AI-powered Next generation Test Automation Framework

Next Generation Software Testing Services

The quality of a software application in today’s fast-paced world is judged by its features and frequency of fresh upgrades. New-age apps in industries targeting Gen Z like online gaming, sports prediction, financial trading, and retail pose twin challenges of frequent upgrades and handling voluminous data. Software testing methodologies thus have to be equipped with next-gen tools to make testing proactive, quick, and highly accurate.

This is why agile methodologies, Artificial Intelligence (AI), and Machine Learning (ML) are a no-brainer for software testing today. Next generation Testing services have to work with the twin goals of speed and precision while handling huge workloads, making smarter Test Automation indispensable.

AFTA 4.0- Answering your need for a modern Testing service

AFTA or Aspire’s Framework for Test Automation is a carefully crafted home-grown Test automation framework powered by Artificial Intelligence and Machine Learning (AI-ML) components with self-healing test scripts. Incorporated with Selenium, AFTA 4.0 aids organizations perform test automation right from the start of the development cycle, adding more power to Agile and DevOps driven environments. Combining the aspects of problem-solving, reasoning and machine learning based on repetitive patterns, AFTA 4.0 can help you find and repair your defects in record time.

How AFTA 4.0 is better than AFTA 3.0:

The latest version of AFTA has a couple of features that build on its predecessor in saving testing efforts as well as accuracy.

1. Automated Page Object Model (POM)

AFTA has a feature to automatically prompt for a pop-up during navigation and capture the elements from the UI. Locators are also automatically collected from the UI application on the pages it interacts with. Web scraping with Selenium allows and gathering of required data using Selenium Webdriver Browser automation. It crawls the targeted URL webpage and gathers data at scale. This collection of data locators improves upon the self-healing capabilities of AFTA.

2. Data faker:

Test data will be common for domain-specific applications. For instance, all banking applications will have an account number, name, IFSC code, etc. This concept is similar in medical or telecom. The data faker feature creates random test data which is common across domain-specific applications which need not be freshly captured. This can be a time and effort saver for testing domain-specific applications

Key Features of AI-ML powered Test Automation Framework AFTA 4.0

Rapid testing using self-healing scripts aiding faster go-to-market with minimal errors

Seamless extension across varied user experience platforms and manages functional as well as cross-browser testing

Security testing with inherent penetration checks through active and spider scans that prevents vulnerability attacks and ensures data protection.

Performance testing involving testing response time, throughput thereby assessing basic Non-Functional parameters of the UXP by reusing the automation scripts