How AI Boosts Software Testing Productivity

With the competitiveness that exists in today’s market, companies are on the lookout for any advantage they can get over their competitors. Bolstering software testing productivity with automated testing is beginning to seem like the logical best place to begin for many.

These days, it isn’t uncommon to see businesses bring forward new software all with the help of free tools, open-source software, and a large pool of international developers. We’d argue that the limit to market entry doesn’t exist anymore and this has an influence on the market itself, where saturation with the latest software and applications is at an all-time high. In such a competing landscape, how can you assure your product stands out?

On average, it takes a company about four months to create custom software. However, releasing functional software without any quirks takes about nine months. This begs the question: if the development is typically finished in four months, why is there a discrepancy of five added months before release? The answer: Quality Assurance.

What Makes Traditional QA Testing Difficult

Most seasoned software engineers can attest to the truth that “traditional QA” was a nightmare to manage for most. This sparked the requirement for newer software testing tools with the latest tech to try and reduce the pain for said engineers.

For instance, let’s try and learn how many tests QA needs. Mind you, these tests are incredibly time-intensive to create and run. The software your build needs thousands of lines of code to work. Now, to test the software your team developed, you’d need more code than the software itself – all the while attempting to debug the tests while debugging the code. This generates a painfully meticulous cycle of engineers attempting to figure out whether a bug was in the code, test, or both. 

To top it all off, the simple matter of truth is this: the more complicated your software is, the more test cases you’ll require to develop. One deceptively simple feature can justify tens of test cases, which in turn can need hundreds of lines of new code for every unique test case. And maintenance is needed on the number of tests too, all the while assuring that product software is maintained along with the tests. It can also appear upon some test engineers that their position in this entire concoction is to archive tests and try and untangle a hideously intertwined jumble of code.

Due to the presence and implementation of traditional QA testing, software teams find themselves regularly managing massive amounts of code. Surely, once all the tests are built, the process is streamlined, yes? Not quite.

A common mistake with QA tests is that they’re robust. That isn’t the case in the smallest. A minor change to the source code could cause the tests to flag false decisions or, in some instances, crash the system entirely. Even something as small – and irrelevant – as changing the font style may appear in the tests flagging your software as damaged, so bigger changes require to proceed with a lot of caution, to say the least.

To conclude, software QA testing done wrong isn’t just ineffective, it’s downright painful. A corporation loses productivity not just to time used testing but also to a miserable QA team. As a result, one of the easiest ways to improve overall productivity is to enhance software testing productivity. Turns out, there are software testing tools available to today’s engineers to attempt to do just that. At least mostly. 

The Problem with Testing Tools Today

During development, periodic testing enables developers to examine the software functions, search for bugs, and have their eyes on the end product. The aim is to set the standard of the software. There’s particular freedom during this kind of unit testing that feeds into the drive for test automation.

Comprehensive QA testing is another obstacle in itself. As discussed above, it’s dense, crushingly large, and incredibly brittle. QA testing needs random “black box” inputs. QA testing also has got to use each feature in each possible way. This testing has to ensure the quality of the whole product. It ultimately comes down to the difference between developing a puzzle and checking a private puzzle piece for the goodness of fit and adjustment.

Because of QA testing’s purpose and scope, it’s very difficult to automate in a way that strengthens overall productivity. There are software testing tools that exist, and that does help with generating test scripts. But these characteristics alone aren’t enough. A worthwhile QA testing tool requires to:

• Curate test scripts.
• Execute scripts and log results.
• Save individual test runs for replay later.
• Update test scripts automatically when situations change.

Tools capable of the primary two jobs are out there today, like Selenium. However, tools that will actually boost software productivity require doing all four. These tools aid QA testing by having a library of scripts and recording simple test cases. What they can’t support is automating the general testing process and acquiring from the test results.

Automated Software Testing 

The basic dilemma with QA testing is this: how are you able to accomplish a core set of test scripts that learn as they test and update themselves when needed? Or to put it differently, how am I able to generate a self-healing test process? The answer is machine learning.

Combining the power to review with the power to record tests is truly important to increasing productivity. A testing tool must take the test scripts and develop them with the software, not rewrite them whenever the software modifications. Testing offers an incredible amount of data. If you’re saving the outputs, why not use them to show the scripts? Rather than filing these data away for later analysis, actively utilize them to highlight and refresh your tests.

TestUnity enhances software testing productivity by assuring thorough test coverage, intuitive workflows and interface, and most of all, automation at your fingertips. We provide the testing services on-demand, serve with projects of any scale, and are ready to start with a few days’ advance notice. Choose to team up with a QA services provider like TestUnity. Our team of testing experts specializes in QA and have years of experience implementing tests with different testing software. Get in touch with a TestUnity expert today.

TestUnity

Testunity is a SaaS-based technology platform driven by a vast community of testers & QAs spread around the world, powered by technology & testing experts to create the dedicated testing hub. Which is capable of providing almost all kind of testing services for almost all the platforms exists in software word.