The 2018 Software Testing Year In Review

 In Blog, Agile & DevOps Testing, Test Automation News

The 2018 Year In Review – In the Software Testing Industry

There you have it, another year has gone by. It’s time to look back and discover what we accomplished. We, the software testing industry, had a prosperous year full of new and reinforced trends, successful acquisitions, and a great deal of funding. See this year’s funding and acquisitions below in our infographic, made specifically for you.

The 2018 testing arena garnered up more than $300M worth of funding. The timeline, below, indicates this year’s announced investments and acquisitions. All information given are the disclosed amounts and news.   

2018 year in review

2018 Software Testing Trends

The biggest change in our industry is the implementation of AI and ML-based technology, this followed by a normalization of test automation. Let’s look back on those trends that took 2018 by storm.

Machine learning and artificial intelligence in testing

AI and ML are terms heard almost every day in any industry. Whether it is in healthcare, retail, transportation or testing, AI is either feared or adored. This phenomenon is clearly helping industries of all walks of life. Although when it comes to the software testing field, there is still some hesitation and concern. Testing isn’t as straightforward as it once was because of the Agile pace the industry brought on in the past couple of years. The abundance of data to handle has multiplied and the time to release has shortened. Their lies a whole new approach, one allowing the modern tester to handle a continuous workload powered by ml-based tools.

Artificial intelligence and machine learning are slowly but surely becoming crucial segments in QA and in the software testing world as a whole. Machine learning brings more accurate results to the tester and divides time spent on creating and managing test cases in half. For example, TestCraft’s ML-based algorithm is able to automatically overcome changes in the app and keep tests from failing. This allows our platform to overcome 97.4% of the changes in the app (changes that were not caused by a change in the app logic or process). Now testers are following suit on this trend and are opening their eyes to ML-based software.   

Test automation as the standard

In recent years we’ve all heard that test automation is vital to continuous integration. Although test automation has always been part of the conversation it was never truly accepted by all, similar to ML/AI-based tools now, until now. 2018 was the year test automation became the new norm. According to Gartner’s Magic Quadrant for Software Test Automation report, “In 2017, 57% of respondents named Hewlett Packard Enterprise (HPE) when asked “What other vendors were considered?,” followed by Selenium. In 2018, Selenium came out on top with 43% — with the next four vendors coming in between 18% and 24%.” This show more organizations are leaning toward Selenium, test automation, as the most viable solution for their testing teams.

The demand for test automation is exponentially growing because of the time-to-market factor. Artificial intelligence and machine learning are gaining traction for the same reason test automation is the new common practice. Gartner says, “during the next three years, (they) expect that AI, ML, predictive analytics and RPA will play an increasing role in software testing and automation”, and we couldn’t agree more!

Let us know if you have other mentionable trends on any of our social media sites. 2018 LinkedIn 2018 Twitter 2018 Facebook

Happy holidays and have a great new year!

Here are the sources we used to find the data and investments of the testing world: Gartner Magic Quadrant for Software Test Automation, Globes, and Crunchbase

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