Open Testing: Opening tests like opening source
Scrum Masters

Open Testing: Opening tests like opening source

This text is predicated on a chat I gave on Open Testing at a couple of conferences: STARWEST 2021, TAU: The Homecoming, TSQA 2022, QA or the Freeway 2022, and Conf42: SRE 2022.

I’m tremendous excited to introduce a considerably new concept to you and to our business: Open Testing: What if we open our assessments like we open our supply? I’m not merely speaking about creating open supply take a look at frameworks. I’m speaking about opening the assessments themselves. What if it grew to become regular to share take a look at circumstances and automatic procedures? What if it grew to become regular for corporations to publicly share their take a look at outcomes? And what are the levels of openness in testing for which we should always attempt as an business?

I believe that we – whether or not we’re testers, builders, managers, or another position in software program – can enormously enhance the standard of our work if we undertake rules of openness into our testing practices. To assist me clarify, I’d wish to share how I realized about the principle advantages of open supply software program, after which we will cross these advantages over into testing work.

So, let’s go method again in time to after I first encountered open supply software program.

My first encounter with open supply code

I first began programming after I was in highschool. At 13 years previous, I used to be an incoming freshman at Parkville Excessive College of their magnet faculty for math, science, and laptop science in good previous Baltimore, Maryland. (Enjoyable truth: Parkville’s mascots had been the Knights, which is my final title!) All college students within the magnet program wanted to have a TI-83 Plus graphing calculator. Now, thoughts you, this was again within the day earlier than sensible telephones existed. Flip telephones had been the cool pattern! The TI-83 Plus was cutting-edge handheld know-how at the moment. It was so superior that after I first bought it, it took me 5 minutes to determine the best way to flip it off!

The TI-83 Plus

I rapidly realized that the TI-83 Plus was only a mini-computer in disguise. Do you know that this factor has a full programming language constructed into it? TI-BASIC! Throughout the first two weeks of my freshman Intro to Pc Science class, our trainer taught us the best way to program math formulation: Slope. Circle circumference and space. The quadratic components. You title it, I programmed it, even when it wasn’t a homework task. It felt superior! It was extra enjoyable to me than enjoying video video games, and consider me, I used to be an enormous Nintendo fan.

There have been two additional options of the TI-83 Plus that made it superb for programming. First, it had a hyperlink cable for sharing packages. Two individuals may join their calculators and duplicate packages from one to the opposite. For sure, with all my formulation, I grew to become fairly standard round take a look at time. Second, anybody may open any program file on the calculator and skim its code. The TI-BASIC supply code may not be hidden. By design, it was “open supply.”

That is how I realized my very first lesson about open supply software program: Open supply helps me study. Each time I’d copy packages from others, together with video games, I’d open this system and skim the code to see the way it labored. Generally, I’d make adjustments to enhance it. Extra importantly, although, many instances, I’d study one thing new that may assist me write higher packages. That is how I taught myself to code. All on this tiny display screen. All via ripping open different individuals’s code and studying it. All as a result of the code was open to me.

From the second I wrote my first calculator program, I knew I needed to develop into a software program engineer. I had that spark.

My first open supply library

Let’s fast-forward to school. I entered the Pc Science program at Rochester Institute of Expertise – Go Tigers! By my freshman 12 months in faculty, I had realized Java, C++, slightly Python, and, of all issues, COBOL. All of the code in all my tasks till that time had been written totally by me. Generally, I’d have a look at examples in books as a information, however I’d by no means use different individuals’s code. In actual fact, if a professor caught you utilizing copied code, you then’d fail that task and threat being expelled from the college.

Then, in my first software program engineering course, we realized the best way to write unit assessments utilizing a library known as JUnit. We downloaded JUnit from someplace on-line – this was earlier than Maven grew to become huge – and hooked it into our Java path. Then, we began writing take a look at courses with take a look at case strategies, and someway, all of it ran magically in methods I couldn’t determine on the time.

I used to be astounded that I may use software program that I didn’t write myself in a mission. Permission from a professor was one factor, however the truth that somebody on the market on this planet was making a gift of good code at no cost simply blew my thoughts. I noticed the worth in unit assessments, and I instantly noticed the worth in a easy, free take a look at framework like JUnit.

That’s after I realized my second lesson about open supply software program: Open supply helps me develop into a greater developer. I may have written my very own take a look at framework, however that may have taken me a number of time. JUnit was able to go and free to make use of. Plus, since a number of people had already spent years growing JUnit, it will have extra options and fewer bugs than something I may develop alone for a school mission. Utilizing a bundle like JUnit helped me write and run my unit assessments without having to develop into an professional in take a look at automation frameworks. I may construct cool issues without having to construct each single element.

That revelation felt empowering. Inside a couple of years of taking that software program engineering course, websites for internet hosting open supply tasks like GitHub grew to become big. Programming language bundle indexes like Maven, NuGet, PyPI, and NPM grew to become improvement mainstays. The working joke inside Python grew to become that you could possibly import something! This was method higher than swapping calculator video games with hyperlink cables.

My first probability to provide again

After I graduated faculty, I used to be zealous for open supply software program. I believed in it. I used to be an ardent supporter. However, I used to be principally a client. As a Software program Engineer in Take a look at, I used many main take a look at instruments and frameworks: JUnit, TestNG, Cucumber, NUnit, xUnit.web, SpecFlow, pytest, Jasmine, Mocha, Selenium WebDriver, RestSharp, Relaxation Assured – the listing goes on and on. As a Python developer, I used many modules and frameworks within the Python ecosystem like Django, Flask, and requests.

Then, I bought the possibility to provide again: I launched an open supply mission known as Boa Constrictor. Boa Constrictor is a .NET implementation of the Screenplay Sample. It helps you make higher interactions for higher automation. Out of the field, it gives Internet UI interactions utilizing Selenium WebDriver and Relaxation API interactions utilizing RestSharp, however you should use it to implement any interactions you need.

My firm and I launched Boa Constrictor publicly in October 2020. You may take a look at the boa-constrictor repository on GitHub. Initially, my staff and I at Q2 developed all of the code. We launched it as an open supply mission hoping that it may assist others within the business. However then, one thing cool occurred: people within the business helped us! We began receiving pull requests for brand spanking new options. In actual fact, we even began utilizing some new interactions developed by group members internally in our firm’s take a look at automation mission. We additionally proudly participated in Hacktoberfest in 2020 and 2021.

Boa Constrictor: The .NET Screenplay Sample

That’s after I realized my third lesson about open supply software program: Open supply helps me develop into a greater maintainer. Giant tasks want all the assistance they will get. Even a staff of core maintainers can’t all the time deal with all of the work. Nevertheless, when a mission is open supply, anybody who makes use of it might probably assist out. Every little contribution can add worth for the entire person base. Sustaining software program then turns into simpler, and the mission can develop into extra impactful.

Battling poor high quality

As a Software program Engineer in Take a look at, I discovered myself caught between two worlds. In a single world, I used to be a developer at coronary heart who beloved to jot down code to unravel issues. Within the different world, I used to be a software program high quality skilled who examined software program and advocated for enhancements. These worlds got here collectively primarily via take a look at automation and steady integration. Now that I’m a developer advocate, I nonetheless occupy this intersectionality with a higher duty for serving to others.

Nevertheless, all through my total profession, I preserve hitting one main downside: Software program high quality has an issue with high quality. Let that sink in: software program high quality has a giant downside with high quality. I’ve labored on groups with titles starting from “Software program High quality Assurance” to “Take a look at Engineering & Structure,” and even an “Automation Middle of Excellence.” Regardless of the titular deal with high quality, each staff has suffered from points of poor high quality in workmanship.

Listed here are a couple of poignant examples:

  • Handbook take a look at case repositories are filled with assessments with redundant steps.
  • Take a look at automation tasks are riddled with duplicate code.
  • Setup and cleanup steps are copy-pasted endlessly, whether or not wanted or not.
  • Automation code makes use of poor practices, resembling international variables as an alternative of dependency injection.
  • A 90% success price is handled as a “good” day with “restricted” flakiness.
  • Many assessments cowl foolish, pointless, or unimportant issues as an alternative of helpful, significant behaviors.

How can we name ourselves high quality professionals when our personal work suffers from poor high quality? Why are these sorts of issues so pervasive? I believe they construct up over time. Copy-pasting one process feels innocuous. One rogue variable gained’t be observed. One flaky take a look at isn’t any huge deal. As soon as this begins occurring, groups insularly preserve repeating these practices till they make a multitude. I don’t assume giving groups extra time to work on these issues will clear up them, both, as a result of extra time doesn’t interrupt inertia – it merely prolongs it.

The developer in me desperately desires to unravel these issues. However how? I can do it in my very own tasks, however as a result of my assessments are sealed behind firm doorways, I can’t use it to point out others the best way to do it at scale. Lots of the articles and programs we’ve got on how-to-do-X are filled with toy examples, too.

Altering our high quality tradition

So, how can we get groups to interrupt unhealthy habits? I believe our business wants a tradition change. If we could possibly be extra open with testing like we’re open with supply code, then maybe we may deliver lots of the advantages we see from open supply into testing:

  1. Serving to individuals study testing
  2. Serving to individuals develop into higher testers
  3. Serving to individuals develop into higher take a look at maintainers

If we domesticate a tradition of openness, then we may lead higher practices by instance. Moreover, if we develop into clear about our high quality, it may bolster our customers’ confidence in our merchandise whereas concurrently retaining us motivated to maintain high quality excessive.

There are a number of methods to begin pursuing this concept of open testing. Not each risk could also be relevant for each circumstance, however my objective is to get y’all eager about it. Hopefully, these concepts can encourage higher practices for higher high quality.

Openness via inside collaboration

For a place to begin of reference, let’s contemplate the least open context for testing. Think about a staff the place testing work is totally siloed by position. In this sort of staff, there’s a harsh line between builders and testers. Solely the testers ever see take a look at circumstances, entry take a look at repositories, or contact automation. Take a look at circumstances and take a look at plans are primarily “closed” to non-testers because of entry, readability, and even apathy. The one output from testers are failure percentages and bug experiences. Outcomes are based mostly extra on belief than on proof.

This type of staff sounds fairly bleak. I hope this isn’t the type of staff you’re on, however possibly it’s. Let’s see how openness could make issues higher.

Step one in the direction of open testing is inside openness. Let’s break down some siloes. Testers don’t solely personal high quality. Not everybody must be a tester by title, however everybody on the staff ought to develop into quality-conscious. In actual fact, any software program improvement staff has three primary roles: Enterprise, Improvement, and Testing. Enterprise seems for what issues to unravel, Improvement addresses the best way to implement options, and Testing gives suggestions on the answer. These three roles collectively are often known as “The Three Amigos” or “The Three Hats.”

Every position affords a helpful perspective with distinctive experience. When the Three Amigos keep aside, options below improvement don’t benefit from a number of views. They may have critical design flaws, they may be unreasonable to implement, or they may be tough to check. Misunderstandings may additionally trigger builders to construct the fallacious issues or testers to jot down ineffective assessments. Nevertheless, when the Three Amigos get collectively, they will collectively contribute to the design of product options. Everybody can get on the identical web page. The staff can construct high quality into the product from the beginning. They might do actions like Query Storming and Instance Mapping to assist them outline behaviors.

The Three Amigos

As a part of this collaboration, not everybody could find yourself writing assessments, however everybody can be eager about high quality. Testing then turns into simpler as a result of anticipated behaviors are well-defined and well-understood. Testers get deeper perception into what’s essential to cowl. When testers share outcomes and open bugs, different staff members are extra receptive as a result of the suggestions is extra significant and extra helpful.

We practiced Three Amigos collaboration at my earlier firm, Q2. My pal Steve was a developer who noticed the worth in Instance Mapping. Many instances, he’d decide up poorly-defined person tales with conflicting info or lacking acceptance standards. Generally, he’d burn an entire dash simply attempting to determine issues out! As soon as he realized about Instance Mapping, he began organising half-hour classes with the opposite two Amigos (one among whom was me) to higher perceive person tales from the beginning. He bought into it. Because of proactive collaboration, he may develop the tales extra easily. One time, I bear in mind we stopped engaged on a narrative as a result of we couldn’t justify its enterprise worth, which saved Steve two weeks of pointless work. The story didn’t finish there: Steve grew to become a Software program Engineer in Take a look at! He shifted left so exhausting that he shifted into an entire new position.

Openness via residing specs

One other step in the direction of open testing is residing documentation via specification by instance. Collaboration like we noticed with the Three Amigos is nice, however the worth it gives will be fleeting if it isn’t written down. Groups want artifacts to file designs, examples, and ultimately take a look at circumstances.

One motive why I really like Instance Mapping is as a result of it facilitates a staff to spell out tales, guidelines, examples, and questions onto color-coded playing cards that they will preserve for future refinement.

  1. Tales develop into work gadgets.
  2. Guidelines develop into acceptance standards.
  3. Examples develop into take a look at circumstances.
  4. Questions develop into spikes or future tales.

Throughout Instance Mapping, people sometimes write playing cards rapidly. An instance card describes a conduct to check, nevertheless it won’t fastidiously design the situation. It wants additional refinement. Defining behaviors utilizing a transparent, concise format like Given-When-Then makes behaviors straightforward to grasp and straightforward to check.

For instance, let’s say we needed to check an internet search engine. The instance could possibly be to seek for a phrase like”panda”. We may write this instance as the next situation:

  1. Given the search engine web page is displayed
  2. When the person searches for the phrase “panda”
  3. Then the outcomes web page reveals a listing of hyperlinks for “panda”

This particular Given-When-Then format is named the Gherkin language. Gherkin comes from Conduct-Pushed Improvement instruments like Cucumber, however it may be useful for any sort of testing. Gherkin defines testable behaviors in a concise method that follows the Prepare-Act-Assert sample. You set issues up, you work together with the function, and also you confirm the outcomes.

Moreover, Gherkin encourages Specification by Instance. This situation gives clear directions on the best way to carry out a search. It has actual knowledge, which is the search phrase “panda,” and clear outcomes. Utilizing real-world examples in specs like this helps all Three Amigos perceive the exact conduct.

Turning Instance Mapping playing cards into Gherkin conduct specs

Conduct specs are multifaceted artifacts:

  1. They’re necessities that outline how a function ought to behave.
  2. They’re acceptance standards that should be met for a deliverable to be full.
  3. They’re take a look at circumstances with clear directions.
  4. They might develop into automated scripts with the proper of take a look at framework.
  5. They’re residing documentation for the product.

Residing documentation is open and highly effective. Anybody on the staff or outdoors the staff can learn it to study in regards to the product. Refining concepts into instance playing cards into conduct specs turns into a pipeline that delivers residing doc as a byproduct of the software program improvement lifecycle.

SpecFlow is likely one of the finest frameworks that helps this sort of openness with Specification by Instance and Residing Documentation. SpecFlow is a free and open-source take a look at automation framework for .NET. In SpecFlow, you write your take a look at circumstances as Gherkin eventualities, and also you automate every Given-When-Then step utilizing C# strategies.

Considered one of SpecFlow’s niftiest options, nevertheless, is SpecFlow+ LivingDoc. Most take a look at frameworks focus solely on automation code. When a take a look at is automated, then solely a programmer can learn it and perceive it. Gherkin makes this simpler as a result of steps are written in plain language, however Gherkin eventualities are however saved in a code repository that’s inaccessible to many staff members. SpecFlow+ LivingDoc breaks that sample. It turns Gherkin eventualities right into a searchable doc website accessible to all Three Amigos. It makes take a look at circumstances and take a look at automation far more open. LivingDoc additionally gives take a look at outcomes for every situation. Inexperienced test marks point out passing assessments, whereas pink X’s point out failures.

Traditionally, testers use experiences like this to offer suggestions in-house to their managers and builders. Outcomes point out what works and what must be mounted. Nevertheless, take a look at outcomes will be helpful to extra individuals than simply inside staff members. What if take a look at outcomes had been shared with customers and clients? I’m going to repeat that assertion, as a result of it may appear stunning: What if customers and clients may see take a look at outcomes? 

Give it some thought. Open take a look at outcomes have very constructive results. Transparency with customers builds belief. If customers can see that issues are examined and dealing, then they may achieve confidence within the high quality of the product. If they may peer into the residing documentation, then they may learn to use the product even higher. On the flip facet, transparency holds improvement groups accountable to retaining high quality excessive, each within the product and within the testing. Open take a look at outcomes provide these advantages provided that the outcomes will be trusted. If assessments are ineffective or failures are rampant, then public take a look at outcomes may truly damage those growing the product.

A SpecFlow+ LivingDoc report

Such a radical transparency would require an unlimited tradition shift. It is probably not acceptable for each firm to create public dashboards with their take a look at outcomes, nevertheless it could possibly be a strategic differentiator when used correctly. For instance, after I labored at Q2, we shared LivingDoc experiences with particular PrecisionLender clients after each two-week launch. It constructed belief. Plus, for the reason that LivingDoc report consists of solely high-level conduct specs with easy outcomes, even a vice chairman may learn it! We may share assessments with out sharing automation code. That was highly effective.

Openness via open supply

Let’s preserve extending open testing outward. Along with sharing take a look at outcomes and residing documentation, people can even share instruments, frameworks, and different components of their assessments. That is the place open testing actually is open supply.

We already coated a bunch of open supply tasks for take a look at automation. As an business, we’re actually blessed with so many unbelievable tasks. Each single one among them represents a staff of testers who not solely solved an issue however determined to share their answer with the world. Every answer is summary sufficient to use to many circumstances however concrete sufficient to offer a useful implementation. Collectively, the tasks on this web page have in all probability been downloaded greater than a billion instances, and that’s no joke. And in order for you, you could possibly learn the open supply code for any of them.

Standard open supply take a look at automation tasks

Cool new tasks seem on a regular basis, too. Considered one of my favourite tasks that began previously few years is Playwright, an superior browser automation instrument from Microsoft. Playwright makes end-to-end internet testing straightforward, dependable, and quick. It gives cross-browser and cross-language assist like Selenium, a concise syntax like Cypress, and a bunch of superior options like computerized ready, tracing, and code era. Plus, Playwright is magnitudes sooner than different automation instruments. It took issues that made Selenium, Cypress, and Puppeteer nice, and it took them to the following stage.

Openness via shared take a look at suites

To date, all of the methods of approaching open testing are issues we may do at this time. Many people are in all probability already doing this stuff, even when we didn’t consider them below the phrase “open testing.” However the place can these concepts go sooner or later?

My thoughts goes again to one of many huge issues with testing that I discussed earlier: duplication. Opening up collaboration fixes some unhealthy habits, and sharing elements eliminates some duplication within the plumbing of take a look at automation, however so lots of our assessments throughout the business repeat the identical sorts of steps and comply with the identical kinds of patterns.

For instance, take into consideration any time you’ve ordered one thing from an internet retailer. It could possibly be Amazon, Walmart, Goal – no matter. Each single on-line retailer has a digital buying cart. Everytime you wish to purchase one thing, you add it to your cart. Then, once you’re accomplished buying, you proceed to pay for all of the gadgets in your cart. When you resolve you don’t need one thing anymore, you take away it from the cart. Simple-peasy.

As I describe this sort of buying cart, I don’t want to point out you screenshots from the shop web site to clarify it. Y’all have accomplished a lot on-line buying that you just intuitively know the way it works, whatever the retailer. Heck, I just lately ordered a bunch of components for an previous Volkswagen Beetle from a website named JBugs, and the buying cart was the identical.

In that case many purposes have the identical components, then why can we preserve duplicating the identical assessments somewhere else? Give it some thought. Take into consideration what number of instances totally different groups have written practically an identical buying cart assessments. Ouch. Take into consideration how a lot time was wasted on that duplication of effort.

I believe that is one thing the place Synthetic Intelligence and Machine Studying may assist. What if we may develop machine studying fashions to study widespread behaviors for apps and providers? The training brokers would search for issues like commonplace icons and typical workflows. We may primarily create take a look at suites for issues like login, search, buying, and fee that would run efficiently on most apps. These sorts of assessments in all probability couldn’t cowl the whole lot in any given utility, however they may cowl fundamental, widespread behaviors. Perhaps that would cowl 1 / 4 of all behaviors value testing. Perhaps a 3rd? Perhaps half? Each little bit helps!

AI and ML might help us obtain true Autonomous Testing

Now, think about sharing these generic take a look at suites publicly. In the identical method builders have open supply tasks to assist expedite their coding, and in the identical method knowledge scientists have open knowledge units to make use of for modeling, testers may have open take a look at suites that they may decide up and run as relevant. Not take a look at instruments – however precise runnable assessments that would run towards any utility. If these sorts of take a look at suites show to be helpful, then outstanding ones may develop into universally-accepted bars of high quality for software program apps. For instance, sooner or later, corporations may obtain and execute assessments that run on any system for the apps they’re growing along with the assessments they develop in-house. I believe that could possibly be a extremely cool alternative.

Such a testing – Autonomous Testing – is the longer term. Software program developer and testers will use AI-backed instruments to higher study, discover, and train app behaviors. These instruments will make it simpler than ever to automate scriptable assessments.

The best way to begin pursuing openness

As we’ve got coated, open testing may take many kinds:

  1. It could possibly be openness in collaboration to construct higher high quality from the beginning.
  2. It could possibly be openness in specification by instance and residing documentation.
  3. It could possibly be openness in sharing assessments and their outcomes with clients and customers.
  4. It could possibly be openness in sharing instruments, frameworks, and platforms.
  5. It could possibly be openness in constructing shared take a look at units for widespread utility behaviors.

A few of these concepts may appear far-fetched or aspirational, however fairly truthfully, I believe every of them may add a number of worth to testing practices. I believe each tester and each staff ought to have a look at this listing and ask themselves, “Might we strive a few of these issues?” Maybe your staff may take child steps with higher collaboration or higher specification. Maybe your staff has a cool mission you constructed in-house that you could possibly launch as an open supply mission, like my previous staff and I did with Boa Constrictor. Maybe there’s a startup concept in utilizing machine studying for autonomous testing. Maybe there are different methods to realize open testing that aren’t listed right here. Who is aware of? It could possibly be cool!

We must also contemplate the flip facet. Are there sure points of testing that ought to stay closed? My thoughts goes to safety. Might totally open testing inadvertently reveal safety vulnerabilities? Might lack of protection in some areas welcome expedited exploitation? I don’t know, however I believe we should always contemplate prospects like these.

If you wish to pursue open testing, listed here are three inquiries to get you began:

  1. How is your testing at this time?
    1. In what methods is it already open?
    2. In what methods is it closed?
  2. How may your testing enhance with incremental openness?
    1. We’re speaking child steps right here – small enhancements that you could possibly simply obtain at this time.
    2. It could possibly be as small as attempting Instance Mapping or becoming a member of a mob programming session.
  3. How may your testing enhance with radical openness?
    1. Shoot the moon! Dream huge! Get inventive!
    2. On the earth of software program, something is feasible.


We must also keep in mind that open testing isn’t a objective unto itself. It’s a way to an finish, and that finish is greater high quality: high quality in our practices, high quality in our artifacts, and in the end high quality within the software program we create. We shouldn’t search openness in testing simply because I’m spouting a number of buzzwords on this article. On the similar time, we additionally shouldn’t brush off these concepts as too radical or idealistic. What we should always do is search methods for perpetual enchancment. Keep in mind that this entire concept of open testing got here from the tried-and-true advantages of open supply code.

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