A robust and user-friendly software is a pre-requisite to make a mark in the digital economy and build a loyal customer base.  A comprehensive testing mechanism to detect and rectify bugs and check its operability across platforms is imperative to succeed in the cut-throat digital market. A small error that emerges after launch can be the difference between a success story and also-ran.

Quality assurance today also encompasses testing for performance across browsers, operating systems, and devices including mobiles.

It is no secret then that rigorous testing of a software is not simple, but tedious, prone to error and costs money and manpower. But the pressure to release products and updates quickly has forced developers to look for alternatives to legacy testing methods. The quick-fix solution cannot come at the cost of quality too.

Enter Automated Testing.  

Test Automation is an important role of the Quality Assurance team. Like the name suggests, this involves running automated tests using tools which achieves twin goals of speed and accuracy. Another variable is consistency across different browsers, devices, and operating systems. Along with improvement in software quality, automated testing also helps optimize human resources.

Frameworks, like Aspire’s AFTA 3.0, incorporate Artificial Intelligence and Machine Learning (AI and ML) based data analytics in the Test Automation which improves productivity.

Here is a checklist of some important points before embarking on the Test Automation journey. 

Decide which test cases need automation 

The most cumbersome aspect of testing that can be simplified by automation is repetitions. However, not all tests need it.

Automation is necessary only for tests which are repeated, work with a large volume of data and variables, and those where the applications need to be checked across different platforms.

Experts say some tests need only human judgement (legacy testing). Before starting the automation journey, dividing this workflow into such clearly defined categories will curtail unnecessary costs and save time.

Test automation approach 

To build strong test automation cases, choice of the test automation approach is decisive. The approach or framework is a set of guidelines that helps the quality assurance team run tests efficiently. This has a direct impact on the consistency of the software.

There are six kinds of TA framework approaches that are available: Linear automation, library architecture, data-driven, keyword-driven, module-based, and hybrid.

The different test automation approaches are Linear automation framework

Selection of the right tools

A variety of open source as well as commercial tools are available in the market.

The first point to consider while selecting a test automation tool is to ascertain if your software will be run on particular kind of devices (desktop or mobile) and operating system (iOS or Android).

Secondly, the programming language that your testing team is comfortable with is an important variable.

Significance of data

The amount and quality of data that needs analysis is an important indicator of the type of testing needed. Data is the variable that is taken as input during a test. It is usually stored in an external database as it can be used again for future tests, similar or fresh ones for which the data inputs are same. It is usually stored in formats like XML, Xls, etc. Spending time on creating quality data can simplify automated testing which then impacts the quality of the software.

Not a one-woman/man show

Running automated tests is not a one-engineer show. Unless it’s Ethan Hunt. Selecting the right team members is only one part of the job; ensuring that the workflow is divided and everybody is aware of the team’s output is paramount at all stages. This requires involvement and contribution from all members. Before start, a SWOT analysis of their programming skills would not be a bad idea too.

Regular upgrade of tests

One of the USPs of test automation is consistency in results and low percentage of errors. This can take a beating if inconsistencies creep into the system. Worse, the test result might incorrectly indicate an error despite running correctly. This phenomenon is known as a false positive.

These can be avoided by regular upgradation of the tests by checking its validity.

With Aspire’s Artificial Intelligence (AI) led framework AFTA 3.0, your testing efforts can reduce by 90 percent with a six-week roadmap.

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