Seven Test Automation Industry Shifts and Trends in 2019/20
One of Tryon Solutions' own test automation experts, James Prior, brings you his thoughts on seven notable trends in the test automation industry over the next 12-18 months.
1. Less Low-Level Coding in Automation
The industry has been moving in this direction for a while now, as the basic goal of testing software isn’t necessarily to produce a lot of code but to make the application under test better by identifying defects and ensuring that it meets user requirements. The push for less coding in testing is due to developers being relatively expensive, programming (especially at a low-level) generally taking more time, and readable scripts promoting collaboration while usually being easier to maintain. I’m hesitant to throw around the term “codeless automation” which I see promoted from time-to-time, but certainly “the powers that be” in the automation space have recognized the advantages of making the process of automating test cases easier and potentially faster.
2. Increased Adoptions of Behavior-Driven Development
Testing teams that employ behavior-driven testing solutions and practices are reaping the benefits, and so BDD adoption continues to surge in popularity. It just started getting traction in the mainstream a handful of years ago, and now many of the newer test automation solutions and tools on the market are either BDD or have some BDD components. The collaboration benefits alone are too big to ignore.
3. Continued Rise of Continuous Testing
The never-ending, relentless push for shifting testing left and overall need for efficiency improvements in software development, delivery, and operations (DevOps) will ensure that both continuous testing as an approach and the related CI/CT tools are destined for huge growth. I conduct technical demonstrations for Cycle, our test automation solution, and in recent months I’ve noticed a drastic increase in questions on whether or not our product is compatible with the popular CI/CT tools on the market. The answer, by the way, is that Cycle pairs nicely with all of them. At Tryon, we happen to have a growing fondness for Jenkins:
4. Containers Won’t be Contained
Containerized environments are just too handy of a packaging mechanism for testing teams to not take advantage of, especially when the application in test is large and complex with many dependencies. We’ll see no shortage of companies cranking out their own Docker-like containerization tools in late 2019 and into 2020.
5. Smarter Versions of Everything
So you noticed that I went with “Smarter Versions” as opposed to saying “AI” or “Machine Learning”, and here is why I am careful with terminology: Imagine the human race another two-hundred years down the road (assume no apocalypses came to pass, asteroid, zombie, or otherwise) and what level of artificial intelligence must exist by then; would we look back and consider fancy algorithms that search for the correct XPath to be genuine artificial intelligence? Despite my being overly careful at what I deem to be real “AI”, a lot of very cool smart automation features that are being pitched as AI are either in their infancy or coming very soon that will prove extremely helpful to anyone in the test automation field. My three personal favorites are:
Ability to Self-Heal – Small things that break a test script can drive testers crazy and waste valuable time. A self-healing mode that detects errant changes in say automation IDs or web elements and automatically finds the correct one would be a huge boon for executing as well as maintaining test scripts.
Mimic Actions and Paths of Real-World Users – Currently there are “crawlers” that will automatically test out buttons and fields in a web application and smart recorders that can create a script just by watching a manual test. A more helpful step up from that would be the ability to completely test all of the functionality found throughout a wide variety of common user paths just by watching a few passes from a human manual tester; this is essentially “machine learning”.
Machine Learning for Visual Validation – I’m less familiar with UI visual validations, but I certainly respect the potential advantages as it is currently difficult to automate visual tests. An automated tool based on machine learning (or again, what we currently call “machine learning”) that is designed to look for differences in a UI and its elements should be able to more precisely find defects that human testers could miss.
6. Big Testing Companies Continue to Swallow Smaller Ones
This happens in all industries, and the testing space is certainly not immune. I believe it's concerning, as less competition is a bad thing and the perpetual acquiring of technologies makes for more clunky, cobbled together “suites of tech” rather than seamless solutions designed intentionally from the ground-up.
7. Integrations Remain Key
In addition to a main test automation solution, testing teams will often have a few supplemental tools that help manage projects, analyze test analytics, track bugs, and other testing tasks. With the ongoing need for speed in delivery with the same or better level of quality, solutions with smooth and easy integrations win the day. In response to industry trends, this year we’ve added features to Cycle that make integrations easier. For example, all of the test analytics for a feature execution can be written to a database that can in-turn be easily read-in by test management and defect tracking tools.
Do you agree or disagree? Let us know on social media @TryonSolutions!
This post was written by:
Technical Pre-Sales Consultant
James has been working in software pre-sales and implementation since 2000, and has more recently settled into focusing on technical pre-sales. He takes care of our hands-on demonstrations, and eagerly awaits your request to see our Cycle test automation software in action. Drop him a line at: james.prior[at]tryonsolutions[dot]com.
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