AI, ML and the Amazing Future of Software Development
Quality Assurance teams are the unsung heroes behind each and every successful experience you have with your favorite app. Their hard work in software development is what allows mobile device users to rely on their apps in their everyday lives – from making sure that all features operate seamlessly through every release and update. These problem-solvers aim to make your user experience as smooth as possible.
When your morning alarm clock chimes, you check the weather forecast or text a friend – it is due to these overlooked heroes that we owe our gratitude.
And if the efforts of a team fail to meet expectations, they will undeniably receive negative criticism from users who are not shy about voicing their opinions on popular and highly visible review sites.
Today’s mobile app user expects nothing less than absolute perfection, so it is the responsibility of Quality Assurance teams to ensure a flawless product each time they deploy.
With the evolutionary journey of software development, it is sensible to presume that software will remain intricate and demand thorough testing. But do we have to endure this? Are we destined for a continuous need for more personnel and larger Quality Assurance teams?
Manual Testing of the 80s in Software Development
To comprehend how we’ve come to this point, it’s necessary to rewind all the way back to the 1980s. During that time period, software QA teams heavily relied on manual testing of their products before releasing them into the open market and confirming if they worked properly.
Time was less complicated, and the capabilities of technology were limited. Thus, manual coding became a popular method for testing. Though tedious work that consumed plenty of time when done correctly, it provided testers with an effective way to assess procedures.
Technology, ever-evolving and consistently advancing revolutionized the testing process with automation. The software development and design was now more intricate and advanced than ever before.
Coded Test Automation: 90s to the late 2010s
Within the following decades, progressions in testing emancipated QA testers from having to manually labor through test cases. They no longer needed to detect mistakes concealed amidst unorganized code snippets.
In the fight against software development issues, they uncovered a new weapon: manual testing on a large scale was no longer an option. Thus, if any Quality Assurance (QA) team wanted to test and review possible releases in an expedient manner, automation tools were essential for running test scripts.
So, is the fight against complexity over? Not quite. It might be better to view automated testing less as a game-changing evolution and more like another phase in the battle with software’s ceaselessly expanding intricacy.
With time running out and no definitive success on the horizon, automated testing lagged behind as software and mobile applications exponentially grew in use and became integral parts of our daily lives. Fortunately, what we had all been anticipating was just around the corner – a real revolution!
No-Code Test Automation of the 2020s
Until recently, QA testing teams in software development were in a difficult situation. Automated testing necessitating ever-evolving complex code apparatuses meant that these teams had to assign more and more programmers solely for the purpose of testing, leaving less personnel available to develop new features.
Not only did this drive up costs, it further delayed the product launch. Nonetheless, a botched release could cost considerably more than what was spent (case and point: countless broken launches).
For a while, it seemed that the progress of abstraction – where interface-based representations simplify intricate processes (just think of all those ones and zeros powering this article) – would eventually lead to something big. And sure enough, within the past few years, we have seen an emergence of what many specialists have dubbed as “No-Code Revolution.” Its arrival is undeniable!
The No-Code Revolution is very much alive, particularly with the expanding use of what-you-see-is-what you get website editors like Squarespace and Wix. However, there are also more discreet applications, such as Codeville – a no-code testing platform for mobile apps that I created. This type of technology offers solutions across several industries and makes it easier than ever to create user-friendly products without writing complex code.
The no-code revolution is here, allowing everyday people to manage difficult tasks that were previously left in the hands of experts. This shift has liberated specialists and opened up a world of possibilities for businesses across industries – now, more than ever before, we will witness an influx of innovative no-code solutions appearing over the next few months.
AI-Based Self-Testing Software of Future
All in all, the No-Code Revolution is a breakthrough for our times. I strongly believe that the next period of software development and testing should involve AI-based self-testing programs to take us further into automation.
My vision of self-testing software is shared by many. For years, this concept has been discussed as part of the No-Code Revolution. The rapid pace at which technology changes and develops makes it conceivable that intelligent test automation – where testing AI runs without human involvement – will massively expand by 2025.
Harnessing the power of machine learning (ML) and AI platforms allows us to optimize software releases, ensuring both high speed and quality. Thanks to these intelligent testing methods, an increased return on investment can be achieved with ease – as not only does AI replicate human intelligence, but ML enables computers to learn independently of any manual input!
By utilizing deep learning-centered algorithms, Artificial Intelligence and Machine Learning can access data more efficiently. This allows for extracting patterns from the researched information to make better debugging decisions. QA teams will also be able to conduct an extensive list of tests on diverse devices with various form factors thanks to this incredible technology.
Complete self-testing in hours, not days. A true revolution!
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