dependencies
  • Navigating risk management, compliance, and auditing

#13 The Guide to Software Testability, Ash Winter and Rob Meaney

Learn practical insights on how testability can help bring teams together to observe, control and understand the systems they build. Enabling them to better meet customer needs, achieve a transparent level of quality and predictability of delivery.

#14 A Practical Guide to Testing in DevOps, Katrina Clokie

A Practical Guide to Testing in DevOps offers direction and advice to anyone involved in testing in a DevOps environment

#15 Test Automation University, Angie Jones and Applitools

While not a book, a great shout out to my colleague, friend and co-author in one of my above mentioned books Angie Jones for launching, leading and building the Test Automation University. This is obviously an additional online resource that complements books and other written material.

Summary

I am sure that there are plenty of other great and practical books, but i went with this list as a start. If you feel that there must be an additional up to date book, reach out to me, and I will be more than happy to add to this list.

Happy Reading!

 

 

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Core Pillars of Stable Test Automation Suites

For those who follow me, you already know that to build a continuous testing suites that scales, and that lasts for more than few software iterations, teams must follow rigorous processes.

When i say teams – I mean developers, test engineers and business testers.

 

 

This post isn’t about balancing the work load between personas, but rather on continuously sharpening the test suites value to the entire team.

As we close a decade and enter a new one, and with some cool advancements in the technologies that include AI/ML but also challenging platforms like PWAs, Foldables, 5G and IOT – it’s the perfect time to re-evaluate our testing management and maintenance processes.

What Causes Test Instabilities?

Especially across the digital landscape, there are quite a few recurring patterns that causes test instabilities or flakiness.

  • There are the scripts and frameworks that we use – in this category we can list object locators strategy, popups (security, system), coding skills, timing and steps synchronizations and more.
  • There are backend issues around services, networking and up to date test data and environments.
  • Lab related issues that includes platforms being unavailable or poorly setup for testing (screen is locked, network is disconnected, app isn’t installed, device isn’t in ready state mode)
  • Lastly, Orchestration – This is a tricky root cause since there are not that many early warnings to these kind of issues up until you execute and scale up. Not having sufficient platform to test against, or knowing that a platform is in use is often hard to find (but – not impossible :))

In addition to the above 4 major categories, there are also of course the software development dynamics that includes advancements in the product, market changes that impact your test scripts and infrastructure, and also the external dependencies that you cannot always control (network carriers, 3rd party services that you depend on, etc.).

Test Automation Certification for Value vs. ROI

While there is no 100% safety net for the above mentioned RCAs (root cause analysis), but there are few steps that teams can take and enforce to minimize the risks.

My few recommended tips that should be examined every 2-3 software releases/iterations are:

  1. Think with the end in mind when you write a test automation script. Will the test provide value more than just once? Which test suites/types such test will fit (regression, functional, unit, etc.)
  2. Consider the maintainability of such test script over time, how difficult will that be? and will it be worth the hassle?
  3. Certify the test script prior to integrating it into any pipeline. Certification should address the stability of the test across multiple platforms (only works on my machine is not an option), test execution duration (Less than 5 minutes please), If it is a test that detected defects it needs to be scored somehow as a higher value test that others.
  4. Monitor and measure the impact of your test suites and correct not longer than once a quarter!

The above image is an example of an external dependency that can impact the performance of your app. Assuming you test your mobile app against real cellular networks, you should acknowledge that not every carrier behave and performs the same, and it may impact your overall results. Knowing, measuring and taking this into account can save false negatives and other wrong speculations.

Lastly, and as this section implies – it is time we stop measuring test automation ROI and $ but clear value and risk mitigation to the business. Test automation value is by far more wide than the legacy ROI metrics that were simply covering for cost of test creation and execution regardless of what the test executions actually results in.

I have recently delivered a session about test automation stability for the OnlineTestConf. You can view the recording and slides here

Power Of Analytics

While a lot of the above might be clear to many practitioners, what i often see in the market is that the time element prevents teams from actually seeing what’s wring with their testing infrastructures. Teams invest a lot of money, resources and of course time into building a cool set of testing suites, however once their done, the auto pilot steps in, and until something is broken, these suites remains blind spots. This is again, a legacy practice, and in the modern DevOps/Agile/Continuous Testing era, teams ought to monitor and gain maximum visibility into their test code continuously!

As the above visual suggest – only when you look into the reports in a smart way, you can improve quality, deliver fast and up to date feedback and Yes – get some ROI (in a form of value) from your investment.

Imagine you can upon demand answer questions like –

  • what are my most problematic test scenarios?
  • what are my most flaky or buggy platforms (mobile/web)?
  • which job within my CI is the longest?
  • Which test cases must be retired or be placed in a “blocked” bucket for maintenance (due to popups, objects, other)?

Knowing the above answers upon and perhaps prior to clicking on the RUN button could be a major productivity boost to your entire cycle, wouldn’t it?

The below are 2 real life example from the Perfecto tool, but you can think about similar implementation as well – In the below, based on AI and smart algorithms the tool scans the test reports for pre-defined patterns like popups, elements not found, platforms in use and others, but also allows teams to customize these and add unique and relevant RCAs on their own to better slice and dice the test data.

Bottom Line

As we wrap a decade of software development and testing, it’s perhaps time that we take our test automation a level up and inject smart algorithms, processes and more so we are always on top of what we build, and improve whenever there is a need.

Happy Testing!

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Getting Started With Headless Browser Testing

[Guest Blog by Uzi Eilon, CTO, Perfecto]

The “shift left” trend is actually happening, developers as part of the DevOps pipeline need to test more and add more automation testing in order to release faster.

In addition, those tests are almost the last barrier before production, because the traditional testing is going away.

In such case, the standard unit tests are not good enough, and the E2E tests are complicated and require a longer time of setup and prepare.

This is the reason both Google and Mozilla released new JS headless browsers to help their developers to execute automation tests.

The same happened in the mobile area where Apple and Google released the XCUItest and Espresso.

Headless browsers provide the following capabilities in order for the developers to use it:

  • Same language , same IDE , same working environment:
    Most of the web develops work with  JS so these browsers are JS platform , to add new test you should open new class and write standard JS code.
  • FAST Feedback & Execution
    These tests need to be executed fast (sometime every commit) , these browser reduce the UI and rendering “noise” connect to the element directly  and run very fase.
  • Easy to setup
    Developers time is expensive, and developers will not add complicated processes for test , the setup of the tools is a simple npm installation.
  • Access to all the DevTools capabilities
    Developers need more details , these tools give access to all the DevTools data includes accessibility, network, log , security and more.
    Smart tests can be very powerful and cover not only the functionally but also the efficiency

In order to understand more I played with Puppeteer and I’m happy share my thoughts with you.

Installation

Very simple

npm i –save puppeteer

Documentation

Not a lot of examples or discussions about specific issues but I did find the API documentation that contains everything I was looking for.

Objects identification

Intuitive – Same way I connected to my object via any JS  .

Example:

  • by id : page.type(‘#firstName’,‘Uzi’);·
  • by class page.type(‘.class,‘Uzi’);

Sync and waiting for elements

In this case, I have to admit I struggled with the standard wait for navigation command, it was not stable:

await page.waitForNavigation({waitUntil:‘load’})

at the end I used the following :

await page.waitForSelector(‘#firstName’,{visible:true}).then(()=>
{      // do the actions per page
page.screenshot({path: ‘then.png’,fullPage: false})
});

 

UI

As part of my test I tried to verify the screen by taking a screenshot, I liked the way I could change the browser UI capabilities and configure my page:

const fullScreen = {
deviceScaleFactor: 1,
hasTouch: false,
height:  2400 ,
isLandscape: false,
isMobile: false,
width: 1800,
fullPage: true
};
page.setViewport(fullScreen)

 

Other devOpts options:

it is very easy to use, for example I would like to see all my links in a frame

for (let child of frame.childFrames())
{
dumpFrameTree(child, indent + ‘  ‘);
}

 

Summary:

Using the headless browser like Puppeteer was very easy and intuitive, it felt natural to add it as part of my testing code.

In addition, setting up the headless browser environment and executing was very simple and fast.

On the less convenient point, what I found was that to get the results directly into the CI, one should add more scripting code or use other executions methods.

Lastly, this method still ramps up, hence has some small bugs in few features and also lacks documentation and more samples, however, for an early testing tool for white-box/unit testing, it is very promising and well-positioned to complement tools such as Selenium. AS a matter of fact, what I also saw, is that other browser vendors are taking the same approach and investing in headless browsers – Mozilla, Microsoft.

 

P.S: If you want to learn more about the growing technologies and trends in the market, I encourage you to follow My podcast with Uzi Eilon called Testium (Episode 6 is fully dedicated to this subject)

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Model-Based Testing and Test Impact Analysis

In my previous blogs and over the years, I already stated how complicated, demanding and challenging is the mobile space, therefore it seems obvious that there needs to be a structured method of building test automation and meeting test coverage goals for mobile apps.

While there are various tools and techniques, in this blog I would like to focus on a methodology that has been around for a while but was never adopted in a serious and scalable way by organizations due to the fact that it is extremely hard to accomplish, there are no sufficient tools out there that support it when it comes to non-proprietary open-source tools and more.

First things first, let’s define what is a Model-Based testing

Model-based testing (MBT) is an application for designing and optionally executing artifacts to perform software testing or system testing. Models can be used to represent the desired behavior of a System Under Test (SUT), or to represent testing strategies and a test environment.

mbt

Fig 1: MBT workflow example. Source: Wikipedia

In the context of mobile, if we think about an end-user workflow with an application it will usually start with a Login to the app, performing an action, going back, performing a secondary action and often even a 3rd action based on the previous output of the 2nd. Complex Ha

The importance of modeling a mobile application serves few business goals:

  1. App release velocity
  2. App testing coverage (use cases)
  3. App test automation coverage (%)
  4. Overall app quality
  5. Cross-team synchronization (Dev, Test, Business)

 

As already covered in an old blog  I wrote, mobile apps would behave differently, and support different functionality based on the platform they are running (E.g., not every iOS device support both Touch ID and/or 3D Touch gesture). Therefore, being able to not only model the app and generate the right test cases but also to match these tests across the different platforms can be a key to achieving many of the 1-5 goals above.

In the market, today there are various commercial tools that can assist in MBT like CA Agile Requirement Designer, Tricentis Tosca, and others.

Looking at an example provided by one of the commercial vendors in the market (Tricentis), it can show a common workflow around MBT. A team aims to test an application; therefore, they would scan it using the MBT tool to “learn” its use cases, capabilities, and other artifacts so they can stack these into a common repository that can serve the team to build test automation.

tosca

Fig 2: Tricentis Tosca MBTA tool

In Fig 2., Tricentis examines a web page to learn its entire options, objects, and other data related items. Once the app is scanned, it can be easily converted into a flow diagram that can serve as the basis for test automation scenarios.

With the above goals in mind, it is important to understand that having an MBT tool that serves the automation team is a good thing, but only if it increases the team efficiency, its release velocity, and the overall test automation coverage. If the output of such tool would be a long list of test cases that either does not cover the most important user flows, or it includes many duplicates than this wouldn’t serve the purpose of MBT but rather will delay existing processes, and add unnecessary work to teams that are already under pressure.

In addition to the above commercial tools, there is an older but free tool that allows Android MBT with robotium called MobiGuitar. This tool not just offers MBT capabilities but also code coverage driven by the generated test scripts.

A best practice in that regards would be to probably use an MBT tool that can generate all the application related artifacts that include the app object repository, the full set of use cases, and allow all of that to be exported to leading open-source test automation frameworks like Selenium, Appium, and others.

Mobile Specific MBT – Best Practices and Examples

Drilling down into a workflow that CA would recommend around MBT would look as follows – In reality, the below is easier said than done for a Mobile App compared to Web and Desktop:

  1. The business analysts will create the story using tools like CA Agile Requirement Designer or such (see below more examples)
  2. The story is then passed to an ALM tool (e.g.: CA Agile Central [formerly Rally], Jira, etc.) for project tracking
  3. Teams use the MBT tools to collaborate
    1. The automation engineer adds the automation code snippets to the nodes where needed or adds additional nodes for automation.
    2. The programmer updates the model for technical specs or more technical details.
    3. The Test Data engineer assigns test data to the model
  4. Changes to the story are synchronized with the ALM Tool
  5. Test cases are synchronized with the ALM Tool
  6. The programmer completes coding
  7. The code is promoted from Dev to QA
  8. Testing begins
    1. The tester uses the test cases with test data from MBT tools for manual test case execution
    2. The automation scripts with test data are executed for functional and regression testing

To learn more about efficient MBT solutions, practices please refer to these sources:

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Free iOS automation testing tool – Test Studio for iOS

Hi

I will not write too much in this post, just wanted to provide a link for a free mobile automation tool for iOS web/GUI applications which is available in the App Store

http://www.telerik.com/automated-testing-tools/ios-testing.aspx?utm_source=twitter&utm_medium=sm&utm_content=FRDTNCKNWJ&utm_campaign=ad

The tool provides a simple record/replay mechanism on the iOS native platform and fits basic and not too complex web and native applications.

Soon it should allow sync of the test results and more in the cloud.

Test Studio for iOS does not use image based element detection. It relies on object based recording instead.

I recommend to give it a try

Regards,

Eran Kinsbruner

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Automating mobile tests with SeeTest by Experitest

Hi,

In this short post i will introduce the SeeTest mobile automation testing tool which penetrates the mobile land and provides a very good automation and LAN Cloud solution for iOS/Android and other mobile OS’s.

The tool can be downloaded for short trial via the main web site: http://experitest.com 

The ramping up and connection of a device or simulator is quite easy, see short video which demonstrates the basic steps to get you up and running:

The tool provides built in high level functions (Actions like ‘launch browser’, ‘send url’ etc.) which ease the test development and automation life cycle.

The automation is highly reliable, and has various methods of object recognition and recording, as well as object editing for more precise operations (both OCR, Image and Native object recognition and analysis).

The tool has simple integration into the most common IDE’s (QTP, Jsystem, python, and others), and allows to deploy the initial code which was recorded into that IDE.

The tool has a mobile cloud solution which is unique, and provides remote access from within the local area network to any device which is connected, and by such allows running various scripts on multiple handsets/simulators as part of a regression test cycle or a continuous integration process etc.

For more info regarding pricing model or technical details, either contact me or the SeeTest support through the web

Good Luck

Eran Kinsbruner