Technology has been the biggest game-changer of our times and has become an integral part of our day-to-day functioning. The evolution of technology has significant implications on our lives, both personally and professionally. We all have become highly dependent on tech-led solutions that make our life and workflow easy. Many tech enthusiasts, as well as tech companies, are inquisitive to understand what the next big tech disruption will bring about and how it will further jolt our lives. One of the key game changers today is artificial intelligence (AI).
AI does not require any introduction, as each of us utilizes some form of AI in our daily lives. From a business perspective, almost every organization with an online presence today operates with an active AI mediation. However, in layman language, artificial intelligence is nothing but the replication of human intelligence that is processed by high-tech machines and is programmed to operate like humans and imitate their actions with an aim to reduce or minimize errors as well as free up human time to do more value additional tasks.
AI helps businesses by minimizing manual tasks and automates many processes which require human intervention. But as we move forward, it becomes crucial to stay abreast with the latest developments in the tech led world which is constantly evolving. Today, a lot of businesses are using AI in software testing, as it is a crucial practice that ensures customer satisfaction within a service that they’re using, be it an application or a website. Moreover, having routine AI driven testing can safeguard prospective software breakdowns which otherwise may be disadvantageous, for companies in the long run. Thus, a lot of companies are planning to either set up or have already set up AI testing, to evaluate and scrutinize respective products, platforms, services etc., in order to become aware of the risks and the threshold of the failure involved in its execution.
Implementation of artificial intelligence in software testing
The digital ecosystem which is evolving constantly requires applications to be reliable and flawless, making application testing a crucial part of the business strategy. In such a scenario, the quality of the application matters the most, in terms of performance, functionality and usability that distinguishes businesses from others.
KPMG, a global leader in providing Audit, Tax and Advisory services, in one of the industry articles, stated that ‘AI helps to evaluate business-critical algorithms, puts testing controls in place, and oversees the design, implementation and operation of Al programs to help address inherent challenges: integrity, interpretability, fairness and agility’. Thus, it is of utmost importance that businesses implement AI in software testing of respective services and products.
To ensure better service quality, companies based in India are slowly getting into the process of using AI in software testing and development. However, the practice is still at the nascent stage and the amount of autonomy that is required to reduce manual efforts is at the lower level. Nevertheless, organizations are realizing the fact that automating manual test processes with the right tools and technical know-how is the need of the hour, to accelerate and improve the testing cycle thereby increase the ROI.
Here are the 3 top trends for testing with the help of artificial intelligence
- Self-healing tests: With self-healing, any property changes are automatically sensed, and the internal scripts are self-healed during a runtime. Today, in reference to the user interference (UI), self-healing tests aren’t far-fetched practices anymore but a reality. Sometimes technical glitches happen when an object/product changes its locations, here self-healing tests come into play and make the UI locator more functional in terms of identifying the path analyzer, which is not likely to happen otherwise during object mobility. There are more developments happening in the self-healing space and businesses could expect further innovations in the coming days.
- Smart Automation Execution: Whenever there’s a chance of potential application breakdown or production failures, based on previous data, AI engine promotes code or highlights features using smart algorithms that decides if the code could be processed or not. Additionally, to decrease the chance of application breakdowns or failures, AI could recommend the use of specific methods from the code repository. To automate quality gates, automated code repositories are maintained for different projects based on their individual success ratio.
- Autonomous Testing: AI, precisely, machine learning has been a game changing practice in regard to autonomous software testing, as it can detect errors and perform build, eventually speeding up the developments of product test cases. In the past years, identifying bugs with multiple reiterations was a long and costly task. Automation Testing has practically improved overall test coverage and performance of the applications, as it takes less time to fix technical glitches and is faster and accurate, thus saving a good amount of time and cost.
In conclusion, to cope up with new-age business modifications, and to meet the objectives that are outlined in terms of technological aspects, companies must implement AI for testing, with the objective to run the business operations smoothly, as the more we use applications, the more there is the need to test them on a regular basis, to provide internal and external stakeholders a seamless experience while conducting business.
By Niraj Hutheesing, Founder and Managing Director, Cygnet Infotech